The Data Science Institute brings together faculty from all seven colleges across campus to work collaboratively in a wide range of topics in foundations and applications of data science. DSI faculty at UD combine expertise in statistics, computer science, mathematics, information sciences and numerous related fields.
Faculty Council | Resident Faculty | Affiliated Faculty | Adjunct Faculty
Leading Data Science researchers and program representatives to drive DSI mission and guide DSI operations with four Working Groups.
Blue and Gold Distinguished Professor, Geography & Spatial Sciences and Biden School of Public Policy & Administration
environmental planning, applied geography, international environmental policy, extractive industries and society, mineral governance
Saleem H. Ali’s research interface with the Data Science Institute involves using data for improving science diplomacy between countries as well as between corporations and communities. As a member of the United Nations International Resource Panel, he has worked with geoscience data and metrics of resource efficiency across the mineral supply chain. His research also considers how qualitative data can be more effectively used in concert with quantitative data in community communication to mitigate conflicts. Professor Ali received his doctorate in environmental planning from MIT, Masters in Environmental Studies from Yale University and a Bachelors in Chemistry and Environmental Studies from Tufts University (summa cum laude).
Co-Chair, Research Working Group
Associate Professor, Political Science & International Relations
Text-as-Data; Politics; Environment; Social Science; Violence
Benjamin Bagozzi is an Associate Professor in the Department of Political Science & International Relations at UD. He also leads the Social Analytics Data Lab (SADL) and is Assistant Director of the Master of Science in Data Science program. His primary areas of specialization are political methodology and international relations. Within international relations, his research and teaching interests include environmental politics, human rights, and the study of political violence. Methodologically, he teaches and conducts research in computational social science, text-as-data, and political event data. His research has been funded by the National Science Foundation, the Knight Foundation, and the Department of Defense, among others.
Professor, Entomology and Wildlife Ecology
Ecological modeling, Remote sensing, Ornithology
Jeff Buler is a Professor of Wildlife Ecology at the University of Delaware (UD). He earned his Ph.D. degree in biology from the University of Southern Mississippi and M.S. degree in wildlife from Louisiana State University. He established the Aeroecology Program at UD in 2011 and has lead the development of novel methods and software to use the national network of weather surveillance radars to study the broad-scale distribution, movement, and habitat use patterns of birds, insects, and bats. His general research interests include 1) modeling wildlife species distributions and habitat relationships over broad geographic scales, 2) assessing wildlife response to habitat restoration/management and anthropogenic development, and 3) studying the behavior and ecology of birds during migration.
Associate Professor, Computer & Information Sciences
Co-Chair, Infrastructure Working Group
High Performance Computing, Machine Learning, Interdisciplinary Science
Sunita Chandrasekaran is an Associate Professor with the Department of Computer and Information Sciences at the University of Delaware, USA. She is also a computational scientist with Brookhaven National Laboratory. She received her Ph.D. in 2012 on Tools and Algorithms for High-Level Algorithm Mapping to FPGAs from the School of Computer Science and Engineering, Nanyang Technological University, Singapore. Her research spans High Performance Computing, exascale computing, parallel programming, benchmarking and data science. Applications of interest include scientific domains such as plasma physics, biophysics, solar physics and bioinformatics. She is a recipient of the 2016 IEEE-CS TCHPC Award for Excellence for Early Career Researchers in High Performance Computing and other SPEC HPG awards.
Professor, Business Administration
Director of IFSA and FSAN program
Co-Chair, Training Working Group
Assistant Professor, School of Nursing
Professor, Behavioral Health and Nutrition
Graduate Director, Health Behavior Science Programs
Human Aging, Diabetes Mellitus, Chronic Kidney Disease, Biostatistics, Bioinformatics
Adam Davey is a Professor of Behavioral Health and Nutrition and Graduate Director of Health Behavior Science Programs. He is also Affiliated Faculty for the Center for Bioinformatics and Computational Biology. Previously, he served as Associate Dean for Research in the College of Health Sciences. Prior to joining the University of Delaware, Dr. Davey was Professor and Founding Chair in Temple University’s Department of Epidemiology and Biostatistics within the College of Public Health and held a secondary appointment in the Center for Data Analytics and Biomedical Informatics in Temple’s College of Science and Technology. Davey also brings more than 20 years of experience with data management and analysis including latent variable mixture models and bioinformatics.
Associate Professor, Applied Economics and Statistics
Shanshan Ding is an Associate Professor of Statistics in the Department of Applied Economics and Statistics at the University of Delaware. She is a faculty council member at the Data Science Institute, and an affiliated faculty member with the Center for Bioinformatics and Computational Biology and the Center for Experimental and Applied Economics at UD. Prior to joining UD, She received her PhD degree in Statistics from the University of Minnesota-Twin Cities. Her research interests include dimension reduction, high dimensional and big data, statistical machine learning, statistical foundations of data science, application problems stemming from online learning, network data, bioinformatics, neuroimaging, biomedical and environmental sciences.
Assistant Professor, Mathematical Sciences
statistical methods in evolutionary biology; Bayesian methods; interpretable/explainable AI
Vu Dinh is an assistant professor in the Department of Mathematical Sciences, University of Delaware. His research focus on applied probability/statistics and phylogenetics, with an emphasis on the developments of next-generation methods for phylogenetic inference.
From 2015-2017, he was a post-doctoral research fellow at Fred Hutchinson Cancer Research Center (Seattle, WA). He received his PhD in 2014 from Purdue University, working on computational methods for experimental design and control of biological systems. He earned his bachelor degree in 2008 from the University of Science (Ho Chi Minh City, Vietnam).
Associate Professor, Public Policy & Administration
Associate Professor, Physics & Astronomy
Resident Faculty Representative, DSI Faculty Council
Urban Science; Data Science; Complex Systems
Dr. Dobler is currently the Director of the “Urban Observatory” (UO; cuspuo.org), a multi-institutional facility designed to study complex urban systems through remote imaging. His expertise is in image analysis, computer vision, time series, statistical analysis, and mathematical modeling of large data sets. As the Director of the UO, he applies data analysis techniques from astronomy, computer vision, and machine learning to images of urban skylines to study air quality, energy consumption, lighting technology, public health, and sustainability. In addition, he has led data analysis projects related to equitable distribution of greenspaces, mapping long timescale economic trends across cities, and surrogate measures for traffic safety. Prior to his work on urban systems, Dr. Dobler was an astrophysicist specializing in multi-wavelength, full sky data sets from radio to gamma-ray energies, and led the discovery of one of the largest structures in the Milky Way.
Co-Chair, Infrastructure Working Group
Professor, Electrical & Computer Engineering
Director, Center for Data-intensive and Computational Science (DiCoS),
high-performance computing, parallel programming methods and tools
Rudolf (Rudi) Eigenmann came to the University of Delaware in2017 from Purdue University, where he was a Professor in the School of Electrical and Computer Engineering. From 2013-2017, he has also served as Program Director in the National Science Foundation’s Office of Advanced Cyberinfrastructure. His core research interests include optimizing compilers, programming methodologies, tools, and performance evaluation for high-performance computing, as well as the design of cyberinfrastructure. Dr. Eigenmann received his Ph.D. in Electrical Engineering/Computer Science from ETH Zurich, Switzerland.
Professor, Accounting and Management Information Systems
Machine Learning/AI, Business Analytics, Data Science, Social Network Analytics, FinTech
Xiao Fang is Professor of MIS and JPMorgan Chase Senior Fellow at Lerner College of Business & Economics and Institute for Financial Services Analytics, University of Delaware. His current research focuses on financial technology, social network analytics, and health care analytics, with methods and tools drawn from reference disciplines including Computer Science (e.g., Machine Learning) and Management Science (e.g., Optimization). Professor Fang co-founded INFORMS Workshop on Data Science in 2017. He currently serves as an Associate Editor for INFORMS Journal on Data Science.
Associate Professor of Operations Management, Business Administration
Bayesian Data Science
Adam Fleischhacker is an Associate Professor of Operations Management at the University of Delaware. After a highly successful industry career designing supply chain software, he earned his Ph.D. in supply chain management from Rutgers University in 2009. His current research focuses on unifying narrative, math, and code to accelerate Bayesian-based analytics workflows. He has made these concepts student-accessible in his textbooks, “A Business Analyst’s Introduction to Business Analytics”, and “Persuasive Python” (forthcoming).
Co-Chair, Networking & External Relations Working Group
Professor, Physics and Astronomy
Associate Director, Data Science Institute
astronomy, physics, astrophysics, LSST
John Gizis is an observational astronomer in the Department of Physics and Astronomy and co-chair of the Large Synoptic Survey Telescope (LSST) Stars, Milky Way and Local Volume science Collaboration. The LSST will collect 15 terabytes of optical astronomy data per night and a key example of how astronomy is being transformed by the need for new data science methodology.
Professor and Director, Epidemiology
Disaster; Public Health; Epidemiology; Outbreaks and Pandemics
Jennifer Horney is Professor and Founding Director of the Program in Epidemiology and Core Faculty at the Disaster Research Center at the University of Delaware. Dr. Horney’s research focuses on measuring the health impacts of disasters. She received her PhD in Epidemiology and MPH from the UNC at Chapel Hill. She has led interdisciplinary research projects funded by the NIEHS, NSF, the National Oceanic and Atmospheric Administration, the Department of Homeland Security, the U.S. Department of Agriculture and other federal, state, and local agencies. Dr. Horney was a member of a team of public health practitioners who responded to Hurricanes Isabel, Charley, Katrina, Wilma, Irene, and Harvey where she conducted rapid assessments of disaster impact on the public health of individuals and communities. She has also provided technical assistance to public health agencies globally around disasters, emerging infectious disease outbreaks, and pandemic influenza planning and response.
Professor, Chemical and Biomolecular Engineering
Professor, Materials Science and Engineering
Soft Materials, Polymers, Computational Materials Design
Arthi Jayaraman is a Professor in Chemical and Biomolecular Engineering and Materials Science and Engineering at the University of Delaware. She is also an editor for two ACS journals – Macromolecules and ACS Polymers Au. She received her Ph.D. in Chemical Engineering from North Carolina State University and conducted her postdoctoral research in Materials Science and Engineering at UIUC. After holding the position of Patten Assistant Professor in Chemical and Biological Engineering at University of Colorado (CU) at Boulder, in 2014 she joined UD. Her research expertise is in the development of modeling, theory, simulation, and machine learning methods and their application to study synthetic and biologically relevant soft materials. Her research has been recognized with the AIChE COMSEF Impact Award (2021), American Physical Society (APS) Fellowship (2020), Dudley Saville Lectureship at Princeton University (2016), ACS PMSE Young Investigator (2014), AIChE COMSEF division Young Investigator Award (2013), CU Provost Faculty Achievement Award (2013), and the DOE Early Career Research Award (2010).
Co-Director, Center for Research in Education & Social Policy
Associate Professor, Human Development and Family Sciences
rigorous evaluation research, nutrition, obesity, food insecurity, public health
Dr. Karpyn is co-director of the Center for Research in Education and Social Policy (CRESP) and associate professor of human development and family sciences at the University of Delaware. She also holds adjunct faculty positions at the University of Pennsylvania and Thomas Jefferson University and is an associate fellow for the Center for Public Health Initiatives at the University of Pennsylvania. Prior to joining UD, Karpyn served as the director of research and evaluation at The Food Trust in Philadelphia for 11 years, where her research focused on understanding healthy food purchasing and consumption behavior, especially among children.
Dr. Karpyn is committed to informing policy and practice with rigorous research designs. Her current research efforts include the study of corner store programs in urban areas and in-store marketing approaches in supermarkets to promote purchase and consumption of healthier options.
Professor, Geography and Spatial Sciences
Director, Center for Environmental Monitoring and Analysis
Delaware State Climatologist,
environmental, sensing, data integration
Dr. Leathers serves as a Professor in UD’s Department of Geography, as Delaware’s State Climatologist, Director of the Center for Environmental Monitoring (CEMA) and analysis, Director of the Meteorology/Climatology Program, and is the co-Founder and Associate Director of the Delaware Environmental Observing System (DEOS). He has also served as the Chair of the Department of Geography and as Deputy Dean of the College of Earth, Ocean, and Environment. His major research interests include understanding the role of snow cover in the global climate system, and environmental monitoring.
Co-Chair, Networking & External Relations Working Group
Associate Professor, School of Education
Director, Center for Research in Education and Social Policy
Conduct rigorous research, program evaluation, policy analysis
Henry May, Ph.D. is director of CRESP and associate professor in the College of Education and Human Development at the University of Delaware. Prior to joining the UD faculty in 2012, Dr. May spent 14 years as a policy researcher at the University of Pennsylvania, including 10 years as a senior researcher and statistician at the Consortium for Policy Research in Education (CPRE). He has served as principal investigator or co-PI on several large-scale studies in educational settings, many of which involved mixed-methods randomized field trials. Dr. May has taught advanced statistics courses to graduate students at the University of Pennsylvania and the University of Delaware.
