Panagiotis Markopoulos
Panagiotis Markopoulos, Ph.D. based in San Antonio, Texas. 15 years of experience with specialization in Artificial Intelligence, Machine Learning, Signal Processing.
Ph.D. ·
About
Dr. Panagiotis Markopoulos has more than 15 years of research and teaching experience in electrical and computer engineering and computer science. He is an internationally recognized and awarded expert in machine learning, artificial intelligence, and signal processing, with research focused on the development of reliable learning systems that operate under real-world constraints and in critical applications. His work spans foundational areas including robust learning under data corruption and adversarial contamination, federated and decentralized learning systems, adaptive and continual learning in non-stationary environments, multimodal learning and structured data fusion, and computationally efficient large-scale learning. He has also contributed to emerging areas including quantum and quantum-inspired optimization for machine learning. Dr. Markopoulos applies these methods across multiple domains including computer vision, remote sensing, cybersecurity, computational healthcare, and wireless communication systems.
He has authored more than 80 peer-reviewed publications, including 25 journal articles in leading IEEE and other technical journals, and has presented his research at numerous international conferences. His work has been supported through competitive research funding from major U.S. agencies including the National Science Foundation, the U.S. Air Force Office of Scientific Research (including an AFOSR Young Investigator Program Award), the National Geospatial-Intelligence Agency, and the National Institutes of Health.
Dr. Markopoulos has held tenure-track and tenured faculty positions at the Rochester Institute of Technology and The University of Texas at San Antonio since 2015, and currently serves as Associate Professor and Cloud Technology Endowed Fellow in the Departments of Computer Engineering and Computer Science at UT San Antonio’s College of AI, Cyber, and Computing. He is the founding director of the Machine Learning Optimization and Systems Laboratory and leads major AI research initiatives at UTSA, including the AI Systems thrust in Computer Engineering and the Trustworthy AI thrust within the MATRIX UTSA AI Consortium for Human Well-Being.
Throughout his academic career, Dr. Markopoulos has successfully mentored numerous doctoral and master’s students to completion, with his advisees receiving prestigious distinctions including the Rochester Institute of Technology Best Doctoral Dissertation Award. His former students now hold technical and research positions at leading technology companies including Apple, Amazon, and AMD.
He currently serves as Associate Editor for IEEE Transactions on Artificial Intelligence. His professional service includes membership on the IEEE Signal Processing Society Education Board and leadership roles in organizing international technical conferences and workshops.
Dr. Markopoulos’s theoretical expertise, algorithm development, real-world system applications, and extensive scholarship make him a highly credible expert witness in machine learning, artificial intelligence, and signal processing, as well as their applications in computer vision, remote sensing, cybersecurity, computational healthcare, and wireless communication systems.
Specialties
Work Experience
Associate Professor (w Tenure) and Cloud Technology Endowed Fellow, Departments of Computer Engineering and Computer Science, College of AI, Cyber, and Computing, The University of Texas at San Antonio. Concurrent roles: (i) Lead, AI Systems research thrust, Department of Computer Engineering, 2025 - Present; (ii) Lead, Trustworthy AI Thrust, MATRIX: UT San Antonio AI Consortium for Human Well-Being, 2024 - Present; (iii) Founding Director, UT San Antonio Machine Learning Optimization and Systems (MILOS) Laboratory, 2022 - Present; (iv) Faculty, Graduate Program in Biomedical Engineering, 2025 - Present.
Associate Professor (w Tenure) and Margie and Bill Klesse Endowed Professor, Departments of Electrical & Computer Engineering and Computer Science, Klesse College of Engineering and Integrated Design, The University of Texas at San Antonio. Concurrent roles: (i) Chair, ECE Digital Signal Processing Concentration, September 2022 - August 2025; (ii) Lead, Trustworthy AI Thrust, MATRIX: UT San Antonio AI Consortium for Human Well-Being, 2024 - Present; (iii) Founding Director, UT San Antonio Machine Learning Optimization and Systems (MILOS) Laboratory, 2022 - Present.
Associate Professor (w Tenure), Department of Electrical and Microelectronic Engineering, Kate Gleason College of Engineering, Rochester Institute of Technology. Concurrent roles: (i) Founding Director, Machine Learning Optimization and Signal Processing Lab; (ii) Core Faculty, Center for Human-aware Artificial Intelligence; (iii) Extended Faculty, Ph.D. Program in Computing and Information Sciences; (iv) Extended Faculty, Ph.D. Program in Mathematical Modeling; (v) Member, RIT Faculty Senate, 2021 to 2022.
Departments of Computer Engineering and Computer Science, College of AI, Cyber and Computing
Visiting Faculty Research Program (VFRP), U.S. Air Force Research Laboratory, Information Directorate U.S (contract with Griffiss Institute Inc.) Research in machine learning.
Visiting Faculty Research Program (VFRP), U.S. Air Force Research Laboratory, Information Directorate U.S (contract with Griffiss Institute Inc.) Research in machine learning.
Visiting Faculty Research Program (VFRP), U.S. Air Force Research Laboratory, Information Directorate U.S (contract with Griffiss Institute Inc.) Research in machine learning.
Assistant Professor (Tenure Track), Department of Electrical and Microelectronic Engineering, Kate Gleason College of Engineering, Rochester Institute of Technology.
Graduate Research Assistant, Department of Electrical Engineering, University at Buffalo, The State University of New York. Research in signal processing and machine learning, specializing in machine learning algorithms learning from limited and/or corrupted training data.
Leading AI Systems research thrust in Computer Engineering
Leading Trustworthy AI Thrust at MATRIX AI Consortium
Founding Director of MILOS Laboratory
Jointly offered graduate program in Biomedical Engineering
Departments of Electrical and Computer Engineering and Computer Science
Chair of ECE Digital Signal Processing Concentration
Founding Director of Machine Learning Optimization Laboratory
Founding Director of MSSP Laboratory
Department of Electrical and Microelectronic Engineering
Founding Director of MILOS Lab
Core Faculty at CHAI
Extended Faculty in Ph.D. Program
Extended Faculty in Ph.D. Program
Member of RIT Faculty Senate
Department of Electrical and Microelectronic Engineering
Visiting Faculty at AFRL
Visiting Faculty at AFRL
Visiting Faculty at AFRL
Information Directorate, Rome, NY (Summers 2018, 2020, 2021)
Education
Credentials & Licenses
University at Buffalo, The State University of New York
Technical University of Crete
Technical University of Crete
Goethe Institute
Institute of Electrical and Electronics Engineers