Dr. Panagiotis (Panos) P. Markopoulos, Ph.D.

• Address: Room 340E, San Pedro I Building, 506 Dolorosa St, San Antonio, TX 78204

• E-mail: panagiotis.markopoulos@utsa.edu; panos@utsa.edu 

• Connect: LinkedIn, Google Scholar, ORCiD, GitHub

Dr. Markopoulos is an expert in machine learning, data science, and adaptive signal processing. His current focus is on developing efficient, robust, and reliable machine learning solutions for challenging real-world data. Current research topics include:

• Efficient and robust learning with limited, faulty, and corrupted data. 

• Continual, incremental, and dynamic learning.

• Multimodal data and deep learning fusion.

• Distributed data and federated machine learning.

• Quantum machine learning.

His research has significant applications in remote sensing, computer vision, wireless communication systems, and healthcare technology.

Dr. Panagiotis (Panos P.) Markopoulos, Ph.D., is an Associate Professor and Margie and Bill Klesse Endowed Professor with the Departments of  Electrical and Computer Engineering and Computer Science at The University of Texas at San Antonio (UTSA). He is also a core faculty member of the UTSA School of Data Science and MATRIX: The UTSA AI Consortium for Human Well-Being. Prior to joining UTSA, Dr. Markopoulos was a tenured Associate Professor with the Rochester Institute of Technology (RIT). In the Summers of 2018, 2020, and 2021, he was a Visiting Research Faculty at the U.S. Air Force Research Laboratory (AFRL), Information Directorate, in Rome NY.

His expertise is in the areas of machine learning, data analysis, adaptive signal processing, and communication systems. His research mission is to advance efficient and trustworthy solutions in these areas. Together with students and collaborators, Dr. Markopoulos has co-authored more than 70 journal and conference articles and 3 book chapters. Since 2016, his research has received external funding awards from sponsors including the US National Science Foundation (NSF), the US National Geo-Spatial Intelligence Agency, the US Air Force Office of Scientific Research (AFOSR), and the Air Force Research Laboratory (AFRL). 

In October 2019, Dr. Markopoulos received the Young Investigator Program (YIP) Award, from the AFOSR. In 2021, Dr. Markopoulos was elevated to the grade of IEEE Senior Member.

• Ph.D., Electrical Engineering, University at Buffalo, The State University of New York, 2015.

• M.S., Electronic and Computer Engineering, Technical University of Crete, Greece, 2012.

• Engineering Diploma (5-year program), Electronic and Computer Engineering, Technical University of Crete, Greece, 2010.

• Associate Professor and Margie and Bill Klesse Endowed Professor, Aug. 2022 - present. 

  • Dept. of Electrical and Computer Engineering and Dept. of Computer Science, The University of Texas at San Antonio

  • Concurrent roles at UTSA:

• • Core Faculty Member, School of Data Science, UTSA

• Core Faculty Member and Co-Lead for Trustworthy AI, MATRIX: The UTSA AI Consortium for Human Well-Being

• Associate Professor, Aug. 2021 - Aug. 2022.

  • Dept. of Electrical and Microelectronic Engineering, Rochester Institute of Technology, Rochester, NY.  

  • Concurrent roles at RIT:

  • Director, Machine Learning Optimization & Signal Processing (MILOS) Lab.

  • Core Faculty Member, RIT Center for Human-aware Artificial Intelligence (CHAI).

  • Extended Faculty Member, Ph.D. Program in Computing and Information Sciences and Ph.D. Program in Mathematical Modeling.

  • Member, RIT Faculty Senate, 2021-2022.

• Assistant Professor, Aug. 2015 - Aug. 2021. 

  • Dept. of Electrical and Microelectronic Engineering, Rochester Institute of Technology, Rochester, NY.

• Visiting Research Faculty (Summer), 2018, 2019, 2021.

  • U.S. Air Force Research Laboratory (AFRL), Information Directorate, Rome, NY.

• Graduate Research Assistant, Aug. 2011 - May 2015. 

  • SUNY Research Foundation, University at Buffalo (UB), The State University of New York, Buffalo, NY.

All Publications (Google Scholar) | Codes (GitHub)

• R. Hyder, K. Shao, B. Hou, P. P. Markopoulos, A. Prater-Bennette, and M. S. Asif, "Incremental Task Learning with Incremental Rank Updates," European Conference on Computer Vision (ECCV), 2022. Code 

• M. Dhanaraj and P. P. Markopoulos, "On the Asymptotic L1-PC of Elliptical Distributions," IEEE Signal Processing Letters, 2022. 

