Dr. Zhe is a full professor in the School of Information and Director of the Institute for Successful Longevity at FSU. As a biomedical informatician, his research intersects with biomedical/health informatics, computer science, and information science. He specializes in machine learning, NLP, and knowledge representation. He is an elected fellow of IAHSIand AMIA.

Dr. Gubanov is an assistant professor and a lead PI on a multi-year NSF ($550K) grant and a Casey DeSantis Cancer Innovation Fund ($1.2M) consortium grant with Moffitt Cancer Center to develop new AI for better cancer practices. He earned his PhD from the University of Washington and completed a postdoc at MIT CSAIL. His honors include the Amazon AI AWS Research Award, the Communications of the ACM (CACM) Award, the ACM SIGMOD Research Highlights Award, and the IEEE ICDE Best Paper Award.

Dr. Feng’s recent research focuses on machine learning theory and algorithm design, reinforcement learning in stochastic control, conditional McKean–Vlasov SDEs, data-driven modeling, and the signature method. He is also interested in stochastic analysis, rough path theory, and sub-Riemannian geometry.

Dr. Dexter is an assistant professor of scientific computing at FSU. His research focuses on computational mathematics, scientific machine learning, and uncertainty quantification, applied to areas like energy systems and deep learning. He has published at premier venues like NeurIPS and ICML and is passionate about advancing interdisciplinary research.

Dr. Bhasuran is a researcher in clinical data science and biomedical informatics with over a decade of experience developing AI classification and prediction models. His work integrates clinical NLP, machine learning, and generative AI to advance computational methods for population health and clinical decision-making. His interests include causal inference, knowledge graphs, and fairness/explainability in AI systems.