Associate Professor, Philosophy Dept. and Biden School, and Director of CSEPP, Philosophy
Director, Center for Science, Ethics & Public Policy
Ethics of AI, Machine Ethics, Research Ethics
Thomas M. Powers received a B.A. from the College of William and Mary and a Ph.D. from the University of Texas at Austin. He has been a DAAD-Fulbright fellow at the Ludwig-Maximilians-Universität in Munich, Germany, an NSF research fellow in the School of Engineering and Applied Science at the University of Virginia, and a visiting researcher in the LIP6 (informatics laboratory) at the Sorbonne University in Paris, France. He is currently Associate Professor of Philosophy and the founding director of the Center for Science, Ethics, and Public Policy at the University of Delaware, and a faculty affiliate of the Data Science Institute, the Delaware Biotechnology Institute, the Sociotechnical Systems Center, and the Center for Autonomous and Robotics Systems, all at UD. His research and teaching focuses on ethics in science and in information technologies.
Professor, Marine Science and Policy
Deep Learning, marine robotics, geophysical sensors
Art Trembanis is a professor of oceanographer at the University of Delaware where he develops and utilizes advanced autonomous systems to map and explore oceans and lakes around the world filling in blank spots on the map. For more than 20 years he has specialized in the use and development of advanced technologies for seafloor mapping particularly AUVs (autonomous underwater vehicles) and geophysical sensors used to map and locate shipwrecks and aircraft wreckage. He is a fellow of the Explorers Club and has led seafloor mapping expeditions in locations around the world utilizing . Exploration projects have included discoveries of ancient shipwrecks to modern aircraft and studies of seafloor scour and object detection. He is the Deputy Director for the Center for Autonomous and Robotic systems and co-founder of the Robotic Discovery Laboratory.
Professor, Plant and Soil Sciences
biogeosciences, ecosystem ecology, environmental networks, climate change, environmental data science
Rodrigo Vargas is a Professor in the Department of Plant and Soil Sciences at UD. He has developed an active interdisciplinary and internationally recognized research program focused on advancing carbon cycle science. He studies soil-plant-atmosphere interactions to understand and quantify the response of ecosystems to management, extreme events (e.g., hurricanes), and global environmental change. Dr. Vargas applies a wide range of data analytics, time series analysis, and machine learning approaches to understand carbon dynamics across different spatial and temporal scales. He believes that information should be transferable, as well as easily searchable, shareable, and applicable in decision-making across different scientific domains and stakeholders. He completed his PhD at UC-Riverside and a postdoc at UC-Berkeley.
Chair, DSI Faculty Council
Co-Chair, Research Working Group
Professor, Computer & Information Sciences
Founding Director, Data Science Institute
Computational Biology and Bioinformatics Data Science: Protein Informatics, Biological Text Mining and and Natural Language Processing, Ontology and Semantic Computing, Gene-Disease-Drug Knowledge Network Analytics, Artificial Neural Networks and Machine Learning, Cyberinfrastructure
Mary A. S. Lighthipe Chair Professor, School of Marine Science and Policy
Director, Center for Remote Sensing, University of Delaware,
Ocean Remote Sensing, Climate Change, AI, Deep Learning, Remote Sensing Big Data, Coastal and Physical Oceanography
Xiao-Hai Yan, Director of the Center for Remote Sensing at University of Delaware (UD), has been appointed the Mary A. S. Lighthipe Chair Professor in 2004. Since he joined the UD faculty in 1990, Yan has pioneered the use of satellites in tracking a wide range of ocean and coastal phenomena, from El Niño to oil spills. In 1992, Yan was the first scientist to show that satellite images, in addition to actual temperatures of the sea surface, could be used to precisely determine the size and location of the Western Pacific Warm Pool, a body of water the size of Africa, spanning the equator from the western Pacific to the Indian Ocean. It holds the warmest seawater in the world. Fluctuations in the warm pool’s temperature have been linked to the onset of El Niño and other large-scale climate events. Yan’s results were published by Science magazine, as well as a range of U.S. and international news media, and have since become a classic reference in climate studies. Y
Strategic faculty hiring across and within colleges in foundational and applications areas of data science, complementing current strengths of 100+ faculty.
Augmented Reality and Immersive Analytics, Embodied Cognition, Multimdal Machine Learning
Roghayeh (Leila) Barmaki is an Assistant Professor at the Computer and Information Sciences Department and affiliated with the Data Science Institute at the University of Delaware. Dr. Barmaki leads the Human-Computer Interaction Lab at the University (https://sites.udel.edu/hci-lab/).
Her research interests span Multimodal Data Analytics, Human-Computer Interaction, Virtual and Augmented Realities with applications in Education and Healthcare.
health, biomedical, artificial intelligence
Rahmat Beheshti is an assistant professor in the Data Science Institute and also the Department of Computer & Information Sciences at the University of Delaware. He has a unique interdisciplinary background by finishing his postdoctoral training in Public Health and his PhD in Computer Science and MSc in AI. He has been working in the area of Health Data Science and Biomedical Informatics for the past eight years. Specifically, he has worked extensively on two major public health epidemics: smoking and obesity, and has focused on very different aspects of these two, including the social, economic, environmental, and lately biological factors that affect these epidemics.
Astronomy Supernovae Energy Time-domain
I am a data-driven scientist working on multi-disciplinary and inter-disciplinary problems. My specialty are lightcurves, time series of light, in astronomy, with applications in stellar evolution, cosmology, and solar system science, and in the urban environment, where the study of urban lightcurves enables sociological, ecological, economic inference.
I study astrophysical transients, particularly Supernovae, exploding stars, trying to understand the progenitors of explosions from the explosion signature.
I am the Large Synoptic Survey Telescope (LSST) Science Collaborations Coordinator: in this role I facilitate the work of the international science community in preparing to the advent of the LSST revolutionary survey, which will take a movie of the entire southern hemisphere sky every three nights down to 24th magnitude depth, delivering tens of Tb of data per night.
Austin J. Brockmeier is an assistant professor in the Department of Electrical and Computer Engineering and the Department of Computer and Information Sciences, and is a resident faculty of the DSI. His research interests center on designing algorithms and models for gaining insights into complex data sets, with applications focused on biomedical signals and text mining. He has worked on machine learning methods to search and organize large collections of scientific references for evidence-based research. He has also worked on new approaches for analyzing brain waves and neural recordings for brain-machine interfaces.
He received a BS in computer engineering from the University of Nebraska–Lincoln in 2009 and a Ph.D. in electrical and computer engineering from the University of Florida in 2014. He then worked as a postdoctoral researcher at the University of Liverpool and the University of Manchester. He is a member of the IEEE and IEEE Engineering in Medicine and Biology Society.
Dr. Zachary Collier holds a dual appointment as an Assistant Professor in the School of Education at the University of Delaware and the Center for Research in Education and Social Policy. Dr. Collier’s area of expertise is the advancement and application of finite mixture modeling, particularly latent class and profile analyses. He also seeks to develop effective and efficient heuristic optimization data-mining-type search algorithms in structural equation modeling and propensity score analysis for emerging data intensive applications in education. These intensive datasets include non-random attrition, incomplete longitudinal data, and selection bias.
Assistant Professor, Plant and Soil Sciences
food systems; sustainability; global environmental change; geospatial data science; nutrition; foreign land investments; human migration
Dr. Kyle Davis is an Assistant Professor in the departments of Geography & Spatial Sciences and Plant & Soil Sciences whose work focuses on food systems, agricultural sustainability, and global environmental change. His current research in India, Nigeria, China, & the US combines environmental, economic, and social considerations with direct stakeholder engagement to inform agricultural decision-making and to improve nutrition, environmental sustainability, & climate adaptation strategies. He also explores other human-environment interactions through projects on: the environmental and livelihoods impacts of large-scale land investments; variability & shock propagation through food trade networks; human migration modelling as driven by anticipated climate change impacts; and farmer coping strategies for climate variability and extremes.
Associate Professor, Physics & Astronomy
Resident Faculty Representative, DSI Faculty Council
Urban Science; Data Science; Complex Systems
Dr. Dobler is currently the Director of the “Urban Observatory” (UO; cuspuo.org), a multi-institutional facility designed to study complex urban systems through remote imaging. His expertise is in image analysis, computer vision, time series, statistical analysis, and mathematical modeling of large data sets. As the Director of the UO, he applies data analysis techniques from astronomy, computer vision, and machine learning to images of urban skylines to study air quality, energy consumption, lighting technology, public health, and sustainability. In addition, he has led data analysis projects related to equitable distribution of greenspaces, mapping long timescale economic trends across cities, and surrogate measures for traffic safety. Prior to his work on urban systems, Dr. Dobler was an astrophysicist specializing in multi-wavelength, full sky data sets from radio to gamma-ray energies, and led the discovery of one of the largest structures in the Milky Way.
Geospatial Data Science, Machine Learning, Human Dimensions of Global Change, Sustainability
Jing Gao is an Assistant Professor in the Department of Geography and the Data Science Institute at UD. Her research investigates large-scale human-environment interactions, especially the relationship between global urban land use, population, and climate change. Trained in Geography and Computer Science, she approaches interdisciplinary scientific inquiries by integrating diverse data, quantitative and computational methods from spatial statistics, machine learning, big data mining, geo-visualization, and remote sensing, with narrative-based scenario analyses of societal development. Her research is generating new insights and datasets on global, long-term, spatially-explicit changes in urbanization and population characteristics, extending the SSP-RCP scenario framework used by the IPCC and the research community for understanding global environmental change impacts, spearheading creative data-science practices in long-term spatially-explicit modeling of socioeconomic processes, and developing new methods for evaluating the uncertainty and the success of such practice.
Remote sensing; GIS; Agriculture; Forest; Climate
Dr. Pinki Mondal is an interdisciplinary geospatial data scientist interested in the dynamics of coupled natural and human systems. She has a PhD in Land Change Science from the University of Florida with research focus on environmental remote sensing and Geographic Information Systems (GIS). Her research projects in India, Viet Nam, eastern USA, and several West African countries have revolved around three themes: (a) agricultural sensitivity to climate variability, (b) adaptation strategies in smallholder agricultural systems, and (c) effects of national-level policies on forestry and conservation. Currently, her research focuses on documenting climate change impacts and adaptation in the low- and middle-income countries. Prior to joining UD, she was a Senior Research Associate at Columbia University in the City of New York. She has taught several GIS-focused courses (both at undergraduate and graduate level) at institutions including Columbia University, the City University of New York, and the University of Florida.
Deep Learning, Transfer Learning, Explainable AI, Human-centered AI
Dr. Xi Peng works in the area of Machine Learning, Deep Learning, and Computer Vision. His research focuses on structure and model-oriented deep learning. The goal is to develop frontier AI systems that are not only robust to unknown but also explainable for human.
Currently, he is making efforts to cross-disciplinary data analytics including workspace safety enhancement (biomechanics), biomarker based pain prediction (biochemistry), and multimodal human behavior analysis (psychology/linguistics).
He received the Ph.D. degree in Computer Science from Rutgers University in 2018. He was a research intern at NEC Labs America in 2016, a research intern at IBM T.J. Watson Research Center in 2015, and a full-time engineer at Baidu Research in 2011.
Cencheng Shen received the BS degree in Quantitative Finance from National University of Singapore in 2010, and the PhD degree in Applied Mathematics and Statistics from Johns Hopkins University in 2015. He worked as a visiting assistant professor in the Department of Statistical Science at Temple University from 2015 to 2016, re-joined Johns Hopkins University as an assistant research scientist in The Center for Imaging Science from 2016 to 2018, and is currently an assistant professor in the Department of Applied Economics and Statistics at University of Delaware. His research has been funded by NSF DMS, DARPA SIMPLEX, and DARPA L2M.
Data Science related faculty from UD and affiliated institutions.
Data Science, Graph Neural Networks, Computation Imaging
Dr. Gonzalo Arce’s fields of interest include computational imaging and spectroscopy, signal processing, machine learning, and data science. His active fields of research are: compressive sensing, computational imaging, graph neural networks, and graph signal processing. He is the Charles Black Evans Professor of Electrical and Computer Engineering and the JPMorgan Chase Faculty Fellow at the Institute of Financial Services Analytics. He is a Fellow of the IEEE and SPIE. He holds over fifteen US and international patents.
mathematical cognition; mathematics attitudes; mathematics learning; algebra learning; mathematics instruction
Dr. Christina Areizaga Barbieri is an Assistant Professor at University of Delaware’s School of Education within the Educational Statistics and Research Methods Ph.D program and the Learning Sciences specializations. Dr. Barbieri’s research program is situated within the field of mathematical cognition. Specifically, her work focuses on applying and evaluating the effectiveness of instructional strategies and materials based on principles of learning from cognitive and learning sciences on improving mathematical competencies. Dr. Barbieri also considers the development of positive mathematics and beliefs within the classroom and their role in learning. Born and raised Latina in New York, Dr. Barbieri is particularly concerned with mathematics instruction and learning opportunities in school settings that serve primarily BIPOC students as well as how variations in these opportunities may impact math attitudes and beliefs.
