Christos Diou

Assistant Professor @DIT/HUA


Office 3.5

Omirou 9, Tavros, 17778

Athens, Greece


Hello and welcome to my homepage. I am an Assistant Professor of Artificial Intelligence and Machine Learning at the Department of Informatics and Telematics, at the Harokopio University of Athens, Greece, where I teach courses related to artificial intelligence, machine learning, as well as computer programming. I hold a BSc and Ph.D. in Electrical and Computer Engineering from the Aristotle University of Thessaloniki.

My research focuses on the development of novel machine learning algorithms and their applications in healthcare. My recent research interests include the development of methods for the measurement and modeling of human behavior for health applications, the development of machine learning algorithms that generalize across domains (Domain Generalization) and the use of machine learning for causal effect estimation from observational data.

I have published several papers in international research journals and conferences in topics related to Artificial Intelligence, Machine Learning and their applications, while I have over 15 years of experience participating in national and international research projects. I am currently the PI for the EU-funded projects REBECCA and RELEVIUM.


Apr 10, 2024 We are proud to announce Effector, a python package for global and regional feature effects, which is part of Vasilis Gkolemis’ work towards his PhD. For more information, check:
Apr 1, 2024 Our work (with Aristotelis Ballas) on Multi-Scale and Multi-Layer Contrastive Learning for Domain Generalization has been published at the IEEE Transactions on Artificial Intelligence! Article and preprint.
Mar 28, 2024 Congratulations to Ioannis Sarridis and all collaborators for making it to the top teams at the Face Recognition Challenge in the Era of Synthetic Data (FRCSyn)! As a result, we are happy to announce two publications:
  • P. Melzi et al., FRCSyn Challenge at WACV 2024: Face Recognition Challenge in the Era of Synthetic Data, WACV 2024
  • P. Melzi et al., FRCSyn-onGoing: Benchmarking and comprehensive evaluation of real and synthetic data to improve face recognition systems, Information Fusion, 2024
Mar 19, 2024 Thanks to the friends at the Stavanger University Hospital for inviting me to give the keynote speech on causal modeling for observational data analysis at the 2024 Annual meeting of the Norwegian National Network for Breast Cancer Research.
Mar 5, 2024 Last month I had the pleasure of
Jan 10, 2024 Our new project, MELIORA has just started! MELIORA is a collaboration between health scientists (including DND@HUA), ICT experts (including DIT@HUA), breast cancer patient representatives and other stakeholders to develop and evaluate “Multimodal Engagement and sustainable Lifestyle Interventions Optimizing breast cancer Risk reduction supported by Artificial intelligence”.
Dec 11, 2023 Today I had the opportunity to present our work on DALE, RHALE and RAM at the Department of Mathematics of the University of Patras. You can find the presentation slides here.
Oct 8, 2023 Vasileios Gkolemis presented our papers “Regionally Additive Models: Explainable-by-design models minimizing feature interactions” at the “Uncertainty Meets Explainability in Machine Learning” workshop at ECML-PKDD, and RHALE: Robust and Heterogeneity-aware Accumulated Local Effects at ECAI 2023.
Sep 28, 2023 The presentations from our “Uncertainty meets Explainability in Machine Learning” workshop are now available online.
Aug 5, 2023 We are happy to announce that our paper “Detection of Anomalies in Multivariate Time Series Using Ensemble Techniques” with A. Iliopoulos, J. Violos and I. Varlamis received the best paper award at the 2023 IEEE Big Data Service conference.
Jul 4, 2023 We will be hosting, along with Aristotelis Ballas, a tutorial session on Domain Generalization at this year’s IEEE Big Data Service conference. Edit: You can find the slides here
Jun 21, 2023 Today I gave an invited talk entitled “The promise and risks of Artificial Intelligence in healthcare: An introductory discussion”, at the Summer school: Health Communication & Health Inequalities Across the Health Professions in Greece & the U.S.
May 10, 2023 Vasileios Gkolemis and myself will be organizing the Uncertainty meets Explainability in Machine learning workshop in this year’s ECML-PKDD conference! Please check the CFP.
Apr 18, 2023 Our paper “Integrating nearest neighbors on neural network models for treatment effect estimation” with Niki Kiriakidou has been accepted for publication in the International Journal of Neural Systems! You may find a preprint in arxiv.
Feb 28, 2023 This semester I will be teaching a 6-week synchronous joint module with Rutgers University, along with my colleague, Matthew Matsagkanis! I am grateful to our students for their participation and for supporting this activity.
Jan 30, 2023 Today I gave an invited lecture to MSc students of Karolinska Institutet on digital health, big data analysis and AI in healthcare!
Jan 3, 2023 I will be giving a talk on Interpretable Machine Learning and the DALE method at the MeVer group at the Information Technologies Institute on Jan 04, 2023. Thanks to the colleagues at the MeVer group for the invitation! You may find the slides of the talk here
Nov 1, 2022 Our paper, DALE: Differential Accumulated Local Effects for efficient and accurate global explanations by V. Gkolemis, T. Dalamagas and myself has been accepted at ACML 2022!
Sep 2, 2022 New PhD position available on methods for quantifying and mitigating AI bias. Please check here for details (in Greek).
Sep 1, 2022 Please find pre-prints of our recent papers that will appear on SETN 2022 and IEEE Big Data Service and the Computing in Cardiology conference proceedings.