Chris De Sa

— Gates Hall, Room 450

I am an Assistant Professor in the Computer Science department at Cornell University. I am a member of the Cornell Machine Learning Group. My research interests include algorithmic, software, and hardware techniques for high-performance machine learning, with a focus on relaxed-consistency variants of stochastic algorithms such as asynchronous and low-precision stochastic gradient descent (SGD) and Markov chain Monte Carlo. My work builds towards using these techniques to construct data analytics and machine learning frameworks, including for deep learning, that are efficient, parallel, and distributed.

I graduated from Stanford University in 2017, where I was advised by Kunle Olukotun and by Chris R‌é.


CS 4780 Machine Learning (Spring 2018)

CS 4787 Principles of Large-Scale Machine Learning (Spring 2019)

CS 6787 Advanced Machine Learning Systems (Fall 2018, Fall 2017)

Office Hours Wednesdays 2:00-3:00 PM in Gates 450.


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