# 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 senior at Harvard studying Statistics and Computer Science. Right now I work with Serena Yeung on computer vision and deep learning, and Susan Murphy on reinforcement learning, both motivated by applications to healthcare. I’ve also done research in meta-learning and RL policy characterization with Serena and Susan at the Statistical RL Lab, and Alex D’Amour at Google Brain, and am fortunate to be academically co-advised by David Parkes and Joe Blitzstein.

Previously I spent a summer wondering if RL could be applied to the markets at DRW, and before that I built tools in computational healthcare in Ken Mandl’s group at Boston Childrens’ Hospital and genome editing under George Church at Harvard Medical School and the Wyss Institute.

# Research

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

Michael Zhang*, Xiaotian Cheng*, Daniel Copeland, Gabriel Brat, and Serena Yeung
(in preparation)

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)