Yuxin Chen

Yuxin Chen is an Assistant Professor in the Department of Computer Science at the University of Chicago, specializing in the development of interactive machine learning systems. His research areas include active learning, machine teaching, reinforcement learning, and Bayesian optimization. He received his PhD in Computer Science from ETH Zurich and conducted postdoctoral research at Caltech, focusing on computational and mathematical sciences. Chen's work has garnered several accolades, including the Google European Doctoral Fellowship, the Swiss National Science Foundation Early Postdoc Mobility Fellowship, and the PIMCO Data Science Postdoctoral Fellowship. His research aims to advance the interactivity and practicality of artificial intelligence through the development of interpretable models and active learning techniques.

• 2019–Present·University of Chicago·Assistant Professor
  • Research focuses on active learning, machine teaching, reinforcement learning, and Bayesian optimization, with an emphasis on developing interactive machine learning systems.
• 2017–2019·California Institute of Technology (Caltech)·Postdoctoral Researcher
  • Conducted research in computational and mathematical sciences, exploring the theoretical foundations and practical applications of interactive learning systems.

• 2012–2017·ETH Zurich·PhD (Computer Science)
  • Supervised by Andreas Krause, research concentrated on interactive machine learning and probabilistic reasoning.
• 2005–2009·University of Science and Technology of China·Bachelor (Computer Science)
  • Awarded for excellent thesis work.