# Intro

Welcome to my rendition of yet another vaguely academic personal site (that also sort of looks like the rest of them)!

In all seriousness, I’m Michael, a first-year computer science PhD student at Stanford. I’m excited to rotate with Chris Ré and Chelsea Finn, and spent Summer-Fall of these COVID-times at NVIDIA with José M. Álvarez.

I’m broadly interested in making machine learning more usable “in the real world”, primarily from the aspects of robustness and personalization, and learning with less labels.

Previously I received my A.B. in Statistics and Computer Science at Harvard in 2020, where I’m grateful to have worked with Serena Yeung, Susan Murphy, and Alex D’Amour on methods and applications motivated by the intersections of computer vision and reinforcement learning with healthcare.

# Research

Personalized Federated Learning with First Order Model Optimization

Michael Zhang, Karan Sapra, Sanja Fidler, Serena Yeung, José M. Álvarez
ICLR 2021

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Using Computer Vision to Automate Hand Detection and Tracking of Surgeon Movements in Videos of Open Surgery

Michael Zhang, Xiaotian Cheng, Daniel Copeland, Arjun Desai, Melody Y. Guan, Gabriel A. Brat, Serena Yeung
AMIA 2020 Annual Symposium

Characterizing Policy Divergence for Personalized Meta-Reinforcement Learning

Michael Zhang
NeurIPS 2019 Workshops on Deep Reinforcement Learning and Meta-Learning

Design and Assembly of CRISPR/Cas9-based Virus-like Particles for Programmable and Orthogonal Genetic Engineering in Mammalian Cells

Michael Zhang
Intel Science Talent Search 2016 Finalist (2nd Place)