Chris De Sa

— Gates Hall, Room 450

I am an Assistant Professor in the Computer Science department at Cornell University. 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). 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.

Teaching

CS 6787 Advanced Machine Learning Systems (Fall 2017)

Office Hours Wednesdays 2-3 PM in Gates 450.

Publications