Signal processing, machine learning
Kenneth E. Barner is the Charles Black Evans Professor of Electrical Engineering. His research interests include statistical signal and image processing, nonlinear and sparse signal processing, machine learning, and human-computer interaction, with an emphasis on information access for individuals with disabilities. He received a bachelor’s degree in electrical engineering (magna cum laude) from Lehigh University and master’s and doctoral degrees in electrical engineering at the University of Delaware. Prof. Barner, who joined the UD faculty in 1993, is a Fellow of the IEEE. He has served as associate editor for numerous signal processing journals and was the Founding Editor in Chief of the journal Advances in Human-Computer Interaction. He is a member of Tau Beta Pi, Eta Kappa Nu, and Phi Sigma Kappa.
health economics, labor economics
Emily Battaglia is an economist interested in health and labor economics with a particular focus on understanding the effect of policies on minority groups. Her research has studied issues such as racial inequalities in the labor market and the effect of immigration policies in the labor market. In addition, she also researches how policies impact maternal and infant health. Prior to joining the University of Delaware as an assistant professor of economics, Dr. Battaglia received her Ph.D. in economics from Princeton University, and her B.S. in economics and math and B.A. in Spanish from Penn State University.
hospitality marketing, consumer psychology, digital marketing & research methods
Srikanth Beldona is a professor and the graduate director in the Department of Hospitality Business Management at the Alfred Lerner College of Business and Economics. He earned his Ph.D. from Purdue University and an MBA from the University of Newcastle, Australia. His focus of research is in consumer psychology as it relates to hospitality-based experiences and digital marketing in hospitality and travel. He has published over 65 articles/papers that have appeared in journals such as the Cornell Hospitality Quarterly, Journal of Travel Research, Tourism Management and the International Journal of Hospitality Management among others. He was the guest editor for the Journal of Hospitality and Leisure Marketing’s 2008 special issue titled “The Impact of Technology on the Marketing of Hospitality and Travel Services.”
Beldona is a member of the Editorial Board for the Cornell Hospitality Quarterly. He was honored as one of 2015’s Top 25 Most Extraordinary Minds in Hospitality Marketing.
Big Data, Motor & Social Communication in ASD
My research examines the relationship between motor and other system impairments in children with Autism Spectrum Disorder (ASD). Currently I am working on 3 projects: a) motor differences in children with ASD, b) effects of creative and general motor interventions in children with ASD, and c) more broadly the services received by children with ASD and how those were negatively impacted following the COVID-19 pandemic. My lab visualizes and analyzes large datasets in children with autism and related disorders. I am looking to work with students who are interested in applying data visualization and analytical approaches to understand long-term trends in quantitative and qualitative datasets with the broader goal of understanding patterns of impairment and how that impacts daily functioning and future outcomes of children with developmental disorders.
Metabolic Engineering, Protein Engineering, Biomanufacturing, Synthetic Biology, Systems Biology
Biological systems have been used for the production of value-added compounds for centuries; however, our ability to read and write DNA make it possible to engineer biology to far exceed its natural capabilities. My research group addresses big problems in sustainability, human health, national defense, and space exploration – using synthetic biology, metabolic engineering, genomics & systems biology, and protein engineering. We work mostly in eukaryotic systems (non-model yeast and mammalian cells) as well as bacteria. We are increasingly interested in the use of systems-scale data for better informing biological design decisions.
Classification models, Calibration models, Chemical Sensors, Hyper-Spectral Imaging, Spectroscopy
Karl Booksh is a Professor in the Department of Chemistry and Biochemistry. He has been at the University of Delaware since 2007 after serving on the Arizona State University faculty for a decade. His research interests include the development of chemometric and machine learning strategies for calibration and classification with chemical instrumentation. Of particular interest are methods for hyper-spectral image analyses and analyses of data from multivariate sensors. Booksh is a Fellow of the American Chemical Society and a Fellow of the Society for Applied Spectroscopy.
plasma, nuclear fusion, astrophysics
Dr. Arijit Bose joined the Department of Physics and Astronomy at UD in 2021. Prior to which he was a postdoctoral associate at MIT – Plasma Science and Fusion Center and at UMich. Arijit received a PhD in physics from the University of Rochester in 2017 and a BSc (Hons) physics from the Chennai Mathematical Institute. Arijit received the F. J. Horton Graduate Research Fellowship to conduct his doctoral research on inertial confinement fusion at the Laboratory for Laser Energetics (LLE). LLE houses the Omega laser facility, which is a unique national resource for High-Energy-Density Physics experiments. Arijit’s research involves using high-power lasers, like the National Ignition Facility at Lawrence Livermore National Lab, or pulsed-power systems, like the Z-machine at Sandia National Lab, to study matter at extreme conditions produced in astrophysics phenomenon in the universe and in nuclear fusion energy research.
Director, MS in Data Science
After earning bachelors and masters degrees in mechanical engineering, Dr. Braun earned his PhD in applied mathematics from Northwestern University. He was then an NRC postdoctoral fellow at the National Institute of Standards and Technology. Following his postdoc, he joined the Department of Mathematical Sciences at UD in 1995. He has been funded via the NSF and industrial sources, supervised postdocs, graduate and undergraduate students, and collaborated with a wide variety of scientists and engineers. His recent research has focused on tear film dynamics and blinking.
Neuroimaging, motor control, Parkinson’s disease, healthy aging
Dr. Roxana Burciu is a neuroscientist and an Assistant Professor in the Department of Kinesiology and Applied Physiology. Her research seeks to advance our understanding of the neural control of movement in healthy and disease. The lab she directs uses a variety of non-invasive functional and structural brain imaging techniques coupled with behavioral and genetic measures to investigate the mechanisms contributing to motor impairment in movement disorders such as Parkinson’s disease.
storms and coastal flooding, tidal analysis, climate, GIS, remote sensing
Dr. John Callahan is a interdisciplinary climate scientist and Visiting Assistant Professor in the Department of Geography and Spatial Sciences. Recent research at UD has focused on coastal storms and flooding, tidal data analysis, and developing a statistical predictive model for surge levels in Delaware. John was lead developer of the Delaware Coastal Flood Monitoring System (an online early warning system for coastal flooding) and lead author of the most recent Delaware SLR Projections report released in 2017. Other related work includes GIS and terrain analysis, biases in lidar elevation datasets due to vegetation, down-scaling satellites estimates of soil moisture, relationships between Atlantic White Cedar tree ring growth and weather variables, identifying locations within Delaware vulnerable to stream and coastal flooding, and estimating atmospheric water vapor from GOES satellite imagery. John holds a PhD in Climatology and MSc degree in Geography from UD, and BSc degrees in Mathematics and Physics from Temple University, Philadelphia, PA.
Every aspect of our lives depends on our ability to move. The overarching goal of my research program is to understand how the brain controls movement and adapts to new environments. My research falls under three major themes. The sensorimotor learning and neuroplasticity research line examines how reinforcement feedback can subserve our ability to acquire new motor skills. The neuromechanics line of research examines how the sensorimotor system controls the complex physics of our bodies while striking a balance between efficiency, mobility and stability. We have also begun work on human-human interactions, where the goal is to better understand how we use sensory and task feedback to discover a partner’s movement intention when selecting joint actions. To address these questions, we use a complementary blend of human experiments, theory and computational modelling. The long-term goal is to inform rehabilitation paradigms to improve the quality of life for those suffering from neurological disease, such as Parkinson’s or Stroke.
Data Management and Data Integration, Cloud Computing, Big Data Analytics, Deep Learning, Bioinformatics, Semantic Web and Ontology Engineering
Dr. Chen has developed several novel computational algorithms and software tools to support large-scale sequence clustering, sequence analysis, and proteomics study. He has led the effort for semantic computing and cloud computing as part of the NIH Big Data to Knowledge (BD2K) initiative. Through the Bioinformatics Network of Delaware (BiND), he has assisted in translating the CBCB services and capabilities into statewide resources, leveraging our computational cluster to serve hundreds of users across Delaware institutions. His research interests include data management and data integration, cloud computing, big data analytics and bioinformatics with focus on algorithms and software development.
Environmental Economics, Amazon forest, remote sensing, Brazil
Francisco Costa is an environmental and development economist with work on land use, climate change, and energy efficiency. His main research agenda concentrates on understanding how market incentives and policies can shape land use in tropical forests, with a focus on the Amazon rainforest. He is an Assistant Professor of Economics at the Alfred Lerner College of Business and Economics with a joint appointment at the School of Marine Science & Policy, an Invited Researcher at J-PAL (LAC & K-CAI), and an Affiliated Researcher at Getulio Vargas Foundation (FGV EPGE, Brazil). He received his Ph.D. in Economics from the London School of Economics and his M.A. and B.A. from FGV EPGE.
Mike is an agricultural entomologist who uses ecoinformatics and genomics approaches to understand insect ecology and evolution in changing farmscapes.
STEM-Education, health and environmental data science, chemical informatics, chemometrics
As a STEM Student Success Consultant at the University of Delaware (UD), Dr. Malcolm J. D’Souza assists the Office of Institutional Equity’s Vice Provost in seeing underserved students succeed through data-driven decision-making and proven active-learning techniques. Utilizing experiences gained as a Professor of Chemistry & Dean of Interdisciplinary Collaborative/ Sponsored Research at Wesley College, Dr. D’Souza supports UD administrators, faculty, and partner organizations. Together they author federal grants to cultivate an engaging learning culture that empowers students.
D’Souza’s academic training in chemistry, physics, and mathematics has allowed him to develop undergraduate projects, presentations, and publications in the areas of (societal) data-driven analytics, chemical informatics, chemometrics, and the design of commercial databases.
Dr. D’Souza received the 2021 Delaware-INBRE Lively Summit Award, the 2016 NIH-NIGMS Sidney A. McNairy Jr. Mentoring Award, and the 2012 American Chemical Society E. Emmett Reid Award. In addition, the Delaware Bioscience Association recognized Dr. D’Souza in 2016, 2018, and 2019.
Microscale robots, Control, Cellular Response, Patterning
Dr. Sambeeta ‘Sam’ Das is an assistant professor at the University of Delaware in the Mechanical Engineering Department. Before joining the University of Delaware, Dr. Das was a postdoctoral researcher for three years at the University of Pennsylvania. She was part of the GRASP Lab where she worked on microrobotic control and application of microrobots in biological systems. She earned her Ph.D. at the Pennsylvania State University in 2016 and her doctoral research was on directing micro and nanomotors and their applications in lab-on-a chip devices.
Dr. Das’s research is very interdisciplinary spanning multiple fields like robotics, autonomous systems, physics, organic chemistry, materials engineering, soft matter, and biomedical engineering. The goal of her lab is to seamlessly combine these disparate disciplines to address challenges in tissue engineering. Her research activities focus on develop microrobots capable of precision delivery of biochemicals and cellular patterning, for applications in personalized therapeutics, drug delivery, and high throughput biotechnology research.
Sustainable communities, Land use planning, Collaborative governance, Environmental planning, Growth management
I am an associate professor in the Biden School of Public Policy and Administration at the University of Delaware. I have an undergraduate degree in Architecture from India, graduate degrees in Urban and Regional Planning and Environmental Science from the Ohio State University, and a doctoral degree in Urban and Regional Planning from the University of Michigan. My research interests are at the nexus of public policy and urban planning in the broad areas of land use planning, regional planning and cooperation, growth management, and sustainability. I specifically focus on the factors that impact regional cooperation on land use issues, the impact of regional land use cooperation on development patterns on the ground, local efforts to enhance public engagement in planning, and the role of plans and ordinances in shaping the built environment.
multi-agent learning, distributed information gathering, distributed planning & scheduling, wearable devices/behavior change, financial AI
Keith Decker is an Associate Professor and JPMorgan Chase Fellow in the Department of Computer and Information Sciences, College of Engineering, at the University of Delaware. He is also affiliated faculty at the Delaware Biotechnology Institute and the Institute for Financial Service Analytics. His research interests include multi-agent systems, computational organization design, distributed planning and scheduling, distributed information gathering, multi-agent learning, bioinformatics, AI & finance, and AI & wearable devices. He received his BS in applied math from Carnegie Mellon University, his MS in computer science from Rensselaer Polytechnic Institute, and his Ph.D. in computer science from the University of Massachusetts. He is the recipient of a DARPA special recognition award and has been program co-chair for the International Conference on Autonomous Agents and Multi-Agent Systems, Practical Applications of Autonomous and Multi-agent Systems, etc. His interdisciplinary projects at UD include automated genetic annotation, coalition management techniques for electric vehicle-to-grid power, and machine learning for automated health coaching.
GIS, remote sensing, climate change, land science
My research interests are in the areas of physical and hydroclimatology, GIS and remote sensing focusing on land surface interactions with climate (and vice versa) by investigating regional to global observations and remotely sensed datasets. I rely heavily on using GIS, image processing systems and python for visualization of the geographic data and for mapping and spatial analysis. Geographic areas I have investigated include the Southern Great Plains with my dissertation soil moisture work, the Amazon Basin, the polar oceans examining sea ice thickness, and more recently Delmarva Peninsula.
Extrasolar planets, frequency-domain analysis, Gaussian processes
Dr. Dodson-Robinson is an associate professor in the Department of Physics and Astronomy. She is a member of the 100 Earths Project, a team of astronomers, engineers, and mathematicians using the Discovery Channel Telescope to search for earthlike planets orbiting sunlike stars. Her research group is developing and testing algorithms for validating planet discoveries. Dr. Dodson-Robinson also conducts numerical simulations of the chemistry and dynamics of planet-forming environments. She won the American Astronomical Society’s Annie Jump Cannon award in 2013 and an NSF Career Grant in 2011.
