Associate Professor and Cloud Technology Endowed Fellow
Department of Computer Engineering (CE) and Department of Computer Science (CS)
College of AI, Cyber and Computing (CAICC)
The University of Texas at San Antonio
Address: One UTSA Circle, San Antonio, TX 78249
E-mail: Panagiotis.Markopoulos@utsa.edu
Website: https://www.markopoulos.us
Artificial intelligence, machine learning, data science, and signal/image processing, with emphasis in trustworthiness and efficiency.
Current research topics:
Trustworthy (reliable and explainable) artificial intelligence
Machine learning from limited and/or corrupted data
Federated learning with privacy constraints
Adaptive and continual learning in dynamic environments
Multimodal learning and data fusion
Quantum machine learning
Application areas include, among others:
Computer vision (image classification, object detection and tracking )
Remote sensing (various imagery types including hyperspectral imagery, SAR, electro-optical; modality fusion, image segmentation, object detection and tracking)
Wireless communication systems (physical layer modulation, transmit/receive beamforming, spread-spectrum channelization, multi-user channel access, interference avoidance and suppression, direction-of-arrival estimation and source tracking, radar)
Healthcare (privacy-aware, limited data, data analytics and inference)
I am 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). I serve as 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, I held the Margie and Bill Klesse Endowed Associate Professorship in the Department of Electrical and Computer Engineering (ECE) in the Klesse College of Engineering and Integrated Design (KCEID), at UT San Antonio. In 2025, ECE was reorganized into Electrical Engineering (EE, housed in KCEID) and Computer Engineering (CE, housed in CAICC), and I joined CE at CAICC. Prior to UTSA, I was a tenured Associate Professor at the Rochester Institute of Technology (RIT). During the summers of 2018, 2020, and 2021, I was a Visiting Faculty (Independent Contractor) with the U.S. Air Force Research Laboratory (AFRL), Information Directorate, in Rome, NY.
My expertise lies in machine learning, artificial intelligence, signal and image processing, and data science. Application domains for my work include wireless communications, computer vision, remote sensing, and healthcare, among others. My research mission is to advance efficient, robust, and trustworthy solutions in these areas. Together with students and collaborators, I have co-authored more than 80 journal and conference articles and three book chapters. My research has been funded 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, I was recognized with the AFOSR Young Investigator Program (YIP) Award. In 2021, I was elevated to IEEE Senior Member.
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:
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.
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.”
© Copyright 2025 Panagiotis Markopoulos