Update: In January 2025 I joined the Department of Electrical and Computer Engineering at Villanova University as a Visiting Teaching Assistant Professor. Please feel free to get in touch at kgatsis@villanova.edu.
My research interests are in networked autonomous systems, combining tools from control, optimization, machine learning, and communications. You will find more information on my research page and my publications page.
Previously from January 2024 to January 2025 I was a Lecturer (Assistant Professor) at the Cyber Physical Systems Research Group, School of Electronics and Computer Science, University of Southampton and from December 2019 to December 2023 I was a Lecturer (Assistant Professor) at the Department of Engineering Science in the University of Oxford, UK, where I was affiliated with the Control Engineering Group.
I was a Postdoctoral Researcher at the Department of Electrical and Systems Engineering at the University of Pennsylvania, where I also obtained my PhD degree (Dec. 2016). I was member of the GRASP lab under the supervision of Professor George J. Pappas. I obtained my undergraduate degree in Electrical and Computer Engineering from the University of Patras, Greece.
Google Scholar: link --- Curriculum vitae: link --- Resume: link
E-mail: kgatsis@villanova.edu, k.gatsis@soton.ac.uk
Office: Drosdick 376B
News:
• March 2025: One journal paper on safe and stable reinforcement learning accepted at Neurocomputing (lead auther Liqun Zhao) and one conference paper on safe Neural ODEs accepted at L4DC 2025 (lead author Keyan Miao).
• January 2025: I joined Villanova University, USA!
• September 2024: Postdoc position open in my group (no longer accepting applicants). Details: here .
• July 2024: Exciting new papers to appear at ICML 2024 and UAI 2024 (spotlight)! By leading authors Keyan Miao and Ondrej Bajgar, on the topics of computationally efficient Neural ODEs, and computationally efficient Bayesian Inverse Reinforcement Learning, respectively.
• July 2024: Co-organizing L4DC 2024 taking place in Oxford, UK!
• June 2024: I presented a seminar at the University of Stuttgart on the intersection of Neural Netwwork Systems and Dynamical Systems.
• December 2023: Three papers to be presented at CDC 2023 in Singapore. Leading authors are students: Andre Bertolace, Oliver Gates, Liqun Zhao.
• May 2023: Received the 2023 IEEE Communications Society & Information Theory Society Joint Paper Award for the paper 'Age of Information in Random Access Channels' co-authored with collaborators at the Univ. of Pennsylvania - (IEEE announcement).
• March 2023: Keyan's paper on Neural ODEs accepted at the L4DC conference.
• February 2023: Seminar (in person), Control Group, University of Cambridge
• September 2021: Co-organizing a Workshop on Distributed Learning and Multi-agent Learning during the 60th IEEE Conference on Decision and Control in December (workshop page).
• May 2021: Seminar (remote), Information Processing and Communications Lab, Imperial College London
• April 2021: Seminar (remote), CRAN, Université de Lorraine (Nancy, France)
• April 2021: A large number of my publications have been included in the Best Readings in Communications in Wireless Networked Control (link).
• April 2021: Starting a new AIMS CDT student mini-project in the area of inverse reinforcement learning and safe learning (co-advised with Prof. Alessandro Abate, CS) .
• March 2021: New paper on Communication-Efficient Distributed Learning accepted at Learning for Dynamics & Control (L4DC) Conference (preprint).
• January 2021: New paper on Learning over Networks accepted at American Control Conference (preprint).
• December 2020: Talk (remote) at Oxford-Man Institute Machine Learning Workshop.
• December 2020: Journal paper on 'Statistical Learning for Analysis of Networked Control Systems' accepted at Automatica (link).
• December 2020: Seminar (remote) at University of Manchester, Control Systems Seminar.
• November 2020: Seminar (remote) at Toshiba Research Europe, UK.
• October 2020: Seminar (remote) at University of Sheffield, Department of Automatic Control and Systems Engineering.