Ioannis (Yiannis) Sarridis

I received both my bachelor’s and master’s degrees from the Department of Informatics at Aristotle University of Thessaloniki, Thessaloniki, Greece, in 2018 and 2020, respectively. I am currently pursuing a Ph.D. degree at Harokopio University of Athens and working as a Research Associate with the Centre for Research and Technology Hellas, Thessaloniki, Greece. My research interests include AI fairness, face recognition, AI at the edge, computer vision, and deep learning.

news

Nov 05, 2024	The first journal paper related to my PhD research was published in the IEEE Transactions on Pattern Analysis and Machine Intelligence. I. Sarridis, C. Koutlis, S. Papadopoulos and C. Diou, “FLAC: Fairness-Aware Representation Learning by Suppressing Attribute-Class Associations” in IEEE Transactions on Pattern Analysis & Machine Intelligence, doi: 10.1109/TPAMI.2024.3487254. Paper: link Code: link

Nov 05, 2024

The first journal paper related to my PhD research was published in the IEEE Transactions on Pattern Analysis and Machine Intelligence.

I. Sarridis, C. Koutlis, S. Papadopoulos and C. Diou, “FLAC: Fairness-Aware Representation Learning by Suppressing Attribute-Class Associations” in IEEE Transactions on Pattern Analysis & Machine Intelligence, doi: 10.1109/TPAMI.2024.3487254.
Paper: link
Code: link

selected publications

FLAC: Fairness-Aware Representation Learning by Suppressing Attribute-Class Associations

Ioannis Sarridis, Christos Koutlis, Symeon Papadopoulos, and Christos Diou

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024

DOI Bib

@article{Sarridis2024TPAMI,
  author = {Sarridis, Ioannis and Koutlis, Christos and Papadopoulos, Symeon and Diou, Christos},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  title = {{FLAC}: Fairness-Aware Representation Learning by Suppressing Attribute-Class Associations},
  year = {2024},
  volume = {},
  number = {},
  pages = {1-13},
  keywords = {Prevention and mitigation;Artificial intelligence;Training;Data models;Mutual information;Accuracy;Visualization;Representation learning;Predictive models;Minimization;Bias mitigation;fairness;mutual information},
  doi = {10.1109/TPAMI.2024.3487254},
}