Jing Yu

I am a PhD candidate in the department of Computing and Mathematical Sciences (CMS) at Caltech , advised by John Doyle and Adam Wierman.

I am broadly interested in the interplay between control and learning theory, with a focus on distributed algorithms for large-scale cyber-physical systems. 

My work has been supported in part by the Amazon/Caltech AI4Science Fellowship. Prior to Caltech, I received a B.S. in Mechanical Engineering from Georgia Tech. I previously interned at GE Research Center, Bosch Rexroth, and STERIS.

Email: first name (at) caltech (dot) edu

[Google Scholar] [Github] [Linkedin


March 30, 2023

Jan 27, 2023

Sep 14, 2022

Aug 03, 2022

Jul 15, 2022

Jul 02, 2022

May 02, 2022

Apr 08, 2022

Oct 18, 2021

I have been selected as an Amazon/Caltech AI4Science Fellow of the 2022-2023 class! The AI4Science Fellows program is a result of a partnership between Caltech and Amazon around machine learning and artificial intelligence. The program recognizes graduate students and postdoctoral scholars that have had a remarkable impact in these areas, and in their application to fields beyond computer science

Talk at the ControlX meeting hosted by Prof. Mehran Mesbahi at University of Washington. 

I presented a poster on our recent work on online control of unknown adversarial systems at the Data-driven Decision Process (D3P) program at the Simons Institute.

I'm co-organizing a workshop on System Level Synthesis (SLS) for the Conference on Decision and Control (CDC'22). 

Our paper On Infinite-horizon System Level Synthesis was accepted to the Conference on Decision and Control (CDC'22).

Our paper on robust online voltage control was selected as the finalist for the Best Paper Award of e-Energy’22. Check out the presentation by Chris Yeh.

Talk at Prof. Jason Marden's group at UC San Diego. 
I passed my candidacy!


  • Online Stabilization of Unknown Linear Time-Varying Systems [arXiv
J. Yu, V. Gupta, A. Wierman.In Submission 2023. 
  • Online Adversarial Stabilization of Unknown Networked Systems [arXiv
J. Yu, D. Ho, A. Wierman.ACM SIGMETRICS 2023. 
  • Robust online voltage control with an unknown grid topology [arXiv]
C. Yeh, J. Yu, Y. Shi, A. Wierman.ACM e-Energy 2022. Best paper award finalist. 
  • On Infinite-horizon System Level Synthesis 
O. Kjellqvist*, J. Yu*Conference on Decision and Control (CDC) 2022.
  • Robust Reinforcement Learning: A Constrained Game-theoretic Approach [paper]
J. Yu, C. Gehring, F. Schäfer, A. Anandkumar.Learning for Dynamics and Control Conference (L4DC) 2021.
  • Localized and Distributed H2 State Feedback Control [arXiv]
J. Yu, Y. Wang, J. Anderson.American Control Conference (ACC) 2021
  • Achieving performance and safety in large scale systems with saturation using a nonlinear system level synthesis approach [arXiv]
J. Yu*, D. Ho*.American Control Conference (ACC) 2020

* Equal Contribution


I was a teaching assistant (TA) / co-instructor of the following courses at Caltech (catalog linked):

Outreach and Volunteering 

  • (2018-2020) Muir High School, Pasadena, CA: I tutored high school students in Math and Science as part of an outreach initiative of the Caltech Y Rise Program.
  • (2017-2018) I helped run outreach programs for the CMS department at Caltech, including the Pasadena Science and Art Night, Tech Savvy Science Day for Girls at the Pasadena City College, and facilitate talks organized by Caltech Center for Diversity.
  • (2013-2016) Atlanta, Georgia: I was a volunteer Peer-led Undergraduate Study (PLUS) Leader for Physics I,II and Calculus I, II, III, where I worked with faculties to develop innovative and interactive weekly review sessions to help students better understand challenging course materials.
  • (2014-2016) Atlanta, Georgia: I was a volunteer instructor for the Georgia Tech Invention Studio, committing at least 3 hours per week teaching students how to use the fabrication machines for their engineering projects. I also host outreach workshops for local high schools to engage underrepresented groups in STEM.