I hold a 4-year diploma in Computer Science and 2-year Master of Science in Statistical Science both from Athens University of Economics and Business and a PhD from University of Cambridge, MRC-Biostatistics Unit supervised by Professor Sylvia Richardson. The topic of my doctoral thesis is probabilistic machine learning, and, more precisely, towards using generative modelling in healthcare.

I am very happy to be a postdoctoral associate with The Broad Institute of M.I.T. and Harvard holding an Eric and Wendy Schmidt Center Research Scholarship.

Since the spring semester of 2020 I have also been a visiting researcher at Professor Costis Daskalakis' group at CSAIL, MIT after being granted the 2020 Trinity College, University of Cambridge award in Mathematics.

In parallel to that, from April till October 2022, I was working with Professor Carola Schönlieb , on a research project of mine at CMIH , DAMTP , University of Cambridge.

Prior to pursuing a PhD, I was a research associate (2014-2016) at two EU funded research projects at Athens University of Economics and Business and Technical University of Crete. The aim of my research during these projects, was causal inference through the lens of Information Theory and Bayesian theory and methodology with application to economics and computational biology.

The focus of my MSc thesis was on "Context Tree Weighting for Signal Processing, Bayesian Inference and Model Selection: Theory and Algorithms", a topic that lies at the intersection of Information Theory and Bayesian statistics, under the insightful supervision of Professor Petros Dellaportas. I was very honoured to have the extension of my MSc thesis "Bayesian context trees: Modelling and exact inference for discrete time series" being accepted and published by the Journal of the Royal Statistical Society, Series B (methodology)

During my undergraduate studies, I was delighted to explore the essentials of theoretical computer science namely algorithmic complexity, logic, computability, algorithmic game theory and information theory.

My fields of interest lie in the underpinnings, theory and methodology of machine intelligence, Bayesian inference, theoretical computer science and information theory with applications to healthcare.

September 2023 onwards I will be joining The Broad Institute of MIT and Harvard to work with an extraordinary set of Researchers, namely Professor Constantinos Daskalakis, Professor Caroline Uhler and Doctor Anthony Phillipakis

Contribution to society:

• Founder and chair of {Dis}Ability in AI and founder and secretary of  Women in Data Science and Statistics (RSS special interest group);
• ACM Transactions on Probabilistic Machine Learning member of the editorial board (2023- present);
• Accessibility Chair of ICML (2021-present);
• Diversity, Inclusion and Accessibility Chair of NeurIPS (2021);
• Social Chair of NeurIPS (2019-2020);
• Reviewer at: Journal I.E.E.E. Transactions On Information Theory (2016- present), Journal I.E.E.E. Transactions On Signal Processing (2018- present), Journal Entropy (2020-present), European Journal of Applied Mathematics (2021- present), Workshop of Women in Machine Learning (2018- present), I.E.E.E. International Symposium on Information Theory (2019- present), International Conference on Machine Learning (2020- present), Neural Information Processing Systems (2020- present), Journal of the Royal Statistical Society, Series B (2022- present), Statistics and Computing (2022- present), Nature Computational Science (2023- present)
• Originator and organiser of several workshops in my field (eg " Advances and Challenges in Machine Learning Languages")