معرفی
Yu-Xiang Wang is an Associate Professor at UC San Diego's Halıcıoğlu Data Science Institute and Department of Computer Science and Engineering. He holds the Eugene Aas Chair and previously served as an Assistant Professor at UCSB (2018-2023). His research focuses on statistical machine learning, differential privacy, and provably efficient algorithms for challenges like privacy-constrained learning and sequential decision-making. He leads the S2ML Lab and co-founded the Center for Responsible Machine Learning.
Education: PhD in Statistics & ML from Carnegie Mellon University (2017), MEng/BEng in Electrical Engineering from National University of Singapore (2013/2011). Notable awards include NSF Early CAREER and Google Research Scholar Awards. His work spans foundational theory and practical applications, including watermarking AI-generated content and privacy-preserving techniques.
Key projects include the autodp package for differential privacy computation, and contributions to offline reinforcement learning and nonparametric regression. Advised students include Dheeraj Baby, Rachel Redberg, and Yuqing Zhu. Active in teaching courses on machine learning and differential privacy.
