Optimization · Machine learning · Power systems
Richard Y. Zhang
Associate Professor
Department of Electrical and Computer Engineering
Coordinated Science Laboratory
University of Illinois Urbana-Champaign
Department of Electrical and Computer Engineering
Coordinated Science Laboratory
University of Illinois Urbana-Champaign
My research focuses on low-rank optimization, both as a theoretical lens for understanding how learning algorithms uncover latent signals from complex data, and also as a computational framework for designing large-scale algorithms by operating on these signals.
I received my PhD from MIT EECS and was a postdoc at Berkeley IEOR. I received an NSF CAREER Award in 2021 and have served as an Area Chair at NeurIPS, ICML, and ICLR. I am advising PhD students Hong-Ming Chiu, Iven Guzel, Jing-Teng (Jeter) Hwang, and Haoruo Zhang; Masters student Nalin Tiwary; Undergraduate Kevin Wu. Alumni from my group include Gavin (Jialun) Zhang (PhD '24 → Meta), and June Hou (MS '25 → UIUC PhD).
In Fall 2026, I am teaching ECE490: Introduction to Optimization.
Publications
- Sharp Restricted Isometry Thresholds for Global Minima of Rank-Restricted Matrix LASSO
Richard Y. Zhang — Preprint, Aug 2026. [arxiv] - Sharp Recovery and Landscape Guarantees for the Nonconvex Matrix LASSO
Andrew D. McRae, Richard Y. Zhang — Preprint, Apr 2026. [arxiv] - Sharp Global Guarantees for Nonconvex Low-Rank Recovery in the Noisy Overparameterized Regime
Richard Y. Zhang — SIAM Journal on Optimization, 35.3 (2025): pp. 2128-2154. [doi] [arxiv] - Improved Global Guarantees for the Nonconvex Burer--Monteiro Factorization via Rank Overparameterization
Richard Y. Zhang — Mathematical Programming, 213 (2025): pp. 1009-1038. [doi] [arxiv] - SDP-CROWN: Efficient Bound Propagation for Neural Network Verification with Tightness of Semidefinite Programming
Selected for Spotlight (one of 313/12107 submissions)
Hong-Ming Chiu, Hao Chen, Huan Zhang, Richard Y. Zhang — ICML 2025. [arxiv] - Spectral Initialization and Certification for Power System Angle Estimation
Iven Guzel, Andrew D. McRae, Richard Y. Zhang — Preprint, Jul 2026. [arxiv]
Preprints
- Sharp Restricted Isometry Thresholds for Global Minima of Rank-Restricted Matrix LASSO
Richard Y. Zhang — Preprint, Aug 2026. [arxiv] - Sharp Recovery and Landscape Guarantees for the Nonconvex Matrix LASSO
Andrew D. McRae, Richard Y. Zhang — Preprint, Apr 2026. [arxiv] - Well-conditioned Primal-Dual Interior-point Method for Low-rank Semidefinite Programming
Hong-Ming Chiu, Richard Y. Zhang — Preprint, Jul 2024. [arxiv] - Spectral Initialization and Certification for Power System Angle Estimation
Iven Guzel, Andrew D. McRae, Richard Y. Zhang — Preprint, Jul 2026. [arxiv]
- Nonnegative Low-rank Matrix Recovery Can Have Spurious Local Minima
Richard Y. Zhang — Optimization Letters, 20 (2026): pp. 683-704. [doi] [arxiv] - Scalable Second-order Riemannian Optimization for K-means Clustering
Peng Xu*, Chun Ying Hou*, Xiaohui Chen, Richard Y. Zhang — ICLR 2026. [arxiv]
- Sharp Global Guarantees for Nonconvex Low-Rank Recovery in the Noisy Overparameterized Regime
Richard Y. Zhang — SIAM Journal on Optimization, 35.3 (2025): pp. 2128-2154. [doi] [arxiv] - Improved Global Guarantees for the Nonconvex Burer--Monteiro Factorization via Rank Overparameterization
Richard Y. Zhang — Mathematical Programming, 213 (2025): pp. 1009-1038. [doi] [arxiv] - Complexity of Sparse Semidefinite Programs with Small Treewidth
Richard Y. Zhang — Mathematical Programming, 213 (2025): pp. 201-237. [doi] [arxiv] - Simple Alternating Minimization Provably Solves Complete Dictionary Learning
