Michael Zhang
Applied Scientist at Amazon
Boston, Massachusetts, United States
Summary
🤩
Rockstar🎓
Top SchoolMichael Zhang is an applied scientist and PhD candidate at the University of Toronto with 11 years of experience researching deep neural networks, optimization, and responsible ML applications. He has blended academic rigor and industry impact through roles at Vector Institute, Google, Tesla, and now Amazon, with work spanning dynamics models for offline RL to autonomy and NLP. A seasoned educator, he taught introductory ML to 200+ undergraduates and won teaching awards at Berkeley, reflecting strong communication of complex ideas. His research, advised by Jimmy Ba and rooted in Berkeley training, focuses on understanding how deep models learn and on practical optimization algorithms that transfer to real systems. Michael’s background in both large-scale production internships and foundational RL labs gives him a rare cross-section of deployment-minded research expertise. Based in Boston, he bringsto teams a track record of publishing, teaching, and shipping ML systems that balance theory with real-world constraints.
11 years of coding experience
8 years of employment as a software developer
Master of Science - MS Electrical Engineering and Computer Science, Master of Science - MS Electrical Engineering and Computer Science at University of California, BerkeleyDoctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at University of Toronto
Github Skills (13)
optimizer8
optimization7
robotics6
efficientnet6
java5
pybullet5
mujoco5
gymnasium4
deep-reinforcement-learning4
pytorch4
reinforcement-learning4
spring4
resnet4
Programming languages (3)
Github contributions (5)
michaelrzhang/lookahead
Aug 2019 - Jan 2021
Implementation for the Lookahead Optimizer.
Contributions:5 commits, 2 PRs, 6 pushes in 1 year 5 months
optimizationlookaheadoptimizer
michaelrzhang/michaelrzhang.github.io
Aug 2015 - Aug 2017
Contributions:42 pushes, 1 branch in 2 years
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