Yuexing Hao is a Ph.D. student at Cornell University and an IvyPlus Ph.D. Exchange Scholar at MIT. She is also a research affiliate of the Mayo Clinic Radiation Oncology department. Yuexing’s research focuses on Health Intelligence, Human-Computer Interaction, and AI. She has worked on several AI-based prototype to advance the field of digital health, agriculture, and education. She has rich experience in co-design, co-developing iterative prototypes with users, and conducting evaluations of AI-based prototype quality and user experience.
Yue Huang
Haoran Zhang is a PhD student at the Laboratory for Information and Decision Systems at MIT, advised by Prof. Marzyeh Ghassemi. His research focuses on methods to construct fair and robust machine learning models which maintain their performance across real-world distribution shifts. He is also interested in the application of such methods in the healthcare domain. His research has appeared in venues such as Nature Medicine, NeurIPS, ICML, ICLR, and ACM FAccT. Before joining MIT, Haoran received his M.Sc. from the University of Toronto and his B.Eng. from McMaster University.
Chenyang Zhao
Zhenwen Liang
Paul Pu Liang
Lichao Sun is an Assistant Professor in the Department of Computer Science and Engineering at Lehigh University and an Adjunct Professor at the Mayo Clinic. Dr. Sun’s research centers on generative AI models for biomedical applications, particularly BiomedGPT, a versatile, open-source vision-language model. BiomedGPT has been rigorously evaluated, achieving state-of-the-art results in 16 out of 25 benchmarks. Notably, human evaluation highlights its near-expert-level performance in radiology question answering, report generation, and summarization. Dr. Sun’s work demonstrates how thorough evaluation of multi-modal AI can revolutionize medical diagnostics and improve workflow efficiency.
Yue Zhao
Saleh Kalantari is an Associate Professor in the Department of Human-Centered Design at Cornell University. He leads the Design and Augmented Intelligence Lab (DAIL), where his research focuses on developing digital tools to better understand the impacts of both virtual and built environments on human behavior. Drawing from advances in complementary disciplines such as the behavioral sciences, neuroscience, and computational modeling, Dr. Kalantari promotes a human-centered approach grounded in empirical testing to better evaluate how design choices impact outcomes such as psychological stress and navigation behavior for diverse populations. Much of his research is directed toward analyzing human-building interactions during spatial navigation in large facilities such as hospitals.
Xiangliang Zhang
Marzyeh Ghassemi is an Associate Professor at MIT in Electrical Engineering and Computer Science (EECS) and Institute for Medical Engineering & Science (IMES), and a Vector Institute faculty member holding a Canadian CIFAR AI Chair and Canada Research Chair. She holds MIT affiliations with the Jameel Clinic and CSAIL. Dr. Ghassemi’s Healthy ML Group emphasizes the evaluation of machine learning in healthcare, highlighting how state-of-the-art techniques can introduce biases, especially against minority groups. Their research focuses on correcting these biases, enforcing fairness in models, and assessing how clinical experts interact with AI systems. They also investigate how explainability methods and the delivery of AI recommendations impact model performance and fairness in real-world health applications.