I’m a developer at Athena Research Center, Athens, working on AI explainability and Fairness in European Horizon projects. My journey is rooted in Python, with a focus on data science and machine learning—especially in making AI systems transparent, interpretable, and ethical.
- Explainability & Fairness:
Designing methods and tools to make machine learning models understandable and fair. - European Horizon Projects:
Collaborating across Europe to advance responsible AI in real-world applications.
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FALE: Fairness-Aware ALE Plots
Visualizing and understanding model fairness with ALE plots. -
GLANCE: Global Actions in a Nutshell for Counterfactual Explainability
Intuitive global counterfactual explanations for ML decisions. -
FACTS: Fairness-Aware Counterfactuals for Subgroups
Counterfactual analysis targeting fairness across subgroups. -
GLOVES
A tool for evaluating global explanations in ML.
Explore my research and publications on Google Scholar.