معرفی
Tianbao Yang is an Associate Professor of Computer Science & Engineering at Texas A&M University and a Herbert H. Richardson Faculty Fellow. His research focuses on machine learning, optimization, and their applications in AI, medical imaging, and fair AI. He holds a Ph.D. from Michigan State University and a B.Eng. from the University of Science and Technology of China.
Key research interests include deep AUC maximization, non-convex optimization, stochastic algorithms, and self-supervised learning. His work on LibAUC, a library for deep learning optimization, has achieved top performance in competitions like the Stanford CheXpert and MIT AI Cures challenges.
- Education: Ph.D. in Computer Science (Michigan State University, 2012), B.Eng. in Automation (University of Science and Technology of China, 2007).
- Awards: NSF CAREER Award (2019), UIowa Dean's Excellence in Research Scholar (2019), COLT Best Student Paper (2012).
- Grants: NSF-Amazon Joint Fair AI Grant ($800K, 2022–2025), NSF RI Program for imbalanced data (2021–2024).
His lab (OptMAI Lab) develops algorithms for X-risk optimization, stochastic optimization, and distributed learning. Notable contributions include first-place wins in medical imaging competitions and advances in federated learning and fair AI.
