Dr. Panagiotis (Panos) Markopoulos, PhD
Associate Professor and Cloud Technology Endowed Fellow
Departments of Computer Engineering and Computer Science
College of AI, Cyber and Computing (CAICC)
The University of Texas at San Antonio
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Contact Information
Contact Information
Address: One UTSA Circle, San Antonio, TX 78249
E-mail: Panagiotis.Markopoulos@utsa.edu
Website: https://www.markopoulos.us
Areas of Expertise
Areas of Expertise
Dr. Panagiotis (Panos) Markopoulos’s research focuses on the design of reliable learning systems that operate under real-world constraints and in critical applications. He develops theory and algorithms for learning that are robust to challenging data (e.g., contaminated, limited, imbalanced, missing), adaptive to dynamic environments, and efficient in both computation and sample usage. His work integrates machine learning, optimization theory, and statistical signal processing to advance principled and deployable intelligent systems.
Core Research Areas
Robust learning under data corruption and adversarial contamination
Learning from heterogeneous, distributed, and privacy-constrained data
Federated and decentralized learning systems
Adaptive and continual learning in non-stationary environments
Computational and data efficiency in large-scale learning
Multimodal learning and structured data fusion
Intelligent wireless communication systems and physical-layer signal processing
Quantum and quantum-inspired optimization for machine learning
Application Domains
Wireless Communication Systems: physical-layer modulation, transmit/receive beamforming, interference suppression, direction-of-arrival estimation, radar signal processing
Computer Vision: image classification, object detection and tracking
Remote Sensing: hyperspectral, SAR, and electro-optical imagery; modality fusion; segmentation; object detection and tracking
Cybersecurity: anomaly detection, adversarial robustness, secure learning under attack
Healthcare Analytics: privacy-aware inference from limited clinical data; decision support and computational diagnostics
Brief Biography
Brief Biography
Dr. Panagiotis (Panos) Markopoulos, PhD, is an Associate Professor and Cloud Technology Endowed Fellow with the Departments of Computer Engineering (CE) and Computer Science (CS) in the College of AI, Cyber and Computing (CAICC) at The University of Texas at San Antonio (UT San Antonio). He serves as Founding Director of the Machine Learning Optimization and Systems (MILOS) Laboratory and Lead for Trustworthy AI in MATRIX: The UTSA AI Consortium for Human Well-Being.
From 2022 to 2025, he held the Margie and Bill Klesse Endowed Associate Professorship in Electrical and Computer Engineering at UT San Antonio. In 2025, following a college reorganization, he joined the Department of Computer Engineering within the College of AI, Cyber and Computing. Prior to UTSA, he was a tenured Associate Professor at the Rochester Institute of Technology. During the summers of 2018, 2020, and 2021, he served as Visiting Faculty (Independent Contractor) with the U.S. Air Force Research Laboratory (AFRL), Information Directorate, in Rome, NY.
Dr. Markopoulos develops theory and algorithms for machine learning under real-world system constraints and challenging data conditions. He designs learning methods that are computationally and data efficient, robust to corruption and adversarial contamination, capable of operating over heterogeneous, distributed, and privacy-constrained data sources, and adaptive to non-stationary and continual environments. His work integrates machine learning, optimization theory, and statistical signal processing to advance principled and deployable intelligent systems. Applications span wireless communications, remote sensing, computer vision, cybersecurity, and computational healthcare. He has co-authored more than 80 refereed journal and conference publications and three book chapters.
His research has been supported by the U.S. National Science Foundation (NSF), the National Geospatial-Intelligence Agency (NGA), the U.S. Air Force Office of Scientific Research (AFOSR), and AFRL. In 2019, he received the AFOSR Young Investigator Program (YIP) Award, and in 2021 he was elevated to IEEE Senior Member.
Professional Positions
Professional Positions
Associate Professor and Cloud Technology Endowed Fellow
Department of Computer Engineering (CE), College of AI, Cyber and Computing (CAICC)
Department of Computer Science (CS), College of AI, Cyber and Computing (CAICC)
The University of Texas at San Antonio (UT San Antonio), San Antonio, TX, 9/2025 – Present.
(In 2025, ECE was reorganized into EE, housed in KCEID, and CE, housed in CAICC, and I joined CE at CAICC)
Concurrent Roles:
Lead, AI Systems research thrust, Department of Computer Engineering, 2025 - Present.
Founding Director, Machine Learning Optimization and Systems Laboratory, 2022 – Present.
Lead for Trustworthy AI, MATRIX: The UTSA AI Consortium for Human Well-Being, 2024 – Present.
Margie and Bill Klesse Endowed Associate Professor
Department of Electrical & Computer Engineering (ECE), Klesse College of Engineering and Integrated Design (KCEID)
Department of Computer Science (CS), College of Science (COS)
The University of Texas at San Antonio (UT San Antonio), San Antonio, TX, 8/2022 – 9/2025.
Concurrent Roles:
Founding Director, Machine Learning Optimization and Systems Laboratory, 2022 – Present.
Founding Director, Multimodal Sensing and Signal Processing Education Laboratory, 2023 – 2025.
Chair, Signal Processing and Learning Concentration, ECE Dept., 2022 – 2025.
Co-Lead for Trustworthy AI, MATRIX: The UTSA AI Consortium for Human Well-Being, 2024 – Present.
Core Faculty Member, UTSA School of Data Science, 2022 – 2025 (SDS became part of CAICC).
Associate Professor (with Tenure)
Department of Electrical and Microelectronic Engineering, Kate Gleason College of Engineering (KGCOE)
Rochester Institute of Technology (RIT), Rochester, NY, 2021 – 8/2022.
Concurrent Roles:
Director, Machine Learning Optimization & Signal Processing (MILOS) Lab
Core Faculty, RIT Center for Human-aware Artificial Intelligence (CHAI)
Extended Faculty, PhD Program in Computing and Information Sciences
Extended Faculty, PhD Program in Mathematical Modeling
Member, RIT Faculty Senate (2021-2022)
Assistant Professor (Tenure-Track)
Department of Electrical and Microelectronic Engineering, Kate Gleason College of Engineering (KGCOE)
Rochester Institute of Technology, Rochester, NY, 2015 – 2022.
Visiting Faculty (Independent Contractor)
Visiting Faculty Research Program, U.S. Air Force Research Laboratory (AFRL), Information Institute, Rome, NY, Summers of 2018, 2020, 2021.
Graduate Research Assistant
Department of Electrical Engineering, The State University of New York at Buffalo (UB), Buffalo, NY, 2011 – 2015.
Education
Education
Ph.D., Electrical Engineering
State University of New York at Buffalo, Buffalo, NY, 2015
Dissertation: “Optimal Algorithms for L1-norm Principal Component Analysis: New Tools for Signal Processing and Machine Learning with Few and/or Faulty Training Data.”
M.S., Electronic and Computer Engineering
Technical University of Crete, Chania, Greece, 2012
Thesis: “Full-rate Differential M-PSK Alamouti Modulation with Polynomial-complexity Maximum-likelihood Noncoherent Detection.”
Engineering Diploma (5-year program), Electronic and Computer Engineering
Technical University of Crete, Chania, Greece, 2010
Thesis: “Maximum-Likelihood Noncoherent M-PSK OSTBC Detection with Polynomial Complexity.”
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