Sep 11, 2026|PhD and PostDoc Positions
I am hiring PhD students and Post-doctoral researchers in Helsinki Finland, through the ELLIS Institute Finland call. Please reach out if you are interested to join ELLIS and Uniarts Helsinki.
News
Sep 02, 2026|ELLIS Institute Finland
recruits 7 new principal investigators, and I am one of them! The institute is now grown to 52 professor in various areas of machine learning and artificial intelligence.
Sep 02, 2026|Uniarts Helsinki
released this lovely news post: https://www.uniarts.fi/en/articles/news/kivanc-tatar-appointed-professor-of-digital-arts-at-the-uniarts-helsinki-research-institute/.
Aug 28, 2026|New position in Finland
I am starting a new position in Helsinki as a Full Professor in Digital art with emphasis on AI and Co-Creativity at University of the Arts Helsinki (Uniarts Helsinki), which is one of the largest arts universities in Europe. Excitingly, this position also have a second affiliation, as a PI position at ELLIS Institute Finland located at Aalto University.
Aug 26, 2026|New website
New website is up! It has better project tagging, although it is still not populated in blog and press pages, and some issues in publications listing.
Mar 15, 2026|Docent Lecture
I am giving my docent lecture as the final step of my promotion to Associate Professor on March 20th, 2026 at 13:00 at the Analysen Room in the EDIT building, at Chalmers Johanneberg Campus.
Selected current projects
View all projects
Recent publications
View bibliographyARIA: A Diagnostic Framework for Music Training Data Attribution
Han, C., Panahi, A., and Tatar, K. 2026. ARIA: A Diagnostic Framework for Music Training Data Attribution. arXiv. arXiv:2605.16181 [cs.SD]. DOI:10.48550/arXiv.2605.16181.
Madaghiele, V., Lund, L., Holzer, D., Kelkar, T., Tatar, K., and Holzapfel, A. 2026. Expanding the machine: Notating generative synthesis with a state-based representation and a navigable timbre space. Organised Sound. DOI:10.1017/S1355771825100915.
Liu, H. X. and Tatar, K. 2026. Grounding Machine Creativity in Game Design Knowledge Representations: Empirical Probing of LLM-Based Executable Synthesis of Goal Playable Patterns under Structural Constraints. arXiv. arXiv:2603.07101 [cs]. DOI:10.48550/arXiv.2603.07101.
Mage: Multi-Axis Evaluation of LLM-Generated Executable Game Scenes Beyond Compile-Pass Rate
Liu, H. X. and Tatar, K. 2026. Mage: Multi-Axis Evaluation of LLM-Generated Executable Game Scenes Beyond Compile-Pass Rate. arXiv. arXiv:2605.07342 [cs.LG]. DOI:10.48550/arXiv.2605.07342.