Geyu Liang, Gavin Zhang, Salar Fattahi, Richard Y. Zhang — SIAM Journal on Mathematics of Data Science, 7.3 (2025): pp. 855-883. [doi] [arxiv] - Power System State Estimation by Phase Synchronization and Eigenvectors
Iven Guzel, Richard Y. Zhang — IEEE Transactions on Control of Network Systems, 12.3 (2025): pp. 2207-2218. [doi] [arxiv] - SDP-CROWN: Efficient Bound Propagation for Neural Network Verification with Tightness of Semidefinite Programming
Selected for Spotlight (one of 313/12107 submissions)
Hong-Ming Chiu, Hao Chen, Huan Zhang, Richard Y. Zhang — ICML 2025. [arxiv]
- Statistically Optimal K-means Clustering via Nonnegative Low-rank Semidefinite Programming
Selected for Oral (one of 85/7262 submissions)
Yubo Zhuang, Xiaohui Chen, Yun Yang, Richard Y. Zhang — ICLR 2024. [arxiv] - Fast and Minimax Optimal Estimation of Low-Rank Matrices via Non-Convex Gradient Descent
Gavin Zhang, Hong-Ming Chiu, Richard Y. Zhang — AISTATS 2024. [arxiv]
- Preconditioned Gradient Descent for Overparameterized Nonconvex Burer-Monteiro Factorization with Global Optimality Certification
Gavin Zhang, Salar Fattahi, Richard Y. Zhang — Journal of Machine Learning Research, 24.163 (2023): pp. 1-55. [permalink] [arxiv] - Tight Certification of Adversarially Trained Neural Networks via Nonconvex Low-Rank Semidefinite Relaxations
Hong-Ming Chiu, Richard Y. Zhang — ICML 2023. [arxiv]
- Accelerating SGD for Highly Ill-Conditioned Huge-Scale Online Matrix Completion
Gavin Zhang, Hong-Ming Chiu, Richard Y. Zhang — NeurIPS 2022. [arxiv]
- Sparse Semidefinite Programs with Guaranteed Near-Linear Time Complexity via Dualized Clique Tree Conversion
Richard Y. Zhang, Javad Lavaei — Mathematical Programming, 188.1 (2021): pp. 351-393. [doi] [arxiv] - Uniqueness of Power Flow Solutions Using Monotonicity and Network Topology
SangWoo Park, Richard Y. Zhang, Javad Lavaei, Ross Baldick — IEEE Transactions on Control of Network Systems, 8.1 (2021): pp. 319-330. [doi] - Preconditioned Gradient Descent for Over-Parameterized Nonconvex Matrix Factorization
Gavin Zhang, Salar Fattahi, Richard Y. Zhang — NeurIPS 2021. [permalink] [arxiv]
- Large-Scale Traffic Signal Offset Optimization
Yi Ouyang, Richard Y. Zhang, Javad Lavaei, Pravin Varaiya — IEEE Transactions on Control of Network Systems, 7.3 (2020): pp. 1176-1187. [arxiv] [pdf] - How many samples is a good initial point worth in Low-rank Matrix Recovery?
Selected for Spotlight (one of 280/9454 submissions)
Gavin Zhang, Richard Y. Zhang — NeurIPS 2020. [arxiv] - On the Tightness of Semidefinite Relaxations for Certifying Robustness to Adversarial Examples
Richard Y. Zhang — NeurIPS 2020. [arxiv]
- Sharp Restricted Isometry Bounds for the Inexistence of Spurious Local Minima in Nonconvex Matrix Recovery
Richard Y. Zhang, Somayeh Sojoudi, Javad Lavaei — Journal of Machine Learning Research, 20.114 (2019): pp. 1-34. [permalink] [arxiv] - Spurious Local Minima in Power System State Estimation
Special Issue on Analysis, Control and Optimization of Energy System Networks
Richard Y. Zhang, Javad Lavaei, Ross Baldick — IEEE Transactions on Control of Network Systems, 6.3 (2019): pp. 1086-1096. [doi] [pdf] - Conic optimization for control, energy systems, and machine learning: Applications and algorithms
Richard Y. Zhang, Cedric Josz, Somayeh Sojoudi — Annual Reviews in Control, 47 (2019): pp. 323-340. [doi] [arxiv] - Monotonicity Between Phase Angles and Power Flow and Its Implications for the Uniqueness of Solutions
SangWoo Park, Richard Y. Zhang, Javad Lavaei, Ross Baldick — HICSS 52.
- GMRES-Accelerated ADMM for Quadratic Objectives
Richard Y. Zhang, Jacob K White — SIAM Journal on Optimization, 28.4 (2018): pp. 3025-3056. [doi] [arxiv] - How Much Restricted Isometry is Needed In Nonconvex Matrix Recovery?
