Topic: research

From 9-15 February 2026, the University of Tartu will host a themed week to celebrate the "Women in Science" day. During this week, we aim to highlight the work and achievements of our researchers.

Radwa El Shawi shares her journey and research at the University of Tartu, where she focuses on democratizing machine learning to make AI more accessible, explainable, and human-centered.

15. jaanuaril 2026 kaitses Marharyta Domnich oma doktoritöö „Inimkesksete kontrafaktuaalsete seletuste arendamine seletatavas tehisintellektis“. Tema juhendajad olid Raul Vicente Zafra ja Eduard Barbu

From 9-15 February 2026, the University of Tartu will host a themed week to celebrate the "Women in Science" day. During this week, we aim to highlight the work and achievements of our researchers.

Mohamed Abdelrahman shares his journey as a PhD student in the Data Systems Group at the University of Tartu, where he focuses on Automated Machine Learning (AutoML) and aims to make AI more trustworthy and accessible. His story was introduced by Professor Jaak Vilo, Head of the Institute of Computer Science.

On January 20 at 11:00 Heidi Taveter will defend her doctoral thesis "Using programming-process data of introductory programming courses: finding solver types, giving feedback, and detecting plagiarism" to obtain the degree of Doctor of Philosophy (in Computer Science).

On 13 January at 10:00 Viacheslav Komisarenko will defend his doctoral thesis “Aligning Training Loss to Evaluation Metrics in Deep Learning“.

Researchers at the University of Tartu Institute of Computer Science, Junior Research Fellow of Artificial Intelligence Joonas Ariva and Associate Professor in Artificial Intelligence Dmytro Fishman, together with radiologists from Tartu University Hospital and engineers at Better Medicine, have developed an AI-based tool that accelerates the detection of kidney cancer. Its effectiveness was validated in a study published in Nature Communications Medicine.

On 15 January Marharyta Domnich will defend her doctoral thesis "Advancing human-centric counterfactual explanations in explainable AI“