Richard Y. Zhang

Assistant Professor
Department of Electrical and Computer Engineering
Coordinated Science Laboratory
University of Illinois at Urbana-Champaign
Contact - CV - Google Scholar - dblp - github - LinkedIn

My research is in optimization and machine learning, and their applications in power and energy systems. Specifically: Nonconvex optimization (low-rank matrix factorization); Convex optimization (semidefinite programming); Large-scale linear systems (Krylov subspaces); Exploiting domain-specific structure (quadratic nonconvexity, monotonicity) for provable guarantees in optimal power flow and state estimation.

I received my PhD in Electrical Engineering and Computer Science from MIT in 2017, and was a postdoc at UC Berkeley from 2017-2019.

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How Much Restricted Isometry is Needed In Nonconvex Matrix Recovery?
NeurIPS 2018 Spotlight (5 min)
[paper] [slides] [poster]

Recommendation engines (think YouTube and Netflix) frequently make use of low-rank matrix models. In practice, these are easily trained using SGD, apparently without getting stuck at a local minimum. In this paper, we show that we've just been getting lucky—SGD is readily defeated by bad models that "look easy" to train.

Large-Scale Sparse Inverse Covariance Estimation via Thresholding and Max-Det Matrix Completion
ICML 2018 (10 min)
[paper] [slides] [poster]

Graphical lasso is able to estimate a graphical model on \(n\) vertices from \(O(n\log(n))\) data points. We describe an algorithm that solves graphical lasso in linear \(O(n)\) time and memory, thereby allowing extremely large graphical models to be learned on laptop computers.

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2020 2019 2018 2017 2016 2015 2014 2011-2013


I am a New Zealander of Chinese descent from Christchurch, New Zealand. My last name 张/張 (Zhāng) is pronounced "Dj-uh-ng", but I usually go by the anglicized "Z-ang". 我会说普通话。J'ai étudié le français à l'école. I was a guitarist in the post-rock band Mammoth (see Two Weeks and Life without Light).

People often confuse me with the computer vision expert formerly at Berkeley, or the MIT grad student who co-founded FAIL!, or the power electronics expert at GE, which is why I usually give my middle initial when stating my name. But even then, my name still collides with the researcher at Pfizer and the optometrist in Lexington, MA.

© 2018 Richard Y. Zhang.