Research output per year
Research output per year
Organization profile
Organization profile
The Institute for Interdisciplinary Computational Science is an innovative research center that brings together scholars from diverse fields. The Institute conducts research which builds bridges between computer science, informatics, and other disciplines such as healthcare, medicine, biology, neuroscience, physics, mathematics, psychology, operations research, economics, humanities, and more. The Institute views cross-disciplinary collaboration as essential for progress, fostering a culture of joint research, methodological innovation, and knowledge sharing, with the aim of building a leading community in interdisciplinary computational science and promoting responsible, innovative uses of computation for the benefit of society at large.
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
Profiles
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Eitan Bachmat
- Institute for Interdisciplinary Computational Science - Full Professor, Institute Director
Person: Academic, Administrative
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Danny Barash
- Institute for Interdisciplinary Computational Science - Full Professor
- Statistics and Data Analysis Program - Member
Person: Academic
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Noam Barda
- Department of Epidemiology, Biostatistics and Community Health Sciences - Associate Professor
- Institute for Interdisciplinary Computational Science - Associate Professor
- Statistics and Data Analysis Program - Member
Person: Academic
Research output
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The determinant of the adjacency matrix of a quaternion unit gain graph
Kyrchei, I. I., Treister, E. & Pelykh, V. O., 1 Jan 2026, In: Discrete Mathematics. 349, 1, 114659.Research output: Contribution to journal › Article › peer-review
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Understanding and Improving Laplacian Positional Encodings for Temporal GNNs
Galron, Y., Frasca, F., Maron, H., Treister, E. & Eliasof, M., 1 Jan 2026, Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Proceedings. Ribeiro, R. P., Jorge, A. M., Soares, C., Gama, J., Pfahringer, B., Japkowicz, N., Larrañaga, P. & Abreu, P. H. (eds.). Springer Science and Business Media Deutschland GmbH, p. 420-437 18 p. (Lecture Notes in Computer Science; vol. 16014 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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Zero-Shot Detection of LLM-Generated Code via Approximated Task Conditioning
Ashkenazi, M., Brenner, O., Shohet, T. F. & Treister, E., 1 Jan 2026, Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Proceedings. Ribeiro, R. P., Pfahringer, B., Japkowicz, N., Larrañaga, P., Jorge, A. M., Soares, C., Abreu, P. H. & Gama, J. (eds.). Springer Science and Business Media Deutschland GmbH, p. 187-204 18 p. (Lecture Notes in Computer Science; vol. 16016 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Projects
- 1 Active
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NSF-BSF: Scalable Graph Neural Network Algorithms and Applications to PDEs
Treister, E. (PI) & Ruthotto, L. (CoPI)
United States-Israel Binational Science Foundation (BSF)
1/01/23 → …
Project: Research