Yuan Zhou is an Associate Professor in the Department of Computer Science at the University of Illinois Urbana-Champaign (UIUC). His research interests are in theoretical computer science, focusing on the design and analysis of algorithms, machine learning theory, data science, and computational complexity. He is particularly known for his contributions to bandits, reinforcement learning, high-dimensional statistics, and approximation algorithms. Dr. Zhou earned his Ph.D. from Carnegie Mellon University in 2011 and previously held positions at Indiana University Bloomington as an Assistant Professor and was a Simons-Berkeley Research Fellow before joining UIUC in 2018.
Yuan Zhou's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
Received the National Science Foundation CAREER Award in 2017, a prestigious award supporting early-career faculty who have the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization.
Awarded a Sloan Research Fellowship in Computer Science in 2017, recognizing outstanding early-career scientists and scholars of outstanding promise in their respective fields.
Participated as a Simons-Berkeley Research Fellow during the Fall 2013 program on 'Theoretical Foundations of Data Science', contributing to cutting-edge research in the field at the Simons Institute for the Theory of Computing.
Co-recipient of the Best Student Paper Award at the IEEE Symposium on Foundations of Computer Science (FOCS) in 2010 for the paper 'Almost Optimal Multiplicative Weights Updates for an Adversarial Bandit'.
University of Washington - Year 2012
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