Hanan Abou Ali is a PhD candidate in the Geography and Spatial Sciences department working with Dr. Kyle Davis. Her research is focused on using remote sensing and statistical modeling for crop mapping and studying food security and sustainable agriculture in rural livelihoods and smallholder farms. Hanan has a BS in Surveying Engineering from the Lebanese International University and a MS in GIS from Idaho State University where she was funded through the Fulbright scholarship program. She is passionate about teaching and has experience teaching both undergraduate and graduate level courses and enjoys helping students with their research projects.

Tatiana Acero-Cuellar is a Unidel Distinguished Graduate Fellow and a graduate student in the Department of Physics and Astronomy under the supervision of Dr. Federica Bianco. She completed her B.Sc in Physics at the Universidad Nacional de Colombia. She is a member of the Rubin LSST Dark Energy and Transients and Variable Stars Science Collaborations. Her current research is the study of the potential for Convolutional Neural Network and other machine learning models for the separation of astrophysical transients from image artifacts that does not rely on the computationally expensive Difference Image Analysis technique. She is also currently implementing forward models of dust and transients for the generation of a library of synthetic light echoes.

Shovan Bhowmik is a first year Computer Science PhD student working as a Research Assistant (RA) under the supervision of Professor Dr. Cathy Wu and Professor Dr. Vijay Shanker. His research interests focus in the wide area of data science including Machine Learning, Natural Language Processing, Computational Biology, etc. Currently, his research involves impact relation extraction such as Protein Protein Interaction (PPI), Post Translational Modifications (PTMs), Biological Processes, Chemical-Gene Interactions from the bio-domain literature by mining texts. Previously, he completed his BSc in Computer Science from Bangladesh and published multiple research papers in the field of data science where he received two best paper awards in the international conferences – one for the investigation of N-gram tokens impact in sentiment analysis and another was for the prediction of early colorectal cancer by analyzing colon polyps from images using transfer learning technologies.

Daria Blinova is a Ph.D. student at the Department of Political Science and International Relations at the University of Delaware. Her concentrations of study are International Relations and Political Methodology. Daria’s interests are diverse and include issues relating to international organizations dealing with environmental politics and climate change, manipulation of information in autocratic regimes, international security, and others. She is particularly interested in methodology and data analysis (including text analysis) that she applies in her works. Prior to joining the Ph.D. program at UD, Daria received a Master’s in International Development Administration from Western Michigan University after which her passion for international politics and analytics developed increasingly.

Siddharth is a PhD student working with Dr. Federica Bianco. His research focuses on the use of data science within time-domain astronomy. Siddharth’s interests lie in the exploration of distance metrics and time series, and he is particularly drawn to the application of machine learning for the detection of anomalies in transients. Siddharth is also involved in science with Rubin Observatory, and is a member of the Rubin LSST Transients and Variable Stars and Informatics and Statistics Science Collaborations. Previously, Siddharth completed his BS-MS in Physics from the Indian Institute of Science Education and Research, Bhopal, where he was an INSPIRE fellow.

Riley received a B.S. in Physics from Western Washington University and M.S. in Physics from the University of Delaware, where he is working on completing his Ph.D under supervision of Dr. Federica Bianco studying rapid brightening of stars called “flares”. He is a member of the Rubin LSST Transients and Variable Stars Science Collaboration and works on enabling the study of stellar flares in the LSST Wide Fast Deep survey by taking advantage of atmospheric refraction.

Shar is a NSF Graduate Student Research Fellow working at the intersection of astrophysics and data science under Dr. Federica Bianco. They build deep learning networks to extract rapid transient phenomena from astronomical survey data, looking for extreme astrophysical events that test our understanding of high-energy and fundamental physics. Outside of their graduate studies, they are also an award-winning dancer in the social partner dance of west coast swing.

Easton is a PhD student in the Physics & Astronomy department studying brown dwarfs with Dr. John Gizis. His current research focuses on preparing for brown dwarf discovery in major upcoming sky surveys, such as the Rubin LSST. He uses machine learning to identify and select the comparatively rare brown dwarfs from large survey databases. He is a member of the Rubin LSST Stars, Milky Way, and Local Volume Science Collaboration and is also an associate at the local Mt. Cuba Astronomical Observatory. Previously, Easton received a MS in Physics: Concentration in Astronomy from San Francisco State University where he studied X-ray binaries in globular clusters.

Bhoktear is a 3rd-year PhD candidate in the Department of Geography and Spatial Sciences at UD. His research focuses on the intricate relationship between climate change and deforestation in Nigeria, with a keen interest in understanding the effects of cropland expansion on food security. Passionate about education, Bhoktear was recognized as the “Best Teaching Assistant” last year, a testament to his commitment and hard work. Outside of academia, he relishes long drives, enjoys swimming, and has a fondness for cricket.

Kyungmin Lee is a Ph.D. candidate in Energy and Environmental Policy at the University of Delaware under Dr. Gregory Dobler. Her research interests lie at the intersection of energy, climate change, urban development, and social sustainability. With a broad research interest covering areas of environmental planning in international and regional contexts, she is interested in understanding dynamic interactions between humans and the environment. Her current research focuses on the impact of human behaviors and the built environment on energy use and heat in cities. With a specific interest in quantitative and spatial analysis methods, she has also developed an interest in big data analysis for a public policy using machine learning, image processing, and computer vision techniques. Prior to joining the Ph.D. program, she worked in the field of international environmental development and cooperation at the government research institute, governmental agency, and United Nations. She received a Bachelor of Arts in Economics from Sungshin Women’s University and a Master of City Planning in Environmental Studies from Seoul National University in South Korea.

Tang Li is currently pursuing Ph.D. in Computer Science. He is working under the supervision of Dr. Xi Peng from the department of Computer and Information Science. His current research interest is Machine Learning, Deep Learning, Explainable Machine Learning, and Computer Vision.

Manan Sarupria is a PhD student in the Department of Geography and Spatial Sciences. His research is focused on understanding the impacts of climate change on coastal ecosystems using machine learning and big data analysis. Currently, he is utilizing satellite data to quantify the impacts of saltwater intrusion on coastal farmlands in Delmarva, under the supervision of Dr. Pinki Mondal. Manan holds a Bachelor’s degree in Chemical Engineering and a Master’s degree in Water Resources. He is passionate about exploring the intersection of geospatial data science and climate change. Besides his research, Manan also appreciates the work-life balance that is promoted at UD. He is a passionate drummer, cyclist, and chef-at-home, and enjoys exploring his creative side outside of academia.

Jared Sharpe is a PhD candidate in Financial Services Analytics. His research focuses on applications of Natural Language Processing (NLP) on the Initial Public Offering (IPO) filing process. Jared has presented his work for a variety of audiences including the 4th Workshop on Financial Technology and Natural Language Processing (FinNLP) and the Financial Industry Regulatory Authority (FINRA). Jared was named Outstanding Senator by the Graduate Student Government at UD in 2022 for his contributions evaluating the cost of living for UD graduate students. Jared fell in love with University of Delaware while earning his undergraduate degree in Actuarial Sciences. You can often find Jared walking his dog, Roger, around the Green. Jared is also an avid gardener and DIY-er.

Olushola Soyoye is pursuing a Ph.D. in Educational Statistics and Research Methods. His research interests include data mining, missing data, as well as the application of artificial intelligence (AI) to data in education, health and social policy. He received his bachelor’s and master’s degrees in mathematics education from Tai Solarin University of Education, Ijebu-Ode, Nigeria and the University of Illinois, Urbana-Champaign, respectively.

Swati is a 3rd PhD candidate in the Financial Services Analytics department at the University of Delaware, where I am focused on researching fairness and bias in language models. In addition to my academic pursuits, I also have a wealth of experience in analytics, software development, and product management. My background in these areas has given me a well-rounded skill set and the ability to approach problems from multiple angles. I am passionate about using my skills to make a positive impact in the world and am excited to continue my research and make meaningful contributions to the field of technology and financial services analytics.

Lan is an Urban Data Scientist and PhD candidate at the University of Delaware in Energy and Environmental Policy. Before coming to Udel, she worked as a Data Scientist at Tongji University for almost two years. Currently, her work uses observational methods and data from the “Urban Observatory” (http://MUONetwork.org) to analyze images of city skylines through the application of computer vision and machine learning techniques to study energy consumption and lighting technology in cities, as well as inform operations and energy distribution policies. In detail, she explores three core topics in urban energy: outage detection and grid stability evaluated through urban lighting variability, energy efficient lighting changeover rates, and energy end-use behavior.