معرفی
Yuxin Chen is an Assistant Professor in the Department of Computer Science and a faculty member of the Committee on Computational and Applied Mathematics (CCAM) at the University of Chicago. His research focuses on interactive learning systems, machine learning, and machine teaching with applications in optimization, reinforcement learning, and multi-fidelity modeling.
- PhD in Computer Science from ETH Zurich (2017)
- MS in Computer Science from the University of Kansas (2011)
His work spans Bayesian optimization, active learning, and policy improvement algorithms, addressing challenges in data-efficient decision-making and robustness. Recent publications highlight advancements in constrained optimization, neuromorphic computing, and sustainability applications.
Scientific awards include the Best Paper Award at ICML Workshop on Constructive Machine Learning (CML), 2015 and the MSDE Recent HOT Article, 2025. He actively seeks PhD students for his research group.
