Yang Zheng
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Assistant Professor Office: #3308 Franklin Antonio Hall ORCID · Google Scholar
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Office hours
Tuesday, 5:00 pm - 6:30 pm
Feel free to email me to schedule office hours if needed.
Prospective students: I am actively seeking highly motivated students with a strong background in mathematics, theory, and computation to join my research group. If you have a strong interest in optimization and control, I encourage you to apply. Application instructions can be found here.
Prospective students and visiting interns are welcome to get in touch. Feel free to drop me an email (zhengy@ucsd.edu) with your CV, transcripts, and a brief overview of your interest in joining my group.
Check here: Join us!
Brief Biography
I am an Assistant Professor in Electrical and Computer Engineering at the University of California San Diego. I am affiliated with the CSE department and Contextual Robotics Institute.
From March 2019 to August 2020, I was a postdoctoral scholar in SEAS and CGBC at Harvard University, working with Prof. Na Li and Prof. Ali Malkawi. I was a research associate in the Verification of Autonomous Systems group at Imperial College London in 2021. I received the B.S. and M.E. degrees in the Department of Automotive Engineering from Tsinghua University, Beijing, China, in 2013 and 2015, respectively. In Feb. 2019, I received the DPhil (Ph.D.) degree in Control from the University of Oxford for my work on Chordal Sparsity in Control and Optimization of Large-scale Systems under the supervision of Prof. Antonis Papachristodoulou.
I am broadly interested in learning, optimization, and control of network systems, and their applications to autonomous vehicles and traffic systems. My current research interests include:
Convex and non-convex optimization for control; see e.g., this project.
Principled data-driven and learning-based control; see e.g., this project
Structures and algorithms for large-scale semidefinite optimization; see e.g.,this project.
Applications in mixed traffic control, and certifiable robustness of machine learning (e.g., deep neural networks); see e.g., this project.
Check out some exciting research in the SOC lab at UCSD.
Updates
03/2024: Our SOC Lab has two papers accepted for presentation at the 2024 L4DC!
03/2024: Presented an invited talk on Error bounds, PL, and Quadratic Growth for Weakly Convex Functions, and Linear Convergences of Proximal Point Methods at the 2024 INFORMS IOS conference.
02/2024: Presented a talk on Benign Nonconvex Landscapes in Optimal and Robust Control at the 2024 ITA workshop.
01/2024: Received the NSF CAREER Award! The project title is CAREER: Interplay between Convex and Nonconvex Optimization for Control.
01/2024: Received the 2024 UCSD Jacobs School of Engineering Early Career Faculty Development Award (together with Prof. Jorge Cortes).
01/2024: On the Scalability and Memory Efficiency of Semidefinite Programs for Lipschitz Constant Estimation of Neural Networks was accepted for publication at ICLR 2024.
01/2024: A new preprint: Decentralized Robust Data-driven Predictive Control for Smoothing Mixed Traffic Flow; with Xu Shang and Jiawei Wang.
01/2024: Our paper: Smoothing Mixed Traffic with Robust Data-driven Predictive Control for Connected and Autonomous Vehicles was accepted for publication in ACC 2024. Congratulations to Xu Shang and Jiawei Wang!
12/2023: Three new preprints from our SOC group:
Benign Nonconvex Landscapes in Optimal and Robust Control, Part I: Global Optimality; with Chih-fan Pai (PhD student) and Yujie Tang (Assistant Professor at Peking University)
Error bounds, PL condition, and quadratic growth for weakly convex functions, and linear convergences of proximal point methods; with Feng-Yi Liao (PhD student) and Lijun Ding (University of Wisconsin - Madison)
Convex Approximations for a Bi-level Formulation of Data-Enabled Predictive Control. This work is led by Xu Shang (PhD student).
12/2023: Visited Prof. Lin ZHAO's group at the National University of Singapore and presented a seminar on Nonconvex Optimization for Linear Quadratic Gaussian (LQG) Control.
12/2023: Attended the IEEE CDC 2023 in Singapore;
12/2023: Congratulations to Feng-Yi Liao! He won the Poster Presentation Award in Operations Research and Optimization Methodologies at the 2023 INFORMS Annual Conference for his stellar poster on “Spectral Bundle Methods for Primal and Dual Semidefinite Programs” (see an arXiv prepint here). Well done on this well-deserved recognition!
10/2023: Received the 2023 Best Graduate Teacher Award from the ECE department.