Jing Yu
I am currently a Grainger College of Engineering Distinguished Postdoctoral Fellow hosted by R. Srikant at the University of Illinois Urbana-Champaign. Previously I was a postdoctoral research fellow at University of Michigan hosted by Necmiye Ozay. I obtained my Ph.D. in Control and Dynamical Systems at Caltech, co-advised by John Doyle and Adam Wierman, where I was awarded the Amazon AI4Science Fellowship and the Amori Doctoral Prize.
In fall 2025, I will join the electrical and computer engineering department at University of Washington as an assistant professor.
Research: The next generation of cyber-physical systems (CPS) is large-scale, safety-critical, and time-varying. My research agenda is to design practical control algorithms that enable CPS that are scalable and robust to uncertainties, with fast adaptation. My approach is to develop system-level frameworks that integrate learning and control in a way that resolves technical challenges arising from realistic scenarios, with a focus on online decision making and distributed algorithms for large-scale sustainable energy systems.
Email: jing5 (at) uw (dot) edu
Postdoctoral Fellow
University of Illinois
Urbana-Champaign
Incoming Assistant Professor
University of Washington
CV | Google Scholar | Github
News
(July 2024) Dissertation defense on my PhD work in Scalable Learning-based Control!
(July 2024) I will attend the AI+Science Summer School hosted by the Data Science Institute at the University of Chicago.
(Jun 2024) I am funded through NSF to be a long program participant at the Architecture of Green Energy Systems at Institute for Mathematical and Statistical Innovation (IMSI) from June 23 - Aug 23, 2024. If you are around Chicago and want to chat about research, let's get in touch!
(Dec 2023) I will present our work on adversarial stabilization of unknown time-varying systems at IEEE CDC 2023.
(Sep 2023) Invited poster presentation at the Young Researcher Workshop hosted at Cornell University.
(May 2023) Invited student talk at the Online Optimization Methods for Data-driven Feedback Control workshop at IEEE ACC 2023.
(Mar 2023) I am 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.
(Jan 2023) Invited talk at the ControlX seminar at University of Washington.
(Sep 2022) Poster presentation on online control of unknown adversarial systems at the Data-driven Decision Process (D3P) program at the Simons Institute.
(Aug 2022) I'm co-organizing a workshop on System Level Synthesis (SLS) for the IEEE CDC 2022.
(Jan 2022) Our paper On Infinite-horizon System Level Synthesis is accepted to IEEE CDC 2022.
(Jul 2022) Our paper on robust online voltage control is selected as the finalist for the Best Paper Award of ACM e-Energy 2022. Check out the presentation by Chris Yeh!
(May 2022) Invited talk at Prof. Jason Marden's group at UC Santa Babara.
(Apr 2022) Talk at the 39th Southern California Control Workshop.
(Oct 2021) I passed my candidacy!