Criminal justice, policy, crime, evaluation
Ellen Donnelly is an assistant professor of Sociology and Criminal Justice. Her research broadly examines disparities in the U.S. criminal and juvenile justice systems. She specializes in using statistical methods to estimate the size and sources of disparity in justice processing as well as the impacts of justice reform. Her work in Delaware aims to help policymakers design fairer processing practices.
B.S. Math, B.S. Physics from Pennsylvania State University, Ph.D. in Applied Mathematics from Cornell University. At UD since 2000. Author of four books on computational methods. Author/coauthor of free software packages for numerical computing. Founder and inaugural Director of the Center for Applications of Mathematics in Medicine. Expert on spectral discretizations of differential equations.
family, social stratification, health disparities, sexual and reproductive health
Dr. Mieke Eeckhaut is an Associate Professor of Sociology at the Department of Sociology and Criminal Justice, University of Delaware. Her research examines the social and health consequences of social stratification for the family, with current work focusing on inequalities in the use of long-acting contraceptive methods (sterilization, and intrauterine devices and implants) in the United States. Her recent work has been published in Demography, Journal of Marriage and Family, Journal of Family Issues, Population Studies, European Sociological Review, Acta Sociologica, Perspectives on Sexual and Reproductive Health, Contraception, and Fertility & Sterility. She received her PhD in Sociology from Ghent University (Belgium), and completed a NICHD F32 postdoctoral fellowship at the California Center for Population Research at the University of California, Los Angeles.
pathogens, coevolution, microbiome, evolution, macroecology
I am a molecular disease ecologist. Much of my work has been on the ecology and evolution of avian haemosporidian parasites, commonly known as avian malaria parasites. I have worked on host immune responses to avian malaria infection, effects of avian malaria on host fitness and population size, parasite biogeography, and the evolution of host specificity. I also work on the ecology of Borrelia burgdorferi, the bacterial pathogen that causes Lyme disease in humans.
Evangelos Falaris is Professor of Economics at the University of Delaware. His research areas are Development Economics, Labor Economics and Applied Econometrics.
Investigative journalism, data analysis, medical and science trends, loneliness
As a reporter, Dawn Fallik covered a Super Bowl, an execution, and the Indian Ocean tsunami. She was the co-director of the National Institute of Computer-Assisted Reporting at the University of Missouri, where she worked with journalists to obtain federal, state and local data (once on 3480 cartridges.) She was a staff writer for The Associated Press and The Philadelphia Inquirer’s medical desk before coming to UD in 2007. She now writes for The Wall Street Journal, The Washington Post and Neurology Today. She is part of a team of UD researchers who recently won an NSF grant to investigate illicit mining. She is also interested in the medical ramifications of chronic loneliness and spoke at SXSW – “Generation Lonely: 10,000 Followers and No Friends.”
I am a Professor in the Department of Electrical and Computer Engineering at the University of Delaware. I am also affiliated with the Department of Computer and Information Sciences, Institute for Financial Services Analytics and Center for Bioinformatics and Computational Biology.
I lead the InfoLab group working on exciting topics related to information management such as Information Retrieval, Knowledge base, Data Mining and Biomedical Informatics. My research has been supported by National Science Foundation, University of Delaware Research Foundation and companies such as HP Labs and JPMorgan Chase.
I received my M.S. and Ph.D degree from University of Illinois at Urbana-Champaign in 2004 and 2007, respectively, and B.S. degree from Tsinghua University in 2001.
Social neuroscience, self/identity, stigma/prejudice, STEM achievement
Chad E. Forbes (Ph.D., University of Arizona) is an Associate Professor of Psychological and Brain Sciences at UD. With a background spanning from molecular biology to complex social processes, he utilizes behavioral methodologies as well as EEG, fMRI and genetic approaches to investigate social phenomena. Specifically, he examines how priming negative stereotypes affects our perceptions as well as stigmatized individuals in our society, e.g. minorities and women, to ironically engender situations that inadvertently reinforce the stereotype. Dr. Forbes is currently funded by the NSF to examine how and why minorities and women are more likely to leave academics and STEM fields respectively, how these stressors can be transmitted to others in group interactions, as well as how these phenomena can be reversed. He has numerous publications, including Annual Reviews of Neuroscience and Cerebral Cortex, and was recently recognized as a “Rising Star” by the American Psychological Association.
Information processing, probabilistic techniques, coding
Javier Garcia-Frias received the Ingeniero de Telecomunicación degree from Universidad Politécnica de Madrid, Spain, in 1992, the Licenciado en Ciencias Matemáticas degree from Universidad Nacional de Educación a Distancia, Madrid, in 1995, and the Ph.D. degree in electrical engineering from the University of California, Los Angeles, in 1999. In 1992 and from 1994 to 1996, he was with Telefónica I+D in Madrid. From September 1999 to August 2008, he was an Assistant and then an Associate Professor in the Department of Electrical and Computer Engineering at the University of Delaware, where he is currently a Professor. His research interests are in the area of information processing in communications and in complex systems. Dr. Garcia-Frias is a recipient of a 2001 NSF CAREER award and of a 2001 Presidential Early Career Award (PECASE) in support of his communications program.
infectious diseases, machine learning, data science, Natural Language Processing, predictive analytics
Dr. Roger Geertz Gonzalez is currently editing his dissertation for his second Ph.D. in data sciences at Harrisburg University of Science & Technology. It focuses on predictive population health analytics and it is sponsored by the U.S. Department of Defense Threat Reduction Agency, Duke-National University of Singapore Medical School, the Forestry Administration of Cambodia and University of California-Davis. His first Ph.D. was in higher education from Pennsylvania State University (2005). His data science experience ranges from t-tests, Hierarchical Linear Modeling using SPSS, R and SAS for multivariate data analysis and predictive modeling/machine learning, to Python for image processing, deep learning and natural language processing. You can find his Github site here: https://github.com/Rothgargeert.
housing, credit card markets, inequality
Olga Gorbachev is an associate professor of economics at the Lerner College of Business and Economics at the University of Delaware. Her research centers on understanding the impact economic instability has on household welfare. Economic insecurity is also linked to economic inequality. It plays a major role in household decision-making and in the response of public policy that insures individual livelihoods from exposure to risk. Prior to joining the University of Delaware, she was an assistant professor of economics at the University of Edinburgh, Scotland. She received her Ph.D. in economics from Columbia University and her B.A. in economics from Brown University.
Graphical models, covariance estimation, statistical analysis with missing data, graph signals
Dr. Guillot is an associate professor in the Department of Mathematical Sciences. His research interests include matrix analysis, graphical models, the reconstruction of missing values in datasets, and the analysis of signals on networks. He is interested in the applications of data science in climate science and in engineering problems. Prior to joining UD, he was a postdoctoral fellow at the Statistics Department at Stanford University and a postdoctoral fellow at the Department of Earth Sciences at the University of Southern California. He received his Ph.D. in mathematics from Laval University.
Computational chemistry, computational biophysics, structural biology, molecular dynamics simulations, molecular modeling
Dr. Hadden-Perilla uses all-atom molecular dynamics simulations — often referred to as “the computational microscope” — to study biological machines, such as viruses and molecular motors. Prior to joining the University of Delaware, she held a postdoctoral position at the Beckman Institute for Advanced Science and Technology and served as the Technology Training Organizer for the NIH Center for Macromolecular Modeling and Bioinformatics. Dr. Hadden-Perilla’s research extends beyond elucidation of the mechanisms of biological machines to developing tools and approaches that make the “computational microscope” accessible to blind and vision-impaired researchers.
Property Values, Non-Market Valuation, Groundwater Contamination, Renewable Energy, Energy Infrastructure
I am an environmental economist appointed as Professor and Chair of the Department of Applied Economics and Statistics at the University of Delaware. I received my Ph.D. in Economics (2006) as well as two Master’s Degrees (in Economics and Resource Policy and Behavior) from the University of Michigan, and a BS in Economics and Canadian Studies from Duke University in 1998. My research focuses on the valuation of environmental amenities and disamenities, primarily using revealed preference methods. Topically, my work focuses on the property value impacts of water quality and ecosystem health, as well as on the impacts of wind turbines and other forms of energy infrastructure. I also study land use and other local environmental policies, seeking to explain both their implementation and impacts and am currently working on a number of projects related to energy infrastructure, environmental contamination, and the interface of these issues with local communities.
political communication, social media, public opinion, national politics
Dr. Lindsay Hoffman joined the faculty of the Department of Communication at the University of Delaware in September 2007 after receiving her Ph.D. from The Ohio State University. Her research examines how citizens use internet technology to become engaged with politics and their communities. She also studies public opinion and the importance of perceived public opinion; the effects of viewing political satire on knowledge and participation; political and communication efficacy; and factors that drive news use.
Dr. Hoffman’s research is theoretically grounded in political communication, mass communication, and public opinion. Her work emphasizes both the social circumstances and psychological predispositions that influence individual media uses and effects. Her research also examines the components of mediated messages that encourage individuals to participate in — or distance themselves from — political activities such as voting, engaging with news, or simply expressing opinion.
Macroeconomics, Labor Economics, Public Finance
Hans A. Holter is an Assistant Professor of Economics at the Lerner College of Business and Economics at the University of Delaware. His research focuses on how public policy affects the labor market and the macro-economy. The questions he asks include: how do modern welfare state policies affect the incentives to work and invest in human capital, how effective are they in providing insurance towards unexpected life-events, and how do we optimally design such policies? To answer these questions he develops and simulates large general equilibrium models of the economy, using numerical methods.
Assistant Professor, Department of Civil and Environmental Engineering
Sociohydrology; Model Integration; Big Data; Causal Inference; Sustainability
Dr. Yao Hu is an Assistant Professor in the Department of Geography and Spatial Sciences and Department of Civil Engineering. His research area focuses on the study of integrated human and water systems, developing modeling tools and Cyberinfrastructure that can provide insights into the complexity of the integrated systems, as well as inform evidence-based decision making on water security issues in the ever-changing environment. Dr. Hu is currently leading the Water Security Lab at the University of Delaware.
Dr. John Jeka joined the University of Delaware in 2017 as Professor and Chair of the Department of Kinesiology and Applied Physiology. Dr. Jeka is internationally recognized for his work on human locomotion and balance, with a specific interest in how information from multiple senses is fused for upright stance control. His interdisciplinary research team, which included kinesiologist, biomedical engineers, physical therapists and mathematicians, investigates basic mechanisms in adaptive sensorimotor control in healthy individuals and in patient populations with neurological diseases. With over $10 million in funding, Dr Jeka has been continuously funded since 1994 with grants from the National Institutes of Health and the National Science Foundation as well as private foundation such as the Shriners Foundation and the Erickson Foundation. He has published over 80 articles and has patents on assistive devices to aid mobility.
Budgeting, Financial Management, Transparency, Accountability
Jonathan B. Justice is a professor in the Joseph R. Biden, Jr. School of Public Policy and Administration at the University of Delaware, where he teaches undergraduate courses in public policy; graduate courses in public administration; and the Seoul Case Study Program. Before earning a Ph.D., he worked as a project and program manager for local governments and economic development organizations in and around New York City. His published research has examined questions of public budgeting and finance, decision making, participation, transparency, accountability, and local economic development. His research in progress focuses on public budgeting and finance, fiscal decision making, and administrative accountability.
Materials Science and Engineering; Chemical and Biomolecular Engineering, polymers; plastics valorization; sustainability; manufacturing
Prof. LaShanda T. J. Korley is a Distinguished Professor in the Departments of Materials Science & Engineering and Chemical & Biomolecular Engineering at the University of Delaware (UD). Her research focuses on bio-inspired polymeric materials, film and fiber manufacturing, plastics recycling and upcycling strategies, stimuli-responsive composites, peptide-polymer hybrids, fiber-reinforced hydrogels, and renewable materials derived from biomass. Prof. Korley is the Director of the Energy Frontier Research Center – Center for Plastics Innovation (CPI) funded by the Department of Energy and also the Co-Director of the Materials Research Science and Center – UD Center for Hybrid, Active, and Responsive Materials (UD CHARM). She also is the Principal Investigator for the National Science Foundation Partnerships for International Research and Education (PIRE): Bio-inspired Materials and Systems and the Associate Director of the Center for Research in Soft matter & Polymers (CRiSP) at UD.
Geophysical Flows, Hypersonic Boundary Layers, Fluid Dynamics
Joseph Kuehl is an Associate Professor at the University of Delaware in the Mechanical Engineering Department. He holds Ph.D.s in Physical Oceanography and Mechanical Engineering from the Graduate school of Oceanography and University of Rhode (2009). His research interests include geophysical fluid dynamics (gap-leaping boundary currents, geophysical boundary layer dynamics and transport phenomena), hypersonic boundary-layer stability (numerical laminar-turbulent transition) and nonlinear vibrations (time series analysis, modal decomposition techniques and finite time invariant manifold analysis). He was the recipient of the AFOSR Young Investigator Award (2015) for his hypersonic boundary layer stability and transition research, participates in the NATO STO AVT hypersonic vehicle working groups (240, 190, 346), was a member of the National Academy of Science Committee on Advancing Understanding of the Gulf of Mexico Loop Current Dynamics and is a Co-PI of the 2022 National Ocean Partnership Program (NOPP) award. He has almost two decades of experience in observational, experimental and theoretical physical oceanography.
