Vangelis Metsis

Associate Professor of Computer Science, Texas State University

vangelis1.jpg

Comal Bldg, Room 307F

601 University Drive

San Marcos, TX 78666

Phone: 512-245-7509

vmetsis@txstate.edu

Dr. Vangelis Metsis is an Associate Professor in the Department of Computer Science at Texas State University and the Director of the Intelligent Multimodal Computing and Sensing (IMICS) Lab. He joined the department in August 2014.

Dr. Metsis earned his Ph.D. in Computer Science from the University of Texas at Arlington (UTA) in 2011, focusing on human-centered multimodal data analysis. He holds a B.S. with honors in Computer Science from the Department of Informatics at the Athens University of Economics and Business (AUEB) in Greece.

Dr. Metsis' interests span the areas of Machine Learning and Deep Learning with a focus on human-centric AI applications in Healthcare, Pervasive Computing, Affective Computing, and VR/AR-based Therapy. His work addresses challenges in time-series analysis and multimodal biosignal processing, including novel generative AI methods for data augmentation, robust deep learning architectures for temporal data, and intelligent IoT environments that monitor, assist, and rehabilitate users.

He has secured over $2 million in research funding as Principal Investigator and Co-Principal Investigator, with grants from the NSF, U.S. Department of Education, and industry partners. Dr. Metsis has published extensively in peer-reviewed journals and conferences, with over 80 publications to his name.

Recognized for his dedication to teaching and mentoring, Dr. Metsis received the Presidential Award in Teaching from Texas State University in 2022, along with multiple College of Science and Engineering Excellence in Teaching Awards and the Alpha Chi Favorite Professor honor. He has advised multiple Ph.D. and Master's students, as well as numerous undergraduate researchers. His teaching spans a wide range of computer science courses, from introductory programming to advanced topics in machine learning and computer vision.

selected publications

  1. DSP
    Geometric Knowledge Distillation via Procrustes Analysis for Efficient Motion Sequence Classification
    Bikram De, Kostas Blekos, Vasilis Pikoulis, Dimitrios Kosmopoulos, and Vangelis Metsis
    In 2025 25th International Conference on Digital Signal Processing (DSP), 2025
  2. Biodiffusion: A versatile diffusion model for biomedical signal synthesis
    Xiaomin Li, Mykhailo Sakevych, Gentry Atkinson, and Vangelis Metsis
    Bioengineering, 2024
  3. Recurrence and Self-attention vs the Transformer for Time-Series Classification: A Comparative Study
    Alexander Katrompas, Theodoros Ntakouris, and Vangelis Metsis
    In 20th International Conference on Artificial Intelligence in Medicine, 2022
  4. TTS-GAN: A Transformer-Based Time-Series Generative Adversarial Network
    Xiaomin Li, Vangelis Metsis, Huangyingrui Wang, and Anne Hee Hiong Ngu
    In 20th International Conference on Artificial Intelligence in Medicine, 2022
  5. Classification of emotional arousal during multimedia exposure
    Adam Anderson, Thomas Hsiao, and Vangelis Metsis
    In Proceedings of the 10th International Conference on PErvasive Technologies Related to Assistive Environments, 2017
  6. IoT middleware: A survey on issues and enabling technologies
    Anne H Ngu, Mario Gutierrez, Vangelis Metsis, Surya Nepal, and Quan Z Sheng
    IEEE Internet of Things Journal, 2016
  7. DNA copy number selection using robust structured sparsity-inducing norms
    Vangelis Metsis, Fillia Makedon, Dinggang Shen, and Heng Huang
    IEEE/ACM transactions on computational biology and bioinformatics, 2013
  8. Non-invasive analysis of sleep patterns via multimodal sensor input
    Vangelis Metsis, Dimitrios Kosmopoulos, Vassilis Athitsos, and Fillia Makedon
    Personal and Ubiquitous Computing, 2014
  9. Digital cities of the future: Extending@ home assistive technologies for the elderly and the disabled
    Charalampos Doukas, Vangelis Metsis, Eric Becker, Zhengyi Le, Fillia Makedon, and Ilias Maglogiannis
    Telematics and Informatics, 2011
  10. Spam filtering with naive bayes-which naive bayes?
    Vangelis Metsis, Ion Androutsopoulos, and Georgios Paliouras
    In Third Conference on Email and Anti-Spam (CEAS), 2006