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 theory and machine learning, with a focus on online decision making and distributed algorithms for large-scale energy systems.

My work has been supported in part by the Amazon 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

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News

Sep, 2023

May, 2023

Mar, 2023

Jan, 2023

Sep, 2022

Aug, 2022

Jul, 2022

May, 2022

Apr, 2022

Oct, 2021

Invited poster presentation at the Young Researcher Workshop hosted at Cornell University

Invited student talk at the Online Optimization Methods for Data-driven Feedback Control workshop at ACC 2023.

I was named an Amazon AI4Science Fellow of the 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 Santa Babara.

Talk at the 39th Southern California Control Workshop.

I passed my candidacy!

Publications

* Equal Contribution

Learning the Uncertainty Sets for Control Dynamics via Set Membership: A Non-Asymptotic Analysis [arxiv]

Y. Li*, J. Yu*, L. Conger, A. Wierman.In Submission 2023.

Online Learning for Robust Voltage Control under Uncertain Grid Topology [arXiv]

C. Yeh, J. Yu, Y. Shi, A. Wierman.In Submission 2023.

Online Stabilization of Unknown Linear Time-Varying Systems [arXiv] [code]

J. Yu, V. Gupta, A. Wierman.Accepted to Conference on Decision and Control (CDC) 2023.

Online Adversarial Stabilization of Unknown Networked Systems [arXiv] [code]

J. Yu, D. Ho, A. Wierman.ACM SIGMETRICS 2023.

Robust Online Voltage Control with an Unknown Grid Topology [arXiv] [code]

C. Yeh, J. Yu, Y. Shi, A. Wierman.ACM e-Energy 2022. Best paper award finalist.

On Infinite-horizon System Level Synthesis [arxiv] [code]

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] [code]

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.

Teaching

I was a teaching assistant (TA) of the following courses at Caltech:

TA: (Spring 2023) CDS 231 Robust Control Theory
TA: (Winter 2021) CDS 270 Robust Control and Learning
TA: (Spring 2020) CDS 141: Network Control Systems
TA: (Fall 2019) ACM/EE/IDS 116 Introduction to Probability Models
TA: (Fall 2018) CS/EE 143 Communication Networks

Outreach and Mentoring

(2023) Sustainable Energy Activity Lab (SEAL): I am a mentor for high school clubs where I work with students on a year-long sustainable energy project related to microbial fuel cells. We meet weekly for labs, lectures, and discussions.

(2023) FUTURE Ignited: I am a peer advisor and accountability partner to help undergraduate students from diverse backgrounds to apply to graduate school, where I meet with students weekly to discuss progress and advise on graduate school applications from Sep - Dec.

(2023) First-year Success Research Institute (FSRI): I was a research mentor for incoming historically excluded and/or marginalized first-year undergraduate students where I worked with 3 students on a research project.

(2021-2023) Caltech: I mentored the following undergraduate students (U) and junior graduate students (G) during my time at Caltech: Agnim Agarwal (U, 2023) ; Lauren Conger (G, 2021-2022) ; Tinashe Handina (G, 2022-2023) ; Eric Ma (U, 2023); Patrick Martinez (U, 2023).

(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) Caltech: 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) Georgia Tech: I was a 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) Georgia Tech: 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.