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.
Personalized Federated Learning with First Order Model Optimization
Michael Zhang, Karan Sapra, Sanja Fidler, Serena Yeung, José M. Álvarez