Personal profile
About Me
I am an assistant professor at the department of computer science at Bar Ilan university. I received a Ph.D. in statistics from Yale University in 2017, under the supervision of prof. Ronald Coifman (math), prof. Sahand Negahban (statistics) and prof. Yuval Kluger (computational biology). Between my graduation and 2023,1 was an assistant professor adjunct at the center for outcome research and evaluation at Yale university. Before and after my Ph.D. studies I worked for several years in the industry in various research, algorithms design and advisory board roles. Apart of my academic endeavors, until very recently I was also a commander of an infantry battalion in reserves in the Israeli Defense Force, and I am an amateur jazz pianist. When time permits, I also like to run marathons.
My full CV is available here.
Research Interests:
My main area of interest is in developing methods for machine learning. In particular, a primary focus of mine lies in development of unsupervised learning tools for understanding data, its latent properties, learning useful representation for it and extraction of meaningful information from it. During the last ten years, my primary technical playground is deep learning, although I have also performed research in other areas of machine learning. Whenever possible, I aim to base my work on a solid mathematical and theoretical basis, and to contribute to the theoretical understanding of machine learning and deep learning. Alongside my contributions to unsupervised learning, I have also contributed to supervised learning, in both theoretical and practical aspects.
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Collaborations and top research areas from the last five years
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A Harmonic-Mean Formulation of Average-Reward Reinforcement Learning in SMDPs
Shtossel, E., Vidler, A., Shaham, U. & Kaminka, G. A., 2026, Proceedings of the AAMAS Workshop on Adaptive and Learning Agents (ALA).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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PRISM: PRIor from corpus Statistics for topic Modeling
Ishon, T., Goldberg, Y. & Shaham, U., 2026, In: Transactions on Machine Learning Research. 2026-MarchResearch output: Contribution to journal › Article › peer-review
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Generalizable and Robust Spectral Method for Multi-view Representation Learning
Yacobi, A., Lindenbaum, O. & Shaham, U., 2025, In: Transactions on Machine Learning Research. 2025-AprilResearch output: Contribution to journal › Article › peer-review
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Generalizable Spectral Embedding with an Application to UMAP
Ben-Ari, N., Yacobi, A. & Shaham, U., 2025, In: Transactions on Machine Learning Research. July-2025Research output: Contribution to journal › Article › peer-review
1 Scopus citations -
P-CAFE: Personalized Cost-Aware Incremental Feature Selection for Electronic Health Records
Kashani, N., Cohen, M. & Shaham, U., 21 Oct 2025, ECAI 2025 - 28th European Conference on Artificial Intelligence, including 14th Conference on Prestigious Applications of Intelligent Systems, PAIS 2025 - Proceedings. Lynce, I., Murano, N., Vallati, M., Villata, S., Chesani, F., Milano, M., Omicini, A. & Dastani, M. (eds.). IOS Press BV, p. 3403-3410 8 p. (Frontiers in Artificial Intelligence and Applications; vol. 413).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Open Access
Activities
- 1 Oral presentation
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A Harmonic Mean Formulation of Average Reward Reinforcement Learning in SMDPs
Shtossel, E. (Speaker), Shaham, U. (Speaker), Vidler, A. (Speaker) & Kaminka, G. (Speaker)
26 May 2025Activity: Talk or presentation › Oral presentation
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