• D. G. Chachlakis, M. Dhanaraj, A. Prater-Bennette, P. P. Markopoulos, “Dynamic L1-norm Tucker Tensor Decomposition,” IEEE Journal on Selected Topics in Signal Processing, Special Issue on Tensor Decomposition for Signal Processing and Machine Learning, vol. 15, no. 3, pp. 587-602, April 2021. 

• D. G. Chachlakis and P. P. Markopoulos, “Structured Autocorrelation Matrix Estimation for Coprime Arrays," Signal Processing (Elsevier), vol. 183, no. 107987, June 2021. Code

• M. Sharma, P. P. Markopoulos, E. Saber, M. S. Asif, and A. Prater-Bennette, "Convolutional Auto-Encoder with Tensor-Train Factorization," in Proc. International Conference on Computer Vision (ICCV 2021, RLS-CV workshop), 2021.

• M. Sharma, P. P. Markopoulos, and E. Saber, "YOLOrs-LITE: A Lightweight CNN for Real-time Object Detection in Remote Sensing," in Proc. IEEE International Geoscience and Remote Sensing Symposium (IEEE IGARSS), Brussels, Belgium, July 2021.

• M. Sharma, M. Dhanaraj, D. G. Chachlakis, S. Karam, R. Ptucha, P. P. Markopoulos, E. Saber, “YOLOrs: Object Detection in Multimodal Remote Sensing Imagery,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 1497 - 1508, November 2020.

• D. G. Chachlakis, P. P. Markopoulos, and A. Prater-Bennette, “L1-Norm Tucker Tensor Decomposition,” IEEE Access, vol. 7, pp. 178454 - 178465, November 2019. Code

• Y. Liang, P. P. Markopoulos, and E. Saber, “Spatial-Spectral Segmentation of Hyperspectral Images for Subpixel Target Detection,” SPIE Journal of Applied Remote Sensing, vol. 13, no. 3, pp. 036502:1-036502:16, July 2019. 

• P. P. Markopoulos, M. Dhanaraj, and A. Savakis, “Adaptive L1-Norm Principal-Component Analysis with Online Outlier Rejection,” IEEE Journal Selected Topics in Signal Processing, vol. 12, no. 6, pp. 1-13, December 2018.

• Title: PARTNER: Neuro-Inspired AI for the Edge at UTSA (NAIAD). Funding agency: U.S. National Science Foundation (NSF). Period: September 2023 - August 2027. Amount: $2,800,000. Role: Co-PI. 

• AFOSR Young Investigator Program Award. Title: Theory and Efficient Algorithms for Dynamic and Robust L1-Norm Analysis of Tensor Data. Funding agency: U.S. Air Force Office of Scientific Research (AFOSR). Period: January 2020 - May 2024. Amount: $348,460. Role: Sole PI.

• Title: Target Detection/Tracking and Activity Recognition from Multimodal Data. Funding agency: U.S. Departement of Defense. Period: September 2019 - September 2024. Total amount: $858,534. Role: Co-PI. 

• Young Investigator Program (YIP) Award, Air Force Office of Scientific Research (AFOSR), 2020.   

• Exemplary Performance in Research, Kate Gleason College of Engineering, RIT, 2019, for the research proposals submitted in 2018.

• Exemplary Performance in Teaching, Kate Gleason College of Engineering (KGCOE), RIT, 2019.  

• Exemplary Performance in Research, Kate Gleason College of Engineering, RIT, 2018, for the research proposals submitted in 2017.

• Runner-up Poster Award, IEEE  Western New York Image and Signal Processing Workshop, 2018, for the paper "Gait recognition based on tensor analysis of acceleration data from wearable sensors." 

•  Student Travel Grant Award, SPIE  Defense and Commercial Sensing, 2017, for the paper "Adaptive sparse-binary waveform design for all-spectrum channelization."  

• Exemplary Reviewer, IEEE Communications Society, 2017.  "For  contributions made in furthering the objectives of the Society as Exemplary Reviewer of IEEE Wireless Communications Letters, 2016." 

•  Student Travel Grant Award, SPIE  Defense, Security, and Sensing, 2014, for the paper "Direction finding with L1-norm subspaces."

• Best Paper Award in Physical Layer Communications  and Signal Processing, IEEE/VTS/EURASIP  International Symposium on Wireless Communication Systems, 2013, for the paper "Some options for L1-subspace signal processing."

• Senior Member, IEEE (Computer, Signal Processing, Computational Intelligence, and Communication Societies). 

• Member, SIAM.

• Member, SPIE.

• Member, American Society for Engineering Education (ASEE).