Yu-xiang Wang
Associate Professor
San Diego, California, United States
Summary
👤
Senior🎓
Top SchoolYu-Xiang Wang is an Associate Professor at UC San Diego and director of the Scalable Statistical Machine Learning lab, specializing in statistical theory, differential privacy, reinforcement learning, online learning, and deep learning. With 11 years of experience spanning academia and industry, he was previously faculty at UC Santa Barbara and an applied scientist at Amazon Web Services, and holds a PhD from Carnegie Mellon. His work bridges rigorous theory and practical systems for scalable, privacy-preserving machine learning, often focusing on online and reinforcement settings where decisions must be made under uncertainty. Based in San Diego, he combines a background in electrical engineering from the National University of Singapore with cutting-edge ML research, and leads interdisciplinary efforts in responsible machine learning.
11 years of coding experience
7 years of employment as a software developer
Carnegie Mellon UniversityMaster of Engineering (MEng), Electrical Engineering, Master of Engineering (MEng), Electrical Engineering at National University of Singapore
Github Skills (38)
portable10
notebook10
javascript10
dep10
dataflow10
python10
mxnet10
machine-learning10
scheduler10
information-theory10
differential-privacy10
ranking10
golang10
mutation10
science10
Programming languages (3)
Github contributions (5)
zackchase/label_shift
Jan 2018 - Feb 2018
Contributions:20 commits in 23 days
yuxiangw/autodp
Apr 2019 - Aug 2022
autodp: A flexible and easy-to-use package for differential privacy
Contributions:3 releases, 11 reviews, 58 commits in 3 years 4 months
information-theoryprivacydifferential-privacyuse-packagedifferential
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