Kyriakos G Vamvoudakis
Kyriakos G. Vamvoudakis was born in Athens, Greece. He earned his Diploma in Electronic and Computer Engineering (equivalent to a Master of Science) from the Technical University of Crete, Greece, in 2006, graduating with highest honors. After relocating to the United States, he pursued further studies at The University of Texas at Arlington under the guidance of Frank L. Lewis, obtaining his M.S. and Ph.D. in Electrical Engineering in 2008 and 2011, respectively.
From May 2011 to January 2012, he served as an Adjunct Professor and Faculty Research Associate at the University of Texas at Arlington and the Automation and Robotics Research Institute. Between 2012 and 2016, he was a project research scientist at the Center for Control, Dynamical Systems, and Computation at the University of California, Santa Barbara. He then joined the Kevin T. Crofton Department of Aerospace and Ocean Engineering at Virginia Tech as an assistant professor, a position he held until 2018.
He currently serves as the Dutton-Ducoffe Endowed Professor at The Daniel Guggenheim School of Aerospace Engineering at Georgia Tech. He holds a secondary appointment in the School of Electrical and Computer Engineering. His expertise is in reinforcement learning, control theory, game theory, cyber-physical security, bounded rationality, and safe/assured autonomy. He directs the Intelligent Cyber-Physical Systems (ICPS) Laboratory.
He has received numerous prestigious honors, including the 2019 ARO YIP Award, the 2018 NSF CAREER Award, the 2018 DoD Minerva Research Initiative Award, the 2021 Georgia Tech Chapter Sigma Xi Young Faculty Award, and the 2026 AE Outstanding Research Advisor for PhD Students Award.
His research has also earned multiple best paper nominations and international recognitions, such as the 2016 International Neural Network Society (INNS) Young Investigator Award, a 2024 NASA Group Achievement Award, the Best Paper Award for Autonomous/Unmanned Vehicles at the 27th Army Science Conference (2010), the Best Presentation Award at the World Congress of Computational Intelligence (2010), and the Best Researcher Award from the Automation and Robotics Research Institute (2011).
Dr. Vamvoudakis has actively contributed to the research community through service on numerous international program committees and by organizing special sessions, workshops, and tutorials at major international conferences. He is currently the Editor-in-Chief of Aerospace Science and Technology and serves on the IEEE Control Systems Society Conference Editorial Board. In addition, he is an Associate Editor for several leading journals, including Automatica, IEEE Transactions on Automatic Control, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Systems, Man, and Cybernetics: Systems, IEEE Transactions on Artificial Intelligence, Neural Networks, IEEE Open Journal of the Computer Society, and the Journal of Optimization Theory and Applications.
Previously, he has served as Guest Senior Editor for special issues of IEEE Transactions on Automation Science and Engineering, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Industrial Informatics, IEEE Transactions on Intelligent Transportation Systems, and the IEEE Open Journal of Control Systems. Dr. Vamvoudakis is a registered Professional Engineer (Electrical/Computer Engineering), a member of the Technical Chamber of Greece, an Associate Fellow of AIAA, and a Senior Member of IEEE.
Prof. Vamvoudakis’ teaching interests center on modern control systems, reinforcement learning, and data-driven decision-making for autonomous and cyber-physical systems. He is particularly interested in teaching how learning-based methods can be integrated with classical control theory to address complex, uncertain, and safety-critical environments. His instruction emphasizes a strong theoretical foundation alongside practical implementation, enabling students to understand both the mathematical principles and real-world applications of intelligent control, robotics, and autonomous systems.
Prof. Vamvoudakis’ teaching interests center on modern control systems, reinforcement learning, and data-driven decision-making for autonomous and cyber-physical systems. He is particularly interested in teaching how learning-based methods can be integrated with classical control theory to address complex, uncertain, and safety-critical environments. His instruction emphasizes a strong theoretical foundation alongside practical implementation, enabling students to understand both the mathematical principles and real-world applications of intelligent control, robotics, and autonomous systems.
Other Labs
Intelligent Cyber Physical Systems Lab https://kyriakos.ae.gatech.edu/res.html
Lab/Collaborations:
- Institute for Robotics and Intelligent Machines (IRIM)
- Decision and Control Lab
- The Center for Machine Learning
- Institute of Information Security and Privacy
Disciplines:
- Flight Mechanics & Controls
AE Multidisciplinary Research Areas:
- Cyberphysical Systems, Safety, and Reliability
- Robotics, Autonomy, and Human Interactions
- Education Ph.D., Electrical Engineering, Automation and Robotics Research Institute, University of Texas at Arlington, USA (2008-2011) Dissertation: Online Learning Algorithms for Differential Dynamic Games and Optimal Control Advisor: Frank L. Lewis GPA: 4.0/4.0
- M.Sc., Electrical Engineering, Automation and Robotics Research Institute, University of Texas at Arlington, USA (2006-2008) Advisor: Frank L. Lewis GPA: 4.0/4.0 Diploma (5 year degree, M.Sc. equivalent),
- Electronic and Computer Engineering, Technical University of Crete, Greece (2001-2006) Thesis: Adaptive Control for Mitogen-Activated Protein Kinase Cascade Models Using Radial Basis Function Neural Networks Advisor:
- M. A. Christodoulou Committee: N.D. Sidiropoulos, F. L. Lewis GPA: 8.6/10 (ranking in the top 1% of class), Highest Honors.
