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.
- Online Stabilization of Unknown Linear Time-Varying Systems [arXiv]
- Online Adversarial Stabilization of Unknown Networked Systems [arXiv]
- Robust online voltage control with an unknown grid topology [arXiv]
- On Infinite-horizon System Level Synthesis
- Robust Reinforcement Learning: A Constrained Game-theoretic Approach [paper]
- Localized and Distributed H2 State Feedback Control [arXiv]
- Achieving performance and safety in large scale systems with saturation using a nonlinear system level synthesis approach [arXiv]
* Equal Contribution
I was a teaching assistant (TA) / co-instructor of the following courses at Caltech (catalog linked):
- Co-instructor: (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 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.