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Research interests
Trustworthy AI
Develop data-driven technology that can be trusted to do the critical work
CPS Security
Protect the critical infrastructure against cyber and physical attacks
Human-centric Technology
Design methods that respect human-centric needs and values
Future Energy Systems
Ensure sustainable and reliable access to power and energy for society
Selected Awards
- Siebel Scholar (class of 2018)
- Best paper award, Building and Environment (2018)
- Best paper runner-up award at MobiQuitous (2016)
- Best paper award at Ubicomm for Mobile Ubiquitous Computing (2015)
News
Jan 2020The paper "Conic Relaxations of Power System Optimization: Theory and Algorithms" to appear in European Journal of Operational Research.
Aug 2019New paper on cybersecurity for power grid "Boundary Defense against Cyber Threat for Power System Operation" (Supplementary material).
Jul 2019Paper to appear in Proc. 58th IEEE Conference on Decision and Control "Towards Robust and Scalable Power System State Estimation".
May 2019New paper on robust graph convolutional network "Power up! Robust Graph Convolutional Network against Evasion Attacks based on Graph Powering".
Feb 2019New paper on power system state estimation "Scalable and robust state estimation from abundant but untrusted data".
Oct 2018New paper on stability certfied reinforcement learning "Stability-certified reinforcement learning: a control-theoretic perspective".
Aug 2018Presentations at the International Conference on Applied Energy: "BISCUIT: Building Intelligent System Customer Investment Tools" (paper | slides) and "Advanced Building Control via Deep Reinforcement Learning" (paper).
Jul 2018Presentation at the 23rd International Symposium on Mathematical Programming, Bordeaux, France: "Vulnerability analysis and robustification of power grid state estimation" (slides).
Jun 2018New paper on power system vulnerability analysis "Power Grid AC-based State Estimation: Vulnerability Analysis Against Cyber Attacks" accepted in IEEE Transactions on Automatic Control.
Mar 2018New paper to guarantee safety of smooth RL in real-world systems like power grids: "Control-theoretic analysis of smoothness for stability-certified reinforcement learning."