About

I am a PhD student at the University of Helsinki advised by Teemu Roos. My research interests are broadly in machine learning and information retrieval. I have served as a reviewer for NeurIPS/ICLR/ICML/AISTATS/UAI.

In the past, I worked on ML systems with Tianqi Chen at Carnegie Mellon University in Pittsburgh, US, and on information retrieval methods at iKVA in Cambridge, UK. I received my BSc and MSc degrees in Computer Science from the University of Helsinki, during which I also worked on information theory and graphical models.

Selected Publications

E. Jääsaari, V. Hyvönen, M. Ceccarello, T. Roos, M. Aumüller. VIBE: Vector Index Benchmark for Embeddings. arXiv:2505.17810. [pdf] [code]

E. Jääsaari, V. Hyvönen, T. Roos. LEMUR: Learned Multi-Vector Retrieval. ICML 2026. [pdf] [code]

E. Jääsaari, V. Hyvönen, T. Roos. LoRANN: Low-Rank Matrix Factorization for Approximate Nearest Neighbor Search. NeurIPS 2024. [pdf] [code]

V. Hyvönen, E. Jääsaari, T. Roos. A Multilabel Classification Framework for Approximate Nearest Neighbor Search. Journal of Machine Learning Research 25(46):1–51 (JMLR, 2024). [pdf] [code]

V. Hyvönen, E. Jääsaari, T. Roos. A Multilabel Classification Framework for Approximate Nearest Neighbor Search. NeurIPS 2022. [pdf] [code]

T. Silander, J. Leppä-aho, E. Jääsaari, T. Roos. Quotient Normalized Maximum Likelihood Criterion for Learning Bayesian Network Structures. AISTATS 2018. [pdf]

E. Jääsaari, J. Leppä-aho, T. Silander, T. Roos. Minimax Optimal Bayes Mixtures for Memoryless Sources over Large Alphabets. ALT 2018. [pdf]