I'm an AI Researcher

Focusing on AI Ethics, Fairness and Explainability

ABOUT

Explainable models are easier to supervise, they are better for users, and they can even help humans learn new things.

I wish to do my part in creating more society-friendly AI models.

RESUME

PhD on Explainability and Fairness in AI

Work under the supervision of Jakub Mareček and Tomáš Pevný.

Notable Publications

Jiří Němeček, Mark Kozdoba, Illia Kryvoviaz, Tomáš Pevný, Jakub Mareček. Bias Detection via Maximum Subgroup Discrepancy KDD 2025.

Jiří Němeček, Tomáš Pevný, Jakub Mareček. Generating Likely Counterfactuals Using Sum-Product Networks. ICLR 2025.

Master in Artificial Intelligence

Graduated with honors

Thesis on the Use of Mixed-Integer Programming in Machine Learning, with a focus on Explainability.
Excelling studies

Great overall results, with an average mark of 1.08 (1 is best).

Top placements in class contests on deep learning as well as non-polynomial optimization.
3 Minors

Minors in Computer Vision and Data Science, plus the selective prg.ai minor for top AI students in Prague.
Ethics studies

Courses on Ethics and AI security at Charles University, course on Research Ethics at Warsaw University of Technology.
Explainable AI research

Research work on Explainable AI under Jakub Mareček.

MAMA AI2021 - 2022

AI developer

Helped develop text-to-speech systems in a startup led by people from the IBM’s Watson project.

Volunteer AI instructor

Volunteer instructor for the Czech version of an introductory course on AI for public.

Bachelor in Knowledge Engineering

Graduated with honors

Thesis about Evolutionary algorithms used to train Neural Networks.

Great overall results, with an average mark of 1.18 (1 is best).
Various top placements in extra-curricular competitions.
Initial research work

Volunteer research help to Jan Šochman with neuronal activity simulation research.

CONTACT