- AE's Outstanding Research Advisor for PhD Students, 2026
- Listed in World's Top 2% Scientists (overall) and World's top 1% Scientists in Automation, 2025
- Lifetime Highly Ranked Scholar by ScholarGPS, 2024
- Listed in World's Top 2% Scientists (overall) and World's top 1% Scientists in Automation, 2024
- Two papers recognized as Google Scholar Top Papers in the area of Automation and Control Theory, 2024
- NASA Achievement Award, NASA imaginAviation, 2024
- Inaugural Highly Ranked Scholar by ScholarGPS, 2024
- Associate Fellow of AIAA, 2024
- Listed in World's Top 2% Scientists (overall) and World's top 1% Scientists in Automation, 2023
- Two papers recognized as Google Scholar Top Papers in the area of Automation and Control Theory, 2023
- Student Recognition of Excellence in Teaching: Fall Semester 2022
- CIOS Honor Roll, 2023
- Appointed Dutton-Ducoffe Professor, 2022
- Two papers recognized as Google Scholar Top Papers in the area of Automation and Control Theory, 2022
- Listed in World's Top 2% Scientists (overall) and World's top 1% Scientists in Automation, 2022
- Student Recognition of Excellence in Teaching: 2021
- CIOS Award, 2021.
- Invited Participant, US National Academy of Sciences (NAS) 8th Arab-American Frontiers of Science, Engineering, and Medicine Symposium, Bin Khalifa University, Qatar, 2021
- Listed in World's Top 2% Scientists (overall) and World's top 1% Scientists in Automation, 2021
- Student Recognition of Excellence in Teaching: Class of 1934 CIOS Honor Roll, 2021
- GT Chapter Sigma Xi Young Faculty Award, 2021
- Two papers recognized as Google Scholar Top Papers in the area of Automation and Control Theory, 2020
- Listed in World's Top 2% Scientists (overall) and World's top 1% Scientists in Automation, 2020
- Article Selected as Cover Page in the International Journal of Robust and Nonlinear Control, vol. 30, no. 9, 2020
- ARO YIP Award, 2019 Best Associate Editor Award, Control Theory and Technology, Springer, 2019
- Senior Member of AIAA, 2019
- NSF CAREER Award, 2018
- DoD Minerva Research Initiative Award, 2018 Paper on “Optimal and Autonomous Control Using Reinforcement Learning: A Survey,” is listed at the IEEE Computational Intelligence Society Publication Spotlight, 2018
- Paper recognized as one of the Google Scholar Top Papers in the area of Automation and Control Theory, 2018 International Neural Network Society (INNS) Young Investigator Award, 2016
- Senior Member of IEEE, 2015 Inclusion of the 2010 Automatica paper in the IFAC Virtual Special Issue of Annual Reviews in Control (This virtual special issue highlights papers published between 2010 and 2013 that have appeared in the six journals of the IFAC), as one of the papers with the highest citation rates in the control field, 2014
- Certificates for Four Research Articles Featured in ScienceDirect Top-25 List of Most Popular (Hottest) Articles in Automatica, Elsevier, 2010-2013
- Honor by the Office of the Provost and the University Library for Creative Works and Awards, University of Texas at Arlington, 2011
- Best Researcher Award, Automation and Robotics Research Institute, 2011
- Best Paper Award for Autonomous/Unmanned Vehicles, 27th Army Science Conference, Orlando, December 2010
- Best Presentation Award at the World Congress of Computational Intelligence, Barcelona, July 2010
- Invited member of Sigma Xi, The Scientific Research Honor Society, Tau Beta Pi (TBP),
- Golden Key International, and Eta Kappa Nu (HKN) honor engineering societies Registered Electrical/Computer Engineer (PE), Technical Chamber of Greece (2007)
- Biography appears in Marquis Who's Who in the World since 2009, Marquis Who's Who in Science and Engineering since 2010 and Marquis Who's Who in America since 2012
- STEM Doctoral Fellowship (2008, 2009, 2010, 2011) Fellowship of the Greek State Scholarships Foundation (IKY) for the performance at undergraduate studies
- Honors for every of the six years high school education from the Greek Ministry of Education (GPA 3.92/4)
- NMT Kokolakis, KG Vamvoudakis, WM Haddad, Fixed-time learning for safe time-critical verification using reachability analysis, Automatica 183, 112528, 2026
- J Netter, GP Kontoudis, KG Vamvoudakis, Decentralized Multi-Agent Motion Planning Using Cognitive Hierarchy and Gaussian Process Classification, IEEE Transactions on Intelligent Vehicles, 2026
- A Wadi, KG Vamvoudakis, Trajectory-informed machine learning for quantum optimal control of uncertain systems, Automatica 185, 112756, 2026
- F Fotiadis, KG Vamvoudakis, Input–output data-driven sensor selection for cyber-physical systems, Automatica 186, 112829, 2026
- F. Fotiadis, K. G. Vamvoudakis, Z.-P. Jiang, “Data-Driven Actuator Allocation for Actuator Redundant Systems,” IEEE Transactions on Automatic Control, vol. 69, no. 4, pp. 2249-2264, 2024.