Scholar
Christos Diou
Google Scholar ID: USwu_AgAAAAJ
Department of Informatics and Telematics, Harokopio University of Athens
Citations & Impact
Citations
1,130
H-index
18
i10-index
33
Publications
20
Co-authors
24
list available
Publications
Resume (English only)
Academic Achievements
- Published several papers in international research journals and conferences on topics related to Artificial Intelligence, Machine Learning, and their applications; supervised PhD candidate Ioannis Sarridis et al. whose paper “MAVias: Mitigate any Visual Bias” was accepted for publication in ICCV 2025; co-authored with PhD student Aristotelis Ballas the paper “Gradient-Guided Annealing for Domain Generalization” which was accepted as a highlight paper at CVPR 2025; published the paper “FLAC: Fairness-Aware Representation Learning by Suppressing Attribute-Class Associations” in IEEE Transactions on Pattern Analysis & Machine Intelligence.
Research Experience
- Teaches courses related to artificial intelligence, machine learning, and computer programming; has over 15 years of experience participating in national and international research projects; currently the PI for the EU-funded projects REBECCA and RELEVIUM, and also participates in projects BETTER4U, HUMAINE, and MELIORA.
Education
- Earned a BSc and Ph.D. in Electrical and Computer Engineering from Aristotle University of Thessaloniki.
Background
- Associate Professor at the Department of Informatics and Telematics, Harokopio University of Athens, with research interests in developing novel machine learning algorithms and their applications in healthcare, domain generalization, causal effect estimation, bias assessment and mitigation in multimodal models, and feature effect methods for tabular data.
Miscellany
- Invited to give a talk at Institut Lyfe in Lyon, France; gave a keynote speech at the International Astronomer’s Union Symposium on exploring the Universe with Artificial Intelligence; started beta testing Beam, a platform to support behavior studies; released Effector, a Python package for global and regional feature effects.
