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About Me

I am currently the CTO of Together, building a cloud tailored for artificial intelligence, and the incoming Neubauer Associate Professor of Data Science at the Department of Computer Science of the University of Chicago. Before that I was an Associate Professor at ETH Zurich. I am also currenlty a PhD mentor at INSAIT. I am interested in the fundamental tension between data, model, computation and infrastructure and the goal of my research is to democratize machine learning for wants to use them to make our world a better place.

I finished my PhD at the University of Wisconsin-Madison and spent another year as a postdoctoral researcher at Stanford, both advised by Chris Ré. I did my undergraduate study at Peking University, advised by Bin Cui.

We believe in a system approach in tackling emerging problems that we are facing. Our current research focues on building next-generation machine learning platforms and systems that are data-centric, human-centric, and declaratively scalable.

[Email: cez@uchicago.edu] [Google Scholar] [Twitter]

(Note that My ETH Zurich email doesn’t work anymore so I won’t be able to receive emails sent to ce.zhang@inf.ethz.ch and there seem to be no notice bounching back to the sender; Luckily all other emails still work, including those from Stanford and Wisconsin days)

Check out a summary of our research here.

Another exciting initiative that I am lucky to be part of as the co-Editors-in-Chief is a new journal DMLR, a new member of the JMLR family focusing on data-centric machine learning research. Stay tuned!

As a research group, one of our most important duties is to nurture the next generation of leaders, which arguably gives us the most significant long-lasting impact to the society. Over the years, students graduated from our groups have became professors in great universities and researchers and engineers in leading industrial companies. See a list and their achievements here.

We are super lucky to have been involved in several community building efforts, from machine learning systems, data management for ML, to Data-centric AI. Here are a few recent positioning papers on various topics (joint work with many fellow researchers):

We are always looking for top candidates for PhDs and Postdocs with background in systems or theory on data management, mathematical optimization, and machine learning. Feel free to reach out!

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