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Resident Faculty

Strategic faculty hiring across and within colleges in foundational and applications areas of data science, complementing current strengths of 100+ faculty.


Roghayeh (Leila) Barmaki
Assistant Professor, Computer and Information Sciences

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 (HCI@UD).

Her research interests span Multimodal Data Analytics, Human-Computer Interaction, Virtual and Augmented Realities with applications in Education and Healthcare.

Rahmat Beheshti
Assistant Professor, Computer and Information Sciences

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.

Federica Bianco
Assistant Professor, Physics / SPPA

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 Brockmeier
Assistant Professor, Electrical and Computer Engineering, Computer and Information Sciences

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.

Zachary Collier
Assistant Professor, School of Education/CRESP, Evaluation, Measurement and Statistics

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.

Kyle Davis
Assistant Professor, Geography and Spatial Sciences
Assistant Professor, Plant and Soil Sciences

sustainable agriculture; food-energy-water nexus; food security and nutrition

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.

Gregory Dobler
Assistant Professor, Public Policy & Administration
Assistant 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.

Jing Gao
Assistant Professor of Geospatial Data Science, Geography and Spatial Sciences

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.

Medina Jackson-Browne
Assistant Professor, Epidemiology

Triclosan, Parabens, Asthma, Environment, Children

Medina Jackson-Browne is an assistant professor in the new program in Epidemiology at the College of Health Sciences. Dr. Jackson-Browne received her PhD in Environmental Health Sciences from the Mailman School of Public Health at Columbia University. Previously, she was 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. She recently completed a NIEHS F32 Fellowship award examining the impact of perinatal triclosan exposure on the development of asthma and eczema in children.

Pinki Mondal
Assistant Professor, Geography and Spatial Sciences

Remote sensing; GIS; Agriculture; Forest; Climate

Dr. Pinki Mondal is an interdisciplinary geospatial 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, the US, and 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 developing 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.

Xi Peng
Assistant Professor, Computer and Information Sciences

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
Assistant Professor, Applied Economics and Statistics

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.

Xiugang Wu
Assistant Professor, Electrical and Computer Engineering, Computer and Information Sciences

Xiugang Wu is an assistant professor at the University of Delaware, jointly appointed in Electrical and Computer Engineering, and Computer and Information Sciences. Previously, he was a postdoctoral fellow in Electrical Engineering at Stanford University, and received his Ph.D. degree in Electrical and Computer Engineering from the University of Waterloo. His research interests are in information theory, networks, data science, and the interplay between them. He is a recipient of the 2017 NSF Center for Science of Information (CSoI) Postdoctoral Fellowship.

Our Mission

The Institute aims to accelerate research in data science, serving as a nucleating effort to catalyze interdisciplinary research collaborations across fields impacting our society.