Selected for Spotlight (one of 168/4856 submissions)
Richard Y. Zhang, Cedric Josz, Somayeh Sojoudi, Javad Lavaei — NeurIPS 2018. [arxiv] - Large-Scale Sparse Inverse Covariance Estimation via Thresholding and Max-Det Matrix Completion
Richard Y. Zhang, Salar Fattahi, Somayeh Sojoudi — ICML 2018. [permalink] [arxiv] [slides] - A theory on the absence of spurious solutions for nonconvex and nonsmooth optimization
Cedric Josz, Yi Ouyang, Richard Y. Zhang, Javad Lavaei, Somayeh Sojoudi — NeurIPS 2018. [arxiv] - Sparse Semidefinite Programs with Near-Linear Time Complexity
Richard Y. Zhang, Javad Lavaei — CDC 2018. [arxiv] - Efficient Algorithm for Large-and-Sparse LMI Feasibility Problems
Richard Y. Zhang, Javad Lavaei — CDC 2018. [pdf] - Conic Approximation with Provable Guarantee for Traffic Signal Offset Optimization
Yi Ouyang, Richard Y. Zhang, Javad Lavaei, Pravin Varaiya — CDC 2018. [pdf] - Sparse Inverse Covariance Estimation for Chordal Structures
Salar Fattahi, Richard Y. Zhang, Somayeh Sojoudi — ECC 2018. [arxiv] - Conic Optimization Theory: Convexification Techniques and Numerical Algorithms
Richard Y. Zhang*, Cedric Josz*, Somayeh Sojoudi — ACC 2018. [doi] [arxiv] - Spurious Critical Points in Power System State Estimation
Richard Y. Zhang, Javad Lavaei, Ross Baldick — HICSS 51. [doi] [pdf] - Linear Time Algorithms for Sparse Inverse Covariance Estimation
Salar Fattahi, Richard Y. Zhang, Somayeh Sojoudi — IEEE Access, 7 (2018): pp. 12658-12672. [doi]
- Modified Interior-Point Method for Large-and-Sparse Low-Rank Semidefinite Programs
Richard Y. Zhang, Javad Lavaei — CDC 2017. [doi] [arxiv]
- Robust Stability Analysis for Large-Scale Power Systems
Richard Y. Zhang — Ph.D. thesis, MIT Department of Electrical Engineering & Computer Science, 2016. [permalink] [pdf] - Certifying Microgrid Stability Under Large-Signal Intermittency
Richard Y. Zhang, Jorge Elizondo, James L. Kirtley, Jacob K. White — COMPEL 2016. [doi] - Small-Signal Stability Verification Issues for Transmission Systems with Distributed Renewables
Richard Y. Zhang, Jorge Elizondo, James L. Kirtley, Jacob K. White — PESGM 2016. [doi] [pdf] - Inertial and Frequency Response from Microgrids with Induction Motors
Jorge Elizondo, Richard Y. Zhang, Po-Hsu Huang, Jacob K. White, James L. Kirtley — COMPEL 2016. [doi] - Parameter Insensitivity in ADMM-Preconditioned Solution of Saddle-Point Problems
Richard Y. Zhang, Jacob K. White — Tech report, Feb 2016. [arxiv]
- Toeplitz-Plus-Hankel Matrix Recovery for Green's Function Computations on General Substrates
Richard Y. Zhang, Jacob K. White — Proceedings of the IEEE, 103.11 (2015): pp. 1970-1984. [doi] [pdf] - Design of Resonance Damping via Control Synthesis
Richard Y. Zhang, Al-Thaddeus Avestruz, Jacob K. White, Steven B. Leeb — COMPEL 2015. [doi] [pdf] - Robust Small Signal Stability for Microgrids under Uncertainty
Jorge Elizondo, Richard Y. Zhang, Jacob K. White, James L. Kirtley — PEDG 2015. [doi] [pdf] - An energy-based method for the assessment of battery and ultracapacitor in pulse load applications
Outstanding Presentation Award (Poster)
Yiou He, Richard Y. Zhang, John G. Kassakian — APEC 2015. [doi] [pdf]
- Fast simulation of complicated 3D structures above lossy magnetic media
Richard Y. Zhang, Jacob K. White, John G. Kassakian — IEEE Transactions on Magnetics, 50.10 (2014): 7027416. [doi] [pdf] - Analytical model for effects of twisting on litz-wire losses
Charles R. Sullivan, Richard Y. Zhang — COMPEL 2014. [doi] [pdf] - Realistic litz wire characterization using fast numerical simulations
Outstanding Presentation Award (Oral)
Richard Y. Zhang, Jacob K. White, John G. Kassakian, Charles R. Sullivan — APEC 2014. [doi] [pdf] [slides] - Simplified design method for litz wire
Charles R. Sullivan, Richard Y. Zhang — APEC 2014. [doi] [pdf]
- A Generalized Approach to Planar Induction Heating Magnetics
Richard Y. Zhang — S.M. thesis, MIT Department of Electrical Engineering & Computer Science, 2012. [permalink] [pdf] - The Future of the Electric Grid -- An Interdisciplinary MIT study
John G. Kassakian, Richard Schmalensee et al. — Technical report, MIT Energy Initiative, 2011. [permalink]
- A go-cart as an electric vehicle for undergraduate teaching and assessment
Bill Heffernan, Richard Duke, Richard Zhang, Paul Gaynor, Michael Cusdin — AUPEC 2010.
Trivia
My last name 张/張 (Zhāng) is pronounced “Dj-uh-ng”, but I usually go by the anglicized “Z-ang.” People often confuse me with Dr. Richard Zhang, which is why I usually state my middle initial. I am originally from New Zealand. I was in a post-rock band in college.