Finance, Data Science, Banking Systems, Machine Learning for Finance
Paul Laux is Professor of Finance in the Lerner College of Business and Economics and JPMorgan Chase Senior Faculty Fellow in the Institute for Financial Services Analytics at the University of Delaware, where he teaches Ph.D. students in data science for financial services. His research interests are at the intersections of financial markets, corporate finance, and data science. His research has appeared in The Journal of Finance, the Journal of Financial Economics, the Journal of Financial and Quantitative Analysis, the Journal of Financial Intermediation, the Financial Analysts Journal, Financial Management, and the Journal of International Business Studies, among others.
Ecohydrology, forest biogeochemistry, biometeorology
Delphis Levia is a Professor of Ecohydrology at the University of Delaware. He holds academic appointments in the Department of Geography & Spatial Sciences (primary), Department of Plant & Soils Sciences (joint), and Department of Civil & Environmental Engineering (joint). He currently serves as a Series Editor for Springer Nature’s prestigious Ecological Studies Series and an Associate Editor of Hydrological Processes, a top international hydrology journal published by Wiley. He has a strong international network of research collaborators and published papers on research conducted in many different countries, including Germany, Japan, Spain, China, Cambodia, and Panama. Some of his collaborative research involves big data and machine learning to better understand the interactions between forests and water.
Environmental pollution; Public health; Geohealth; Food-web bioaccumulation
Dr. Li studies the sources, transport, fate, and bioavailability of contaminants and nutrients in ecosystems and their impacts on public health, with an emphasis on linking global environmental changes to ecological and human health. Dr. Li currently uses multidisciplinary research approaches including analytical isotope geochemistry, ecosystem modeling, and field monitoring to understand the effects of global changes (climate change and pollution) on the burden of legacy and emerging contaminants in marine biota.
Ecosystem, Modeling, Coastal
Dr. Li’s research involves developing, coupling and implementing physical-biogeochemical numerical models to identify key drivers, influence pathways and consequences of marine ecosystem variability, with focus on the “bottom-up” effects cascading from physical environment (e.g., stratification, circulation, sea ice) to primary production and the food web. By addressing dynamical linkages between physical drivers and the ecosystem responses, our lab then can apply those linkages to decode historical record in the past and predict likely changes in the future. The interdisciplinary nature of our research is built upon collaboration with physical, biogeochemical, ecological, geological and satellite oceanographers.
Ocean Data Synthesis, Ocean Reanalysis, Climate Change, Ocean Dynamics
Dr. Liang is interested in using a combination of observations, numerical models and theory to understand how the ocean works and how the ocean is affected by and responds to the changing climate. In particular, Dr. Liang is interested in how the heat, salt, carbon, and other biogeochemical tracers are transported in the global ocean. Another of Dr. Liang’s current research interests is the dynamic processes that can supply energy to ocean mixing, and these processes mainly include internal tides, near-inertial oscillations, and mesoscale eddies. Dr. Liang has extensive seagoing experience, primarily in acquiring and processing data from Lowered/Vessel-mounted Acoustic Doppler Current Profiler (ADCP). Furthermore, he is familiar with the system of ocean state estimation (e.g., ECCO), which is powerful and has huge potential in addressing fundamental oceanographic questions.
Li Liao, associate professor of Computer & Information Sciences at the UD, has worked in the field of bioinformatics for more than 20 years, with broad expertise in developing computational methods to solve a wide variety of biological problems, from detecting remote protein homology to reverse engineering the biological networks and to predicting disease comorbidity. An author of more than 70 peer-reviewed publications, he is active in research and serving the bioinformatics community. He has served as a panelist for NSF, program committee member and/or organizer for over 20 conferences and workshops in bioinformatics for the past 5 years, and is currently on the editorial board of several journals, including the ACM/IEEE Transactions on Computational Biology & Bioinformatics. He received a PhD in theoretical physics from Peking University, and graduate degrees from University of Pennsylvania and Columbia University in chemistry and computer science respectively.
Development Economics, Education, Health
Adrienne Lucas is a Professor of Economics and Economics Department Chair in the Lerner College of Business and Economics at the University of Delaware. She is a development economist specializing in the economics of education and disease. Her current research focuses on improving student learning within existing schooling systems in Africa and South Asia. She carefully establishes causation using both randomized controlled trials and administrative data. Her work has been funded by governments, non-governmental organizations, and private foundations. Prior to joining the University of Delaware, she was an assistant professor of economics at Wellesley College. She received her Ph.D. and A.M. in Economics from Brown University and her B.A. in Economics from Wesleyan University.
Business Analytics, Revenue Management, Food Safety, Consumer Behavior
Jing Ma is an assistant professor in the Department of Hospitality Business Management in the Alfred Lerner College of Business and Economics. Her research interests lie in the application of analytics and statistical methods to the study of hospitality business operations and revenue management, consumer behaviors, and food safety. Her goal is to provide data driven solutions for the hospitality industry.
Mokshay Madiman is an Associate Professor in the Department of Mathematical Sciences at the University of Delaware. His research is primarily in probability, information theory, and geometric functional analysis, but also interacts with machine learning and combinatorics. After a Ph.D. in applied mathematics from Brown University in 2005, Dr. Madiman joined the Department of Statistics at Yale University as a Gibbs Assistant Professor, and left Yale in 2012 as an Associate Professor of Statistics and Applied Mathematics. He has held several visiting positions for a month or more, including at the Isaac Newton Institute for Mathematical Sciences in Cambridge (UK), Princeton University, Université Paris-Est at Marne-la-Vallée (France), the Mathematical Sciences Research Institute in Berkeley, and the Tata Institute of Fundamental Research in India. His work has been recognized by a NSF CAREER award and numerous invited talks and lecture series.
Cyber-physical systems; connected and automated vehicles; smart cities
Dr. Andreas Malikopoulos is the Terri Connor Kelly and John Kelly Career Development Associate Professor in the Department of Mechanical Engineering and the Director of the Sociotechnical Systems Center at the University of Delaware (UD). Prior to these appointments, he was the Deputy Director and the Lead of the Sustainable Mobility Theme of the Urban Dynamics Institute at Oak Ridge National Laboratory, and a Senior Researcher with General Motors Global Research & Development. He received a Diploma from the National Technical University of Athens, Greece, and his M.S. and Ph.D. degrees from the University of Michigan, Ann Arbor, in 2004 and 2008, respectively, all in Mechanical Engineering. Dr. Malikopoulos is the recipient of several prizes and awards, including the 2007 Dare to Dream Opportunity Grant from the University of Michigan Ross School of Business, the 2007 University of Michigan Teaching Fellow, the 2010 Alvin M. Weinberg Fellowship, the 2019 IEEE Intelligent Transportation Systems Young Researcher Award, and the 2020 UD’s College of Engineering Outstanding Junior Faculty Award. He is a Senior Member of the IEEE and a Fellow of the ASME.
Lena Mashayekhy is an associate professor in the Department of Computer and Information Sciences at the University of Delaware. Her research interests include edge/cloud computing, data-intensive computing, Internet of Things, and algorithmic game theory. Her doctoral dissertation received the 2016 IEEE TCSC Outstanding PhD Dissertation Award. She is also a recipient of the 2017 IEEE TCSC Award for Excellence in Scalable Computing for Early Career Researchers. She has published more than thirty peer-reviewed papers in venues such as IEEE Transactions on Parallel and Distributed Systems and IEEE Transactions on Cloud Computing.
Sustainability; Education; Health;
Matthew Mauriello is an Assistant Professor and Human-Computer Interaction researcher (HCI/CS) in CIS, as well as the director of the Sensify Lab (sensifylab.org). His research interests center around designing better user experiences with technology and tackling societal problems in the areas of sustainability, human-building interactions, wearables, personal informatics, education, health & wellness, and games. The aim of this research is twofold: (i) to understand and improve the role of technology with respect to personal and societal issues and (ii) complement and extend rather than supplant user capabilities. His approach to research begins with formative work to explore user challenges and perceptions that help to identify what roles HCI might play (e.g., to identify pain points that technology could alleviate). This work typically informs an iterative design and engineering phase that often results in a cyber‐physical or software system that leverages advances from diverse areas of computer science (e.g., machine learning, image processing, information visualization, social computing) to improve user experiences.
data4good, technology and social justice, e-government, social policy, advocacy
John G. McNutt is Professor in the School of Public Policy and Administration at the University of Delaware. Dr. McNutt is a specialist in the application of high technology to political and social engagement. His work focuses on the role of technology and data in lobbying, e-government and e-democracy, political campaigning and deliberation, organizing and other forms of political participation. He has conducted research on professional associations, child advocacy groups, consumer and environmental protection groups, social action organizations and legislative bodies. Dr. McNutt has edited, co-edited or co-authored seven books and many journal articles, book chapters and other publications.
antarctica, climate change, oceans
Carlos Moffat received a B.S. in Marine Biology from the University of Concepción, Chile, and a Ph.D. in Physical Oceanography from the MIT-WHOI Joint Program. He was a Postdoctoral Researcher at the Woods Hole Oceanographic Institution. Since early 2016, he has held a faculty position at the School of Marine Science and Policy at the University of Delaware.
His research interests span a range of problems in Coastal Physical Oceanography, including understanding the role the ocean plays in glacier retreat, the dynamics of river discharge to the continental shelf, and physical-biological interactions.
Oceanography, Underwater Robotics, Marine Ecology, Polar Marine Science
Mark received his B.A. in Biology from St. Olaf College and a Ph. D. in Biology from the University of California, Santa Barbara. Mark joined the faculty at Cal Poly State University in 1998 and founded the Center of Marine and Coastal Sciences in 2004. In 2012, Mark became the founding Director of the School of Marine Science and Policy at the University of Delaware and was named the Maxwell P. and Mildred H. Harrington Professor of Marine Studies in 2020.
Dr. Moline was an early adopter of autonomous underwater technologies and sensor developer to improve sampling of the ocean in multiple disciplines. He has applied these technologies in tropical, temperate and Polar Regions.
Past awards include the New Investigator Program award (NASA), the Young Investigator Program award (ONR), the Presidential Early Career Award for Scientists and Engineers (PECASE), and the Fulbright Distinguished Arctic Chair.
Inverse scattering, electromagnetism, solar cells
Peter Monk is currently a Unidel Professor with the Department of Mathematical Sciences, University of Delaware, Newark, DE, USA. He is the author of Finite Element Methods for Maxwell’s Equation and a coauthor with F. Cakoni and D. Colton of The Linear Sampling Method in Inverse Electromagnetic Scattering (CBMS-SIAM 2011).
Neural encoding of social information, Innate social behavior, Animal communication, Dominance hierarchies
Josh Neunuebel received a B.S. in Molecular and Cellular Biology and a M.S. in Zoology from Texas A&M University. Josh received a Ph.D. in Neuroscience from UT Health Science Center-Houston. During Josh’s doctoral and first post-doctoral appointments (Johns Hopkins University), he systematically mapped the flow of information through the hippocampus and identified key mechanisms of memory storage. As a post-doctoral fellow at HHMI Janelia Research Campus, Josh focused on the neurobiology of animal behavior, in particular, how mouse vocalizations shape the dynamics of social behavior. In the fall of 2014, Josh accepted a faculty position in the Department of Psychological and Brain Sciences at UD. His research focuses on how the nervous system processes and integrates social information that underlies purposeful innate behavior. His research team laid the groundwork for elucidating the neurobiology of social behavior by building a novel system for simultaneously recording neural, audio, and behavioral data from freely socializing mice, which requires high-performance computing and machine- and deep-learning approaches to analyze.
Co-Chair, Research Information Management Committee
My research involves directly measuring properties of the Earth’s surface and trying to understand how those properties are affected by climatic, geologic, and anthropogenic processes. My students and I collect data using a very wide range of techniques including remote sensing and traditional instrument surveys. The basic research questions I address can be posed in many different settings. As a result, my publications encompass a wide spectrum of surficial environments including icy landscapes, river channels, earthworks, and beaches.
Biophysics, Computational biology, molecular modeling, statistical biophysics
A key theme of Dr. Perilla’s research is to explore fundamental cell processes across multiple scales. Dr. Perilla’s primary technique is molecular dynamics (MD). During the past three decades, MD simulations have emerged as a “computational microscope”, which has provided a unique framework for the study of the phenomena of cell biology in atomic (or near-atomic) detail. Remarkably, due to the the ambitious nature of Dr. Perilla’s research, his lab has developed novel MD approaches for computation, data analysis, and interface to experiments. In addition, the synergistic interplay between Dr. Perilla’s computational work and state-of-the-art experimental work performed by experimental collaborators, has resulted in a robust framework for elucidating accurately and quantitatively the physical mechanisms of biomolecular function.
Stars, magnetic fields, stellar evolution, spectropolarimetry
Dr. Véronique Petit studied Physics at Université Laval in Québec City, Canada. Dr. Petit is interested in the lives of massive stars, which are tens of times more massive than our Sun, especially in the relatively new and rapidly evolving study of these stars’ intriguing magnetic fields. Dr. Petit uses state of the art observations to challenge, constrain, and guide quantitative theoretical models, within the context of large observing programs such as the Magnetism in Massive Star (MiMeS) and the Binarity and Magnetic Interactions in various classes of Stars (BinaMIcS) projects. Her key areas of expertise include optical, ultraviolet, and X-ray spectroscopy, optical spectropolarimetry, polarized radiative transfer, and Bayesian inference.
Director, CBCB Bioinformatics Core Facility
Viral ecology, microbiome, metagenomics, genomics, bioinformatics
Dr. Polson’s research interests lie at the intersection of genomics and microbial ecology, examining the ways in which microorganisms and viruses affect and are affected by their environments. While admitting a preference for marine research, his research also encompass a broad range of other environments from soils and agriculture to the extreme environments of hot springs and deep sea hydrothermal vents. The data intensive nature of the research has led him to specialize in bioinformatic aspects, identifying creative solutions to visualize and analyze microbial communities including high-throughput genomic, transcriptomic, and metagenomic data.
beaches, surf, swash, coastal
Jack Puleo is a Professor and Chair in the Department of Civil and Environmental Engineering and a core faculty member of the Center for Applied Coastal Research (CACR). He completed a B.S. from Humboldt State University, a M.S. from Oregon State University and the Ph.D. from the University of Florida. He joined the faculty at UD in 2004. He was a Fulbright Scholar and visiting Professor at Plymouth University in 2011-2012.
Puleo conducts research on small-scale hydrodynamic and sediment transport processes in coastal environments. His research involves designing sensor networks, developing new sensors, and conducting rapid-response deployments to quantify intra-storm processes. Outcomes of the research lead to improved parameterizations for sediment transport that could be incorporated into high resolution and engineering-level predictive models for coastal change.
He has received the NSF CAREER Award in 2007, teaching awards from ASCE, the College of Engineering, and the University of Delaware (twice), a Chi Epsilon advising award, a ASBPA Robert G. Dean Award, and a German DAAD Scholarship.
Dr. Wei Qian is an Assistant Professor of Statistics at the Department of Applied Economics and Statistics; he is also affiliated faculty of the Institute for Financial Services Analytics. Dr. Qian conducts research in the field of statistics and machine learning, with particular interests in high-dimensional statistics, model selection, dimension reduction, nonparametric and semiparatric estimation, actuarial statistics, forecasting, online recommendation, and data science applications.
Multiple testing, high dimensional data, Bayesian modelling, bioinformatics
Dr. Jing Qiu obtained her PhD in Statistics from Cornell University and was a tenured faculty at the Department of Statistics, University of Missouri at Columbia before she joined the UD in 2015. She is currently a tenured associate professor of Statistics and an affiliated faculty member at CBCB.
Her research interest lies in the analysis of high dimensional data, statistical modeling of genomics data, multiple testing and Baysian modelling. She has published one book chapter and 26 papers on peer reviewed journals including top journals such as Science, Journal of the Royal Statistical Society: Series B, Bioinformatics, Biometrics, Biostatistics, BMC Bioinformatics. She serves on the Editorial Board of Mathematics of Computation and Data Science (specialty section of Frontiers in Applied Mathematics and Statistics) as Review Editor since 2016 and on the committee on the Award of Outstanding Statistical Application, the American Statistical Association since 2016.
Low rank tensor methods, multi-scale multi-physics simulations, computational fluid dynamics, fusion energy science
Professor Jingmei Qiu got her Ph.D. from Brown University in 2007. She spent a year at Michigan State University as a research associate. She held a tenure track faculty position in Colorado School of Mines 2008-2011, in University of Houston from 2011 to 2017 and was promoted to Associate Professor in 2014. She moved to University of Delaware in 2017 and was promoted to Professor in 2019.
Professor Qiu’s research interests include high order numerical methods for fluid, kinetic and multi-scale models. Recently she is interested in Eulerian-Lagrangian high order approaches and low rank tensor approximations to high dimensional nonlinear dynamics.
historic preservation; 3D image analysis; cultural heritage data
Chandra Reedy is a professor of historic preservation in the University of Delaware’s Biden School of Public Policy & Administration, where she also serves as Director of the Center for Historic Architecture and Design and its Laboratory for Analysis of Cultural Materials. She combines laboratory research with ethnographic field research, most recently in China, Japan, and Cambodia. She focuses on developing new methods for documenting, preserving, and understanding the characteristics and cultural context of traditional materials, technologies, and intangible cultural heritage, and their preservation issues. Her most recent work has focused on 3D image analysis for porosity studies of bricks and archaeological ceramic materials. For the past 12 years she has served as Editor-in-Chief of Studies in Conservation, the flagship journal of the International Institute for Conservation of Historic and Artistic works.
climate change, complexity, food systems
James Rising is an interdisciplinary modeller in the School of Marine Science and Policy. His research focuses on the impacts of climate change and the interaction between human decisions and the environment. He builds integrated models to better understand social choices, issues around climate justice, and how to make the most of natural resources. Prior to joining the the University of Delaware, James held positions at the Grantham Research Institute at the London School of Economics, Energy Policy Institute at the University of Chicago, and Energy & Resources Group at UC Berkeley. He received his Ph.D. from Columbia University’s program in Sustainable Development. He has also had a career as a software developer, working with over a dozen companies on audio and video processing, social networks, and artificial intelligence.
Financial Institutions and Housing Finance
Professor Robinson works at the University of Delaware as an Associate Professor in the Joseph R. Biden Jr. School of Public Policy and Administration. His background features extensive training and expertise in banking where he has worked outside of academics with the Federal Reserve Bank of Philadelphia, the Federal Reserve Bank of Richmond and the Office of the Comptroller of the Currency. Breck’s research has focused on lending opportunities for low-income and minority communities and the use of financial institutions in facilitating economic development. His work has appeared in the Journal of Banking and Finance, Housing Policy Debate, Real Estate Economics and the Journal of Real Estate Finance and Economics among others. Breck received a B.A. in economics and political science from the University of Maryland Baltimore County, a M.A. in economics from the University of Delaware and a M.B.A. and Ph.D. in finance from the University of Tennessee
Professor, Mathematical Sciences
Louis Rossi is Vice Provost for Graduate and Professional Education and Dean of the Graduate College and Professor, Department of Mathematical Sciences. He has wide ranging research interests in swarming, fluid dynamics, computational methods and modeling. Recent projects include the analysis of aggregations of living systems, wireless and wired biologically inspired network protocols and high Reynolds number flow fields. Most recently, he is interested in the coordination of groups of plankton.
educational technology, learning sciences, data-intensive methods
Dr. Teomara (Teya) Rutherford is an Associate Professor of Education in the UD School of Education’s Learning Sciences specialization area. She earned her PhD in Learning, Cognition, and Development from University of California, Irvine, her JD from Boston University School of Law, and her bachelor’s degree in Elementary Education with a concentration in Computers in the Classroom from Florida International University.
Dr. Rutherford’s research focuses on learning and motivation in digital contexts, with a particular focus on how and why students make decisions as they engage with educational technology. She received an NSF CAREER award in 2019 to study students’ in-the-moment motivations and emotions as they work within a digital mathematics learning tool. This work uses data-intensive methods, such as learning analytics, to understand how motivation relates to choice and success within the software.
AI, machine learning, quantum, networks, algorithms, nlp
Dr. Ilya Safro received his Ph.D. from the Weizmann Institute of Science under the supervision of Achi Brandt and Dorit Ron. In January 2021, he joined the Department of Computer and Information Sciences at the University of Delaware. In 2012-2020, Dr. Safro held assistant and associate professor positions in the School of Computing at Clemson University. He was also a Faculty Scholar of the Clemson University School of Health Research. Before that he was a postdoc and Argonne scholar at the Division of Mathematics and Computer Science at Argonne National Laboratory. Dr. Safro research is funded by NSF, DARPA, DOE, BMW, and Greenville Healthcare Systems. His research interests include algorithms and models for AI, machine learning, NLP, network science and graphs, quantum computing and large-scale optimization.
atomic clocks, quantum simulation, dark matter, atomic theory, high-performance computing
Marianna S. Safronova (Ph.D., 2001) is a Professor of Physics at the University of Delaware. Her diverse research interests include applications of quantum technologies to search for physics beyond the standard model of elementary particles and fields, development of atomic and nuclear clocks and their applications, ultra-cold atoms and quantum information, studies of fundamental symmetries, dark matter searches, quantum many-body theory and development of high-precision relativistic atomic codes, development of the online atomic data portal, highly-charged ions, superheavy atoms, and other topics. She is a Fellow of the American Physical Society and the 2018-2019 Chair of the American Physical Society Division of the Atomic, Molecular, and Optical Physics. She was a member of the Committee on a Decadal Assessment and Outlook Report on Atomic, Molecular, and Optical Science (AMO2020), National Academy of Sciences, Engineering and Medicine. She is a member of the Quantum Science and Technology Journal Editorial Board. Safronova earned a Ph.D. in physics from the University of Notre Dame.
Math modeling, math and biology, math and medicine, math and finance
The focus of my current research is in the application of mathematics in medicine. I am a member of the Center for the Application of Mathematics in Medicine (CAMM). My research involves mathematical modeling, ordinary and partial differential equations, stochastic differential equations, discrete mathematics, asymptotic and perturbation methods, scientific computing and data processing.
Perception, attention, vision, dyslexia, thalamus
I study the relationship between the architecture of the human visual system and the functions of attention, perception and awareness, in both normal and clinical populations. I specialize in measuring the visual subcortex—the lateral geniculate nucleus, pulvinar and thalamic reticular nucleus in the thalamus, and the superior colliculus—using structural and functional magnetic resonance imaging. Multiple streams of information arise from distinct ganglion cell populations in the retina; the subcortical nuclei play central roles in the recurrent regulation of visual function, and here, like nowhere else in the brain, these visual streams are spatially disjoint and their activity can be measured with high-resolution functional magnetic resonance imaging. Abnormalities in these structures may be important in clinical disorders such as dyslexia.
Cosmic Rays, Radio Detection, Analysis Methods, Monte Carlo Simulations, Neural Networks
Frank G. Schroeder graduated at Technical University of Darmstadt, Germany and received his PhD in Physics at the Karlsruhe Institute of Technology (KIT), Germany in 2011. During his postdoctoral career he did research at the Universidad Nacional de San Martin, Buenos Aires, Argentina, and became leader of a young investigator group at KIT, Germany. He joined University of Delaware as tenure-track faculty in 2018. His research is about the detection and data analysis of ultra-high-energy cosmic rays, in particular, at the Pierre Auger Observatory in Argentina and at the IceCube Neutrino Observatory at the South Pole.
Hotel revenue management
Dr. Zvi Schwartz is a Professor in the Department of Hospitality Business Management, Alfred Lerner College of Business and Economics at the University of Delaware. He was the Marriott Senior Faculty Fellow for Hospitality Finance and Revenue Management, and the director of graduate programs, at Virginia Tech.
He received a doctoral degree from Purdue, an MBA at Tel-Aviv University, and a BA in Economics from Haifa University. Zvi has over a decade of lodging industry experience as a manager at Hyatt Hotels, and an entrepreneur with Inntegral and Technolodge.
His scholarly research and industry consulting focuses on the core technical elements of the revenue management cycle. Recent projects explored novel hotel forecasting approaches, occupancy forecasting accuracy measures, hotel competitive sets, overbooking optimization, and revenue management performance measures.
Dr. Schwartz is a three-time recipient of ICHRIE’s Wiley Memorial Best Published Research Paper of the Year Award.
policy, innovation, institutions, corporate sustainability, sustainable development, green economy
Areas of research include: Energy policy and development: green economy, renewables, energy efficiency, resilient energy infrastructure, clean energy transitions, oil and natural gas markets. Can discuss environment and climate change policy, including the blue economy, climate change adaptation, climate finance and risk, tourism industry. Also studies corporate sustainability and public policy, such as corporate social responsibility; foreign direct investment and sustainable development; environmental and social governance in businessSpecializes in policy, regulation, institutions and governance in small economies, island states and territories including U.S. policy in the Caribbean, Pacific and African/Indian Ocean.
education, policy, causal inference
Dr. Kenneth A. Shores is an assistant professor specializing in education policy in the School of Education at the University of Delaware, and he is affiliated with the UD Center for Research in Education and Social Policy. His research is focused on educational inequality and encompasses both descriptive and causal inference. To this end, his work addresses racial/ethnic and socioeconomic inequality in test scores, school disciplinary policy, classification systems, and school resources. In addition, he has examined how improvements to school finance systems can reduce educational inequality and how vulnerabilities in school finance systems can contribute to it.
Dr. Shores was a National Academy of Education/Spencer Dissertation Fellow, a Philanthropy and Civic Society Fellow, a Stanford Graduate Fellow, and an Institute of Education Sciences (IES) Predoctoral Fellow. In 2018, he was the co-recipient of the National Council on Measurement in Education’s Annual Award for exceptional achievement in educational measurement.
He received his Ph.D. in education policy analysis from Stanford University. Prior to graduate school, he was a middle school teacher on the Navajo Nation.
Assistant Professor, Geography & Spatial Sciences
Assistant Professor, Disaster Research Center
climate change; adaptation; decision-making; text mining
A.R. Siders is an assistant professor in the Disaster Research Center, Biden School of Public Policy and Administration, and Department of Geography and Spatial Sciences. She holds a JD from Harvard and a PhD from Stanford. She previously served as an environmental fellow at the Harvard University Center for the Environment, a legal fellow at the Sabin Center for Climate Change Law, and a Presidential Management Fellow with the US Navy. Her research explores climate change adaptation decision-making and evaluation: how and why communities decide when, where, and how to adapt to the effects of climate change and how decisions and decision-making processes affect risk reduction and equity. Her work has been published in journals such as Science and Climatic Change and has appeared in news outlets such as the New York Times and Science Friday.
Abhyudai Singh earned his bachelor’s degree in mechanical engineering from the Indian Institute of Technology in Kanpur, India. He received master’s degrees in both mechanical and electrical & computer engineering from Michigan State University, and a master’s degree in ecology, evolution and marine biology from University of California Santa Barbara (UCSB). After earning his doctoral degree in electrical & computer engineering in 2008, also from UCSB, he completed postdoctoral work in UC San Diego’s Department of Chemistry and Biochemistry. From 2011 to 2017 he was an Assistant Professor in the Departments of Electrical & Computer Engineering, Biomedical Engineering and Mathematical Sciences at the University of Delaware, and was promoted to Associate Professor in 2017. His research interests are in dynamics, control, and identification of biomedical systems with applications to systems/synthetic biology and neuroscience.
Medical informatics; Data analytics; Healthcare; Reliability engineering
Junbo Son is currently an assistant professor of operations management at the University of Delaware. Junbo has strong background in advanced engineering systems and applied statistics. Junbo has been closely working with major firms in automotive industry and IT-driven healthcare companies. Also, Junbo has been involved in many statistical consulting projects in engineering and healthcare. His research has focused on business data analytics and data-driven operations management focusing on modern smart and connected systems enabled by advanced IT, efficient sensors and Internet-of-Things (IoT). The motivation and inspiration of Junbo’s research primarily come from real world business problems identified by industry collaborators. He enjoys interdisciplinary research topics based on his diverse training background and publishes his research in prestigious engineering and business journals.
Plant roots; biomechanics; molecular development; phenotyping
Erin Sparks is an Assistant Professor in Plant and Soil Sciences and the Delaware Biotechnology Institute at the University of Delaware, where she started her position in 2017. She has a B.S. in Biomedical Engineering, a Ph.D. in Cell and Developmental Biology, and Postdoctoral experience in Plant Molecular Biology. Erin’s lab works at interdisciplinary interfaces to understand the development and function of aerial roots in cereal crops.
multi-robot systems, robot motion planning, navigation
Herbert Tanner received his Ph.D. in mechanical engineering from the National Technical University of Athens, Greece, in 2001. After a post doc at the Department of Electrical and Systems Engineering at the University of Pennsylvania from 2001 to 2003, he joined the Department of Mechanical Engineering at the University of New Mexico, where he served as an assistant professor from 2003 to 2008. In 2008 he joined the Department of Mechanical Engineering at the University of Delaware, where he is currently a professor.
Dr. Tanner received NSF’s Career award in 2005. He is a fellow of the ASME, and a senior member of IEEE. He has served in the editorial boards of the IEEE Robotics and Automation Magazine, the IEEE Transactions on Automation Science and Engineering, and the IEEE Transactions on Automatic Control, as well as the conference editorial boards of both IEEE Control Systems and IEEE Robotics and Automation Societies.
Household finance, behavioral economics, development economics
Jeremy Tobacman studies household finance, development economics, and behavioral economics. He works with large datasets on consumption, saving, and borrowing, and he uses computational methods to solve for equilibria of decision-making models. He is also interested in management of risks due to weather and other natural hazards.
social network analysis, combinatorial optimization, temporal point process, graph algorithms
Dr. Tong is an assistant professor in the Department of Computer and Information Science at the University of Delaware. He is working in the area of algorithm design and machine learning with applications in social network analysis, including online misinformation, social relationship analysis, and online discussion forum modeling. He received a BS in math from Beijing Institute of Technology in 2013 and a Ph.D. in computer science from the University of Texas at Dallas in 2018.
Marketing, Advertising, Causal Inference, Econometrics, Energy
My goal as an empirical researcher is to apply novel analytic tools to large datasets for the pragmatic application and validation of consumer behavior & economic theories. Broadly speaking, my research employs large real-world datasets to identify factors that affect consumers’ decision-making (e.g., consumers’ limited information), and it measures the returns on marketing investments (e.g., advertising). An example, in one paper I ask: how do the changes in advertising content affect consumers’ demand and firms’ revenues? My research also quantifies the economic values of policy and market interventions, such as regulatory changes. For example, in one of my recent projects, I ask: how does the “Airbnb Law” affect the performance of hotels in the area? I employ a wide variety of methodological approaches developed in econometrics, statistics, and computer science that allow for theory testing (e.g., “Is the effect of advertising informative, persuasive, or both?”), causal inference (e.g., “Does rebranding improve a firm’s performance?”), & counterfactual simulation (e.g., “If a pharmaceutical company changed its syringe design, what would be the impact on societal cost?”).
Surface Waves, Sea Spray, Airflow Turbulence
My research interests are centered on Air-Sea interactions: Turbulence at the ocean surface; Atmospheric and oceanic boundary layers; Bubble entrainment; Generation and transport of sea spray; Rain impact on the sea surface; Wind wave generation; Wave-current interactions.
Director, Delaware Energy Institute
Director, Catalysis Center for Energy Innovation
Dionisios (Dion) G. Vlachos is the Unidel Dan Rich Chair in Energy of Chemical & Biomolecular Engineering, a Professor of Physics and Astronomy at the University of Delaware, the Director of the University of Delaware Energy Institute (UDEI), of the UD node of the manufacturing institute RAPID, and of the Catalysis Center for Energy Innovation (CCEI), an Energy Frontier Research Center (EFRC). He is the ExxonMobil Visiting Chair Professor, National University of Singapore, Singapore, 2018-2021. He obtained a five-year diploma in Chemical Engineering from the National Technical University of Athens, Greece in 1987, his M.S. and Ph.D. from the University of Minnesota in 1990 and 1992 respectively, and spent a postdoctoral year at the Army High Performance Computing Research Center in Minnesota. After that, Dr. Vlachos joined the University of Massachusetts as an assistant professor, was promoted to an associate professor in 1998 and joined the University of Delaware in 2000.
Assistant Professor, Earth Sciences
Hydrology, Ecosystem Services, Sustainable and Resilient Communities, High Throughput/Performance Computing
Dr. Voter is an Assistant Professor in the Department of Civil and Environmental Engineering and the Department of Earth Sciences. Dr. Voter’s research focuses on the challenges of sustainably managing water resources and restoring ecosystem services in a world where urbanization is expanding, agricultural demand is intensifying, and the climate is changing. Her research involves synthesizing empirical data and using physically-based hydrologic models to 1) push the boundaries of our integrated understanding of water resources and ecology, then 2) identify key ecohydrologic control points – times, places, or processes – where management actions are most effective.
AI, Business Analytics
Dr. Harry Wang is a Full Professor of Management Information Systems at the University of Delaware with more than 15 years’ research, teaching, and management experience in AI, business intelligence and analytics, business process management, and enterprise systems. He currently also serve as the chief scientist of Tezign (a tech startup based in Shanghai, China backed by VC firms like Sequoia Capital and Hearst Ventures) and an independent director for So-Young International Inc. (NASDAQ: SY – the largest social community in China for consumers, professionals, and service providers in the medical aesthetics industry). Professor Wang was the founding director of OneConnect (NYSE: OCFT) US Research Institute based in New York City from 2018 to 2019 and the VP of Technology for the Association for Information Systems from 2015 to 2018. He was one of the founding members for the Institute for Financial Services Analytics at the University of Delaware and a JPMorgan Chase Fellow from 2014 to 2018.
Revenue Management; Pricing; Predictive Modeling; Consumer Behavior; Optimization
Tim Webb is an assistant professor in the Department of Hospitality Business Management in the Alfred Lerner College of Business and Economics. He earned his PhD in hospitality and tourism management from Virginia Polytechnic Institute. He’s also earned an MS in Mathematics from the University of Connecticut and a BS in Applied Mathematics from SUNY Buffalo State. Dr. Webb has several years of work experience in various analytical roles including the title of data scientist for Delaware North. His research is focused on data driven solutions for the hospitality industry and he has a vast amount of applied experience in the areas of forecasting, pricing and optimization for hospitality organizations.
Automated writing evaluation; automated essay scoring; automated feedback; writing instruction; writing assessment
Dr. Joshua Wilson is an associate professor in the School of Education at the University of Delaware. His research broadly focuses on ways to improve the teaching and learning of writing and specifically focuses on ways that automated writing evaluation systems can facilitate those improvements. His research has been supported by grants from federal, foundation, and industry sponsors and has been published in journals such as International Journal of Artificial Intelligence in Education, Computers & Education, Journal of Educational Computing Research, Journal of Educational Psychology, and Journal of School Psychology among others. Dr. Wilson sits on the editorial boards of such top journals as Assessing Writing, Journal of Educational Psychology, and Journal of Learning Disabilities.
metagenomics, bioinformatics, viral ecology, microbiology
Eric Wommack graduated Summa Cum Laude from Emory University with bachelors in Biological Sciences & Economics. Realizing that the number of economic theories always exceeds the number of economists and ignoring significant opportunity costs, he chose the more glamorous, albeit indigent, path of graduate work in the life sciences. After graduating from Emory he was awarded a Bobby Jones Fellowship to pursue a M.Sc. in Physiology under the mentorship of Prof. Ian Johnson at the University of St. Andrews, Scotland. After obtaining his M.Sc., he btained a Ph.D. exploring the role of viruses in marine ecosystems under the mentorship of Prof. Rita R. Colwell at the University of Maryland. He was awarded a National Research Council fellowship for post-doctoral work investigating microbial degradation of chiral pesticides under the mentorship of David Lewis (U.S. Environmental Protection Agency) and Prof. Robert Hodson at the University of Georgia.
Digital Signal Processing, Wireless Communications, and Radar Imaging
Xiang-Gen Xia received his B.S. and M.S degrees in mathematics, M.S. degree in mathematics and his Ph.D. degree in electrical engineering. Prior to UD, he was a Senior/Research Staff Member at Hughes Research Laboratories, Malibu, CA. In 1996, Dr. Xia joined the UD Department of Electrical and Computer Engineering. His current research interests include space-time coding, MIMO and OFDM systems, digital signal processing, and SAR and ISAR imaging. Dr. Xia is the author of the book Modulated Coding for Intersymbol Interference Channels (New York, Marcel Dekker, 2000).
Optimization, Machine Learning, Empirical Analysis
Dr. Zhao is an assistant professor of operations management in the Department of Business Administration at the University of Delaware. Before joining the University of Delaware, he was an assistant professor in the University of Houston. He received a Ph.D. degree in the Department of Industrial & System Engineering at the University at Buffalo. In his industrial experience, he served as a postdoctoral researcher in the Department of Business Analytics & Mathematical Sciences (BAMS) in IBM T.J. Watson research center, and then a senior operations research specialist in Advanced Analytics and Optimization Services (AAOS) in SAS.
HIV; Lymph Node; Mathematical Modeling; Immune System
Dr. Zurakowski’s group develops mathematical models of diseases. By understanding the way that viruses and cells interact, we can learn about the behavior of things we cannot measure from the behavior of things we can. Using models and methods we developed, we have been able to prove that patterns of dead-end HIV DNA circles seen after a particular drug is given to HIV patients prove that HIV continues to replicate in hidden regions of the human body even when HIV medicines have stopped all directly measurable replication. The methods we developed to study HIV can also be applied to traditional engineering applications.
The models we develop allow us to suggest novel experiments that reveal otherwise unmeasurable disease behaviors. We validate our models against clinical and in vitro data using Bayesian inference techniques. The measurements used in our applications are subject to measurement uncertainties of a type not seen in traditional engineering applications. The data is also routinely subject to censoring. In order to accurately use the information present in this kind of data, we also develop novel models of uncertainty.
Data Science related professionals outside of UD.
Dr. Akins is Director of the Center for Pediatric Clinical Research and Development for the Nemours Children’s Health System and an affiliated Full Professor in Materials Science & Engineering, Biomedical Engineering, and Biological Sciences at the University of Delaware. Dr. Akins received his PhD from the University of Pennsylvania where he trained in the Biophysical Cytology and Cell & Molecular Biology Programs with an emphasis on computational imaging, dynamic systems, and advanced statistics. He has contributed seminal work in multiple areas including protein analytics, regenerative medicine, and muscle pathophysiology. Dr. Akins is committed to improving the health and care of children with complex perinatal and congenital diseases through research and innovation. He also currently leads mentoring and scientist development programs focused on building biomedical research and research capacity in the state.
Assistant Professor, Data Science Institute
Helping society through artificial intelligence technologies
Dr. Haider Ali is an Adjunct Faculty (Assistant Professor) in the Data Science Institute at the University of Delaware. He is also a CEO and Founder of the Crowdception Inc. with over 15 years of extensive professional experience (mainly research and development in Computer Vision, Machine Learning, Applied AI, Robotics and Knowledge Based Systems) in Asia, Europe and the United States of America. Prior to joining the University of Delaware, he was an Assistant Research Professor in the Department of Computer Science at the Johns Hopkins University until April, 2019. He was an Associate Research Scientist at Center for Imaging Science (CIS), JHU from 2017-2018 and a Senior Research Scientist at the Institute of Robotics and Mechatronics (RM) of the German Aerospace Center (DLR), Germany from 2011-2017. He received his Ph.D. in Computer Science at Vienna University of Technology, Austria in 2010.
Civil & Environmental Engineering
Machine Learning, Information Retrieval, Recommender System and Large Scale Search Systems
Dr. Bhattacharya research focuses on leveraging machine learning and information retrieval algorithms to build at-scale recommender systems and search systems. Currently Dr. Bhattacharya is a Senior Research Scientist at Netflix Research, where she works on developing at-scale machine learning models for Search and Recommendation Systems. Prior to Netflix, she was a Senior Applied Scientist at Etsy, a two-sided marketplace. At Etsy, Moumita was tech leading a team that developed recommendation systems to show relevant products to Etsy users. Dr. Bhattacharya has a PhD in Computer Science with a focus on Machine Learning and its applications in disease prediction and patient risk stratification. She is actively serving as Program Committees for SIAM International Conference on Data Mining and The Web Conference 2023 since 2020 and is a reviewer for conferences such as WSDM, The Web Conference 2023, American Medical Informatic Association (AMIA), and journals including Journal of the American College of Cardiology, among others.
Imaging, Spectroscopy, Biophysics, Nanotransport, Machine Learning
Hacene Boukari, PhD, is Professor of physics and Associate Dean for Research in the College of Agriculture, Science, and Technology (CAST) at Delaware State University (DSU). He obtained his PhD degree in Chemical Physics from the University of Maryland. His career started while working on a 22-million-dollar NASA project (Zeno Experiment) to build and operate a spectrometer for studying supercritical xenon in microgravity aboard the NASA Space-Shuttle. Before joining DSU (2010), he held several positions, including Senior Scientist at NIH, Guest Researcher at NIST, and Postdoctoral Fellow at University of Maryland. He worked on diverse projects, including understanding the transport properties of supercritical fluids, determining interactions of biopolymers and cells, and probing diffusion of nanoparticles in complex matrices. His current work focuses on combining machine learning methods and novel optical and imaging techniques to investigate interactions of nanoparticles in crowded complex systems and their impacts on the overall behavior of the systems. He received the researcher award from NASA and the DSU research and service awards.
Medical Informatics; Speech Processing; Deep Learning; Data Mining
I received my Ph.D. in Experimental Psychology from The Pennsylvania State University in 1983, although my dissertation research was conducted while working as a researcher at the University of Maryland, conducting studies on the perception of coarticulatory information with James G. Martin. After graduating, I worked as a Research Scientist in the Sensory Communication Research Laboratory (later Center for Auditory and Speech Sciences) at Gallaudet University from 1983 until 1989 conducting research on the application of digital speech processing techniques to hearing enhancement, primarily for acoustic hearing aid users. In 1989 I became the director of the Speech Processing Laboratory of the Applied Science and Engineering Laboratories at the Alfred I. duPont Hospital for Children, now named Nemours Children’s Hospital, Delaware (NCH-D) where my research interests in acoustic phonetics and speech processing expanded to include text to speech synthesis and speech recognition. Since 1989, I have held several positions at NCH-D and am now the director of the Nemours Center for Pediatric Auditory and Speech Sciences (CPASS). There are currently three laboratories in CPASS: the Audit
Psychometrics, Structural Equation Modeling, Psychological Well-Being
Dr. Chen is a senior research biostatistician at the Nemours Center for HealthCare Delivery Science, Associate Professor of Pediatrics at the Thomas Jefferson University. Before joining Nemours, Dr. Chen was an Assistant Professor of Psychology in the Department of Psychology at the University of Delaware and later at the University of Hong Kong. Dr. Chen obtained her Ph.D. from Arizona State University, where she pursued a rigorous course of training in both quantitative methodology and social psychology. Dr. Chen’s scholarly work builds on the foundation of her dual training in quantitative methodology and social psychology. She conducts basic research on measurement, basic research on social/health psychology, and applies her work on measurement to key constructs in social/health psychology. Dr. Chen’s work has been widely cited by researchers, including top ranked journals’ most cited list, and Classics in Academic & Psychological Testing.
statistical machine learning, bioinformatics, survival analysis, data mining, high-dimensional data analysis
Dr. Devarajan is an Associate Research Professor in the Department of Biostatistics and Bioinformatics at Fox Chase Cancer Center (FCCC) and Adjunct Associate Professor in the Lewis Katz School of Medicine at Temple University (TU). He has been an affiliated faculty member in the Center for High-dimensional Statistics in the Department of Statistics, Operations and Data Science at TU. His primary research interests encompass statistical machine learning and data science with applications in bioinformatics, genomics, neuroscience, biomedicine and natural language processing; its principal focus is the development of statistical and computational approaches for massive data sets and includes methods for pattern recognition, outlier detection, feature selection, biomarker discovery, and predictive modeling. He has published over 100 peer-reviewed papers, book chapters and pre-prints. Dr. Devarajan serves as Co-Chair of the Data Safety and Monitoring Board at FCCC and on the editorial board of scientific journals. Previously, he held research positions at the Bristol-Myers Squibb Pharmaceutical Research Institute and AstraZeneca Pharmaceuticals.
Biostatistics, Data Science, Machine Learning, Longitudinal Data, Classification
Md. Jobayer Hossain, PhD, is a Senior Research Scientist and the Director of the Biostatistics Program at Nemours Children’s Health. He has over 20 years of experience in the design and analysis of clinical, epidemiological, and public health studies. His research interests focus on the innovative application of statistical, data science, and machine learning methods to explore etiologic pathways and health trends in diverse pediatric populations that improves the health of children affected by a broad range of diseases, disorders, and health conditions. Besides routine modeling of data, his research focuses on tracking changes in health trajectories; recognizing hidden patterns; creating and predicting classes of distinct patterns; and identifying individual and community-level demographic, clinical and other features responsible for diverse trajectories. Dr. Hossain provides training and education on statistics and analytical software skills at Nemours and affiliated institutions. As an active research and teaching faculty, Dr. Hossain is a lead or co-author for 134 published articles and more than 250 published abstracts and presentations.
Boston Children’s Hospital
Triclosan, Parabens, Asthma, Environment, Children
Medina Jackson-Browne is a Senior Staff Scientist in Division of General Pediatrics at Boston Children’s Hospital. Dr. Jackson-Browne received her PhD in Environmental Health Sciences from the Mailman School of Public Health at Columbia University. Previously, she was an assistant professor in the in Epidemiology program in the College of Health Sciences at the University of Delaware and a postdoctoral research scholar in the Department of Epidemiology at the Brown University School of Public Health. Her primary research focus is understanding the effects of exposure to environmental chemicals, particularly during gestation and in early childhood, on the alteration of immune function and the development of allergic diseases in children.
Health Services Research, Epidemiology, Kidney Disease, Electronic Health Records
Claudine Jurkovitz, MD, MPH, has been working at ChristianaCare Health Services Inc. since 2005 and in 2019 was appointed Director of Clinical Research in the ChristianaCare Value Institute, recently renamed Institute for Research in Equity and Community Health (iREACH). She has been leading the Delaware ACCEL-Center for Translational Research (CTR) Biostatistics Epidemiology Research Design (BERD) core since 2017. BERD scientists provide consultations in biostatistics, health informatics and bioinformatics to Investigators from all ACCEL-CTR Institutions. She was appointed Director of the Delaware INBRE Centralized Research Support Network (CRSN) core in 2017. CRSN’s goal is to leverage existing infrastructure such as the BERD or large local claims databases to make these services available to the INBRE network’s investigators. As a Nephrologist Epidemiologist, Dr. Jurkovitz has developed her own research interests in the field of kidney disease and health services research.
Machine Learning, Text and Image Mining, Biomedical Informatics
Dr. Pengyuan Li is a Research Staff Member from IBM Almaden Research Center. His research focuses on machine learning, text-and-image mining, document analysis, and biomedical informatics. He has developed algorithms and web applications for enabling computer-aid diagnosis and for supporting the biocuration community. His work has been published at top conferences and journals, such as Bioinformatics, Journal of the American Medical Informatics Association, IEEE Journal of Biomedical and Health Informatics, ISMB/ECCB, and CIKM. Dr. Li has served as a program committee member for conferences, such as WWW, and as a reviewer for journals such as Bioinformatics. He has been a visiting scholar at the University of California Los Angeles, the University of British Columbia, and Tongji University for discovering and developing new ideas with researchers from various backgrounds. Dr. Li obtained his PhD degree in Computer Science from the University of Delaware.
Computer vision, genomics, neuroscience
I am a Principal Computational Scientist at The Jackson Laboratory with expertise in neuroscience, computer vision, systems genetics, and machine learning. My graduate training was in pure mathematics, after which I transitioned to systems biology. As a post-doctoral researcher, I developed systems-biology tools to integrate heterogeneous gene-expression data sets and, in a separate post-doctoral position, studied the neural networks underlying learning and memory. In 2016, I was appointed Assistant Professor in the Department of Neurological Sciences at the UVM Larner College of Medicine. In 2020, I took a new position at The Jackson Laboratory as a Senior Computational Scientist. Throughout this time, I have maintained a strong record of extramural funding in genetics, neuroscience, and data science, including a recently awarded R01 for “Integrating high-throughput histology with systems genetics through causal graphical models”. I am also the co-lead of the Data Analysis Core of the JAX-Sen Mouse Tissue Mapping Center. Through this project, my team is developing and implementing state-of-the-art methodologies for spatial ‘omics’.
Big data, social network analysis, machine learning, health services research
Dr. Ostovari is a Lead Research Investigator at the Institute for Research on Equity and Community Health (iREACH), Christiana Care Health Services, Inc. She holds a Ph.D. in Industrial Engineering from Purdue University. Dr. Ostovari is interested in the application of social network analysis and machine learning for improving access to care and health outcomes for patients with chronic conditions. She has successfully obtained external funding, including a Mentored Research Development Award (MRDA) in 2019 and a pilot grant from the DE-CTR ACCEL program in 2021. She has presented her research in multiple national and international conferences, including the American Medical Informatics Association (AMIA) Annual Symposium, and has several publications in peer-reviewed journals, such as PLOS One and JAMIA.
Machine learning, neural networks, natural language processing
Dr. Reedy received a Ph.D in Cognitive Science from Rensselaer Polytechnic Institute in 2020 with a thesis combining a diploid genetic algorithm with a social artificial life simulation. They joined the Biomedical Research Informatics Center at Nemours Children’s Hospital in 2022 as a research data scientist. At Nemours, they use machine learning, natural language processing, and data analysis to extract information from health records to better understand and improve children’s health.
Dr. Tawiah is an Assistant Professor at Delaware State University, where he teaches introductory and upper-level sociology courses. His research focuses on health disparities inequality, labor, family, machine learning, and data science education. He is also a consultant with the Food Science Program at Delaware State University, applying data science expertise. He has successfully obtained funding from USDA-AFRI and USDA-NIFA to introduce data science into classroom education.
Integrated data, research and practice partnerships, data driven policy, research to policy best practices
Laura Wallace, Ph.D. is a researcher in the Learning Supports Division, Early Childhood practice area at American Institutes for Research (AIR). Dr. Wallace has over 10 years of research and evaluation experience. Many of her projects have been participatory evaluations and research-practice partnerships involving collaboration with a range of stakeholders including community, state, and national partners. Dr. Wallace’s focus is on zero to 3 intervention and prevention programs, and she has expertise in home visits and integrated early childhood programs. She has conducted research in child welfare, early childhood education workforce development, childcare cost analysis, and large-scale integrated state administrative data. Additionally, Dr. Wallace has direct service experience and worked as the Director of Early Learning at the Maternity Care Coalition in Philadelphia, PA. Dr. Wallace holds a Ph.D. in School Psychology from Lehigh University in Bethlehem, PA where she focused on the evaluation of integrated birth to three child welfare programs. She also holds a MS in psychology from Villanova University with a specialization in child development and parent child interactions.
Director of Biostatistics, Christiana Care Health System
Fellow, American Heart Association
Biostatistics, public health, health economics, bioinformatics, data analysis
As director of biostatistics at the Christiana Care Health System, I carried out study design, methodology research, data analysis, writing drafts as the lead author for peer reviewed research papers, and teaching courses. I published manuscripts in New England Journal of Medicine, Journal of American Medicine, JACC, Circulation, Journal of Clinical Hypertension, The Canadian Journal of Cardiology, among others. My work and papers have been widely reported via media and cited in academic journals. I have worked extensively on several large, international, multi-center, randomized clinical trials, including the Clinical Outcomes Utilizing Revascularization and Aggressive Drug Evaluation, the Enoxaparin and Thrombolysis Reperfusion for Acute Myocardial Infarction Treatment, American College of Cardiology Foundation-The Society of Thoracic Surgeons Collaboration on the Comparative Effectiveness of Revascularization Strategies, Systolic Blood Pressure Intervention Trial, and Individual Breastfeeding Support with Incentives for Low-income Mothers.