October 14, 2025 —
Meet Dr. Panagiotis (Panos) Markopoulos, appointed Thrust Co-Lead of MATRIX, contributing to the Trustworthy AI thrust.
Dr. Markopoulos is an Associate Professor and Cloud Technology Endowed Fellow in the College of AI, Cyber, and Computing (CAICC) at UT San Antonio, with joint appointments in the Departments of Computer Engineering and Computer Science. He is also a faculty member of the Graduate Program in Biomedical Engineering and the Founding Director of the Machine Learning Optimization and Systems (MILOS) Laboratory.
His research focuses on Trustworthy Artificial Intelligence with current emphasis on robust and efficient machine learning (ML) from challenging real-world data (including limited, corrupted, missing, dynamic, biased, multimodal), federated learning under privacy constraints, and adaptive and continual learning. Applications of his ML research span critical domains, from healthcare to defense, advancing the reliability, fairness, security, and ethical alignment of AI systems.
His work has been supported by sponsors including the NSF, NIH, AFOSR, and NGA. In 2019 he received the AFOSR Young Investigator Program (YIP) Award. At UT San Antonio, he held the Margie and Bill Klesse Endowed Professorship from 2022 to 2025 and has held the Cloud Technology Endowed Fellowship since 2025.
Dr. Markopoulos’s leadership in MATRIX includes heading the Trustworthy AI thrust and advancing collaborative research across UT San Antonio and partner institutions.
Reflecting on his role in MATRIX, Dr. Markopoulos shared:
“MATRIX AI Consortium brings together engineers, computer scientists, clinicians, and domain experts to deliver AI that serves human well-being. The Trustworthy AI thrust focuses on concrete advances that make AI systems reliable with challenging data, resilient to attacks, fair and explainable in decisions, and aligned with societal values.”
Outside research, he enjoys spending time with his family and exploring local nature and culture.
Explore our full list of consortium members to discover potential collaborators and connect with researchers advancing interdisciplinary, cross-cutting AI at MATRIX.