PSCC 2024 Tutorial

Trustworthy AI for Power Systems


What are your takeaways?

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Tutorial Slides

09.00-09.20 Introduction
Spyros Chatzivasileiadis, DTU
[ slides ]
09.20-10.20 Trustworthy AI for Optimization
Pascal van Hentenryck, GeorgiaTech
[ slides ]
10.30-11.30 Trustworthy AI and Machine Learning Verification for Power Systems
Sam Chevalier, Univ. of Vermont
[ slides ]
11.45-12.45 Physics-Informed Neural Networks for Power System Dynamics
Spyros Chatzivasileiadis, DTU
[ slides ]
[ code ]
14.00-15.00 Safe Reinforcement Learning for Power Systems
Baosen Zhang, Univ. of Washington
[ slides ]
15.15-16.15 Implicit Layers: A Toolkit for AI in Power Systems
Priya Donti, MIT
[ slides ]
16.15-16.30 Conclusion
Spyros Chatzivasileiadis, DTU
[ slides ]

Short Bios

Baosen Zhang is the Keith and Nancy Rattie Endowed Career Development Professor at the University of Washington, Seattle, USA. He received his B.A.Sc. degree in engineering science from the University of Toronto, Toronto, ON, Canada, in 2008 and his Ph.D. from the Department of Electrical Engineering and Computer Science at the University of California at Berkeley, in 2013. Before joining UW, he was postdoctoral scholar at Stanford University, jointly hosted by departments of Civil and Environmental Engineering and Management & Science Engineering. His interest is in the area of power systems and cyberphysical systems, particularly in the fundamentals of physical resource allocations, economics, and controlling systems with humans in the loop. [ More information? Click here ]

Pascal Van Hentenryck is the A. Russell Chandler III Chair and Professor at Georgia Tech., the director of the NSF Artificial Intelligence Institute for Advances in Optimization (AI4OPT), and the director of Tech-AI, the AI hub at Georgia Tech. Van Hentenryck’s research focuses on artificial intelligence for engineering and science and, in particular, energy, supply chains and manufacturing, transportation, and health care. Earlier in his career, Van Hentenryck designed and implemented several widely used optimization systems, including the constraint programming language CHIP (the foundation of modern constraint-programming systems) and the modeling language OPL (now an IBM product). [ More information? Click here ]

Priya Donti is an Assistant Professor and the Silverman (1968) Family Career Development Professor at MIT EECS and LIDS. She is also a co-founder and Chair of Climate Change AI, a global nonprofit initiative to catalyze impactful work at the intersection of climate change and machine learning. Priya is recipient of the MIT Technology Review’s 2021 “35 Innovators Under 35” award and the 2022 ACM SIGEnergy Doctoral Dissertation Award. [ More information? Click here ]

Sam Chevalier is an assistant professor of electrical engineering at the University of Vermont. Until fall of 2023, he was a Marie Curie Postdoctoral Research Fellow at the Technical University of Denmark (DTU), where his research focused on developing data driven optimization and control strategies for low carbon electrical power sytems. Prior to DTU, Sam received his PhD (‘21) from the mechanical engineering department at MIT.[ More information? Click here ]

Spyros Chatzivasileiadis is Professor and the Head of Section for Power Systems at the Technical University of Denmark (DTU). Before that he was a postdoctoral researcher at the Massachusetts Institute of Technology (MIT), USA and at Lawrence Berkeley National Laboratory, USA. Spyros holds a PhD from ETH Zurich, Switzerland (2013) and a Diploma in Electrical and Computer Engineering from the National Technical University of Athens (NTUA), Greece (2007). Spyros has received the Best Teacher of the Semester Award at DTU Electrical Engineering, and is the recipient of an ERC Starting Grant in 2020. [ More information? Click here ]