Mathematical Sciences
Our long history of research has had an enduring impact on computer science, operations research, and information theory. We’re currently focused on optimization, probability, complexity, geometry of data, as well as linear and multi-linear algebra, to deliver tools that are fundamental to big data and AI.
Our work
DOFramework: A testing framework for decision optimization model learners
Technical noteOrit DavidovichNew tensor algebra changes the rules of data analysis
ResearchLior Horesh7 minute readRalph Gomory receives the Vannevar Bush Award: The pioneer of applied math
NewsKatia Moskvitch10 minute readIBM-Stanford team’s solution of a longstanding problem could greatly boost AI
ResearchMark Squillante and Soumyadip Ghosh6 minute read
Publications
POKE: A Compact and Efficient PKE from Higher-dimensional Isogenies
- Andrea Basso
- Luciano Maino
- 2025
- Eurocrypt 2025
Dense Associative Memory with Epanechnikov energy
- Benjamin Hoover
- Krishnakumar Balasubramanian
- et al.
- 2025
- ICLR 2025
Text-Guided Few-Shot Semantic Segmentation with Training-Free Multimodal Feature Matching
- Guillaume Buthmann
- Tomoya