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SUMMARY:Machine Learning for Power Systems: Is it time to trust it?
DTSTART:20230512T110000
DTEND:20230512T120000
DTSTAMP:20260407T111447Z
UID:0e16d58b491c995ad9a1b4265240b2e41c08d079bffde61806f76bda
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof. Spyros Chatzivasileiadis (DTU)\nAbstract: \nIn this tal
 k\, we introduce methods that remove the barrier for applying neural netwo
 rks in real-life power systems\, and unlock a series of new applications. 
 More specifically\, we introduce a framework that addresses five key chall
 enges (dataset generation\, data pre-processing\, neural network training\
 , verification\, and embedding in other tools) associated with building tr
 ustworthy ML models which learn from physics-based simulation data. We int
 roduce methods for (i) physics-informed neural networks in power systems\,
   (ii) verifying neural network behavior in power systems and (iii) obtai
 n provable worst-case guarantees of their performance. Up to this moment\,
  neural networks have been applied in power systems as a black-box\; this 
 has presented a major barrier for their adoption in practice. Using a rigo
 rous framework based on mixed integer linear programming\, our methods can
  obtain provable worst-case guarantees of the neural network performance. 
 Such methods have the potential to build the missing trust of power system
  operators on neural networks\, and unlock a series of new applications in
  power systems and other safety-critical systems.\n \nShort Bio: \nSpyro
 s Chatzivasileiadis is the Head of Section for Power Systems and an Associ
 ate Professor at the Technical University of Denmark (DTU). Before that he
  was a postdoctoral researcher at MIT and Lawrence Berkeley National Lab\,
  USA. Spyros holds a PhD from ETH Zurich\, Switzerland (2013) and a Diplom
 a in Electrical and Computer Engineering from the National Technical Unive
 rsity of Athens (NTUA)\, Greece (2007). He is currently working on trustwo
 rthy machine learning for power systems\, quantum computing\, and on power
  system optimization\, dynamics\, and control of AC and HVDC grids. Spyros
  has received the Best Teacher of the Semester Award at DTU Electrical Eng
 ineering\, and is the recipient of an ERC Starting Grant in 2020.
LOCATION:ME C2 405 https://plan.epfl.ch/?room==ME%20C2%20405
STATUS:CONFIRMED
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