Dr. Deepak R. Mishra is the Merle C. Prunty, Jr. Professor and Head of the Department of Geography at the University of Georgia, where he also directs the Center for Geospatial Research (CGR) and the Small Satellite Research Laboratory (SSRL). His research focuses on using geospatial and remote sensing technologies to study and monitor inland and coastal water resources.

Dr. Mishra’s projects integrate field-based spectroscopy with satellite remote sensing to investigate coastal and aquatic ecosystems affected by natural and anthropogenic forces. His ongoing work includes developing satellite-based decision support tools for coastal conservation, modeling harmful algal blooms, studying carbon sequestration in tidal wetlands, mapping seagrass and coral disease, and creating cyberinfrastructure for monitoring coastal environments. His lab also engages in small satellite development for space-based AI applications.

Yuan Ke is an Associate Professor in the Department of Statistics at the University of Georgia. Before joining UGA, he was the Bruce Lindsay Visiting Assistant Professor at Pennsylvania State University and a Postdoctoral Research Associate in the Department of Operations Research and Financial Engineering at Princeton University. He earned his Ph.D. in Mathematics from the University of York, an M.Sc. in Statistics from the London School of Economics, and a B.Sc. in Physics from Beijing Normal University.

Dr. Ke’s research focuses on high-dimensional statistics, robust statistics, time series analysis, and statistical machine learning. His work lies at the intersection of statistical theory and practical methodology, developing tools to address modern data challenges characterized by complexity and scale. Through his scholarship and teaching, Dr. Ke contributes to the advancement of both foundational and applied aspects of data science, preparing students and collaborators to engage with emerging problems in machine learning and quantitative analysis.

Xiaoming Zhai investigates innovative science assessment and supports teachers in implementing assessment practices, with a current emphasis on applying AI and machine learning in science education. He serves as Principal Investigator on two NSF-funded projects and holds a Ph.D. in Curriculum and Instruction (physics) from Beijing Normal University (2017).

Zhai is Guest Editor for a Special Issue of the Journal of Science Education and Technology on applying machine learning in science assessment and serves on the editorial boards of the Journal of Research in Science Teaching, Journal of Science Education and Technology, and Disciplinary and Interdisciplinary Science Education Research. His research addresses (a) the use of innovative assessments—including machine learning—to examine complex constructs in science learning and teaching and (b) the application of assessment results to instruction, with publications in journals such as Journal of Research in Science Teaching, Studies in Science Education, International Journal of Science Education, Research in Science Education, Computers & Education, and British Journal of Educational Technology.

Dr. Juliet Sekandi is an Associate Professor in the Department of Epidemiology and Biostatistics and Director of the Global Health Institute in the College of Public Health at the University of Georgia, where she also serves as Graduate Coordinator for the Certificate in Global Health program. A physician and global health scholar, she holds medical and surgical degrees from Mbarara University of Science and Technology in Uganda, an M.S. from Case Western Reserve University, and a Doctor of Public Health (DrPH) from UGA.

Dr. Sekandi’s research focuses on infectious disease prevention and health service innovation, with particular emphasis on tuberculosis, HIV, and maternal health. Much of her work has centered on early detection of infectious diseases in urban communities, aiming to reduce diagnostic delays and interrupt transmission. Her more recent work explores mobile health (mHealth) approaches to improve healthcare delivery in developing countries.

Drew H. Abney is an Assistant Professor whose research explores how behaviors and social interactions shape developmental trajectories throughout infancy and early childhood. His work investigates the dynamic processes underlying early development, using a variety of approaches to capture the richness of real-world behavior. Studies in his lab range from controlled laboratory experiments to naturalistic, free-flowing toy play sessions and daylong recordings of multimodal behavioral data, including vocalizations and body movements.

Dr. Abney applies and advances techniques from applied computational social science and dynamical systems theory to better understand how infants and toddlers develop through social interaction. His work combines methodological rigor with innovative data collection and analysis, aiming to uncover the complex, interdependent factors that drive early developmental change. He earned his Ph.D. in Cognitive and Information Sciences from the University of California, Merced, and completed a postdoctoral fellowship in Developmental Psychology at Indiana University.

Kyle Johnsen is a Professor in the College of Engineering at the University of Georgia. He joined UGA in 2008 after earning his Ph.D. in Computer Engineering from the University of Florida, where he also completed his M.S. and B.S. His research focuses on emerging human-computer interaction technologies for health, education, and the environment.

Johnsen leads the Georgia Informatics Institutes and directs the Virtual Experiences Laboratory. His areas of expertise include virtual reality and multimodal 3D user interfaces, with an emphasis on developing interactive systems that advance applications in his stated domains.

Dr. Neal Outland is an Assistant Professor in the Department of Psychology at the University of Georgia, where he is part of the Industrial-Organizational Psychology program. He received his Ph.D. in Industrial/Organizational Psychology from DePaul University and his B.S. in Psychology from Loyola University New Orleans.

Dr. Outland’s research examines team interaction dynamics, team composition, and cognition within complex and dynamic environments. His work explores how characteristics of individual team members and patterns of interaction contribute to collective success. He also conducts research using computer-simulated teams as analogues for real-world team behavior. Dr. Outland teaches undergraduate and master’s-level statistics courses and continues to develop research on team cognition and computational modeling.