Mike Wu
me[at]mikehwu.com
Publications | CV | Github
LinkedIn | @mike_h_wu
I'm a final year PhD student in Computer Science at Stanford University advised by Noah Goodman. My research is in generative models and self-supervised learning. I'm also interested in ML applications to web3.
I did my undergrad in CS at Yale where I worked on astrostatistics and started YHack, one of the largest collegiate hackathons. Then, I took a year off before starting graduate school, where I worked in the AML team at Facebook Research.
Mike Wu
me[at]mikehwu.com
Publications | CV | Github
LinkedIn | @mike_h_wu
I'm a final year PhD student in Computer Science at Stanford University advised by Noah Goodman. My research is in generative models and self-supervised learning. I'm also interested in ML applications to web3.
I did my undergrad in CS at Yale where I worked on astrostatistics and started YHack, one of the largest collegiate hackathons. Then, I took a year off before starting graduate school, where I worked in the AML team at Facebook Research.
Recent News
- Hot off the press! New paper on approximate probabilistic inference as masked language modeling. Check out transformers being Bayesian.
- Paper on a new DeFi automated market maker using a constant power root invariant. Check out the tl;dr here.
- Launching a new course on Data-Centric Deep Learning with Andrew Maas through Co:rise. It's a four week project-based whirlwind to deep learning ops. Check it out!
- Built Tutela, an analytics tool on Ethereum to access the anonymity of different wallets. Check out the whitepaper here. The product was featured in crypto@stanford and covered by the Golem Foundation.
- New method applying meta-learning to give feedback to student code was covered by the New York Times. The approach was used at Code in Place 2021 on 16,000 student solutions!