Yu-xiang Wang

Associate Professor

San Diego, California, United States
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Summary

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Senior
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Top School
Yu-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.
code11 years of coding experience
job7 years of employment as a software developer
bookCarnegie Mellon University
bookMaster of Engineering (MEng), Electrical Engineering, Master of Engineering (MEng), Electrical Engineering at National University of Singapore
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Github Skills (38)

javascript10
dataflow10
python10
mxnet10
training-data10
scala10
privacy10
go10
differential-privacy10
deep-learning10
ranking10
mobile10
science10
computer-science10
react10

Programming languages (3)

C++Jupyter NotebookPython

Github contributions (5)

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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
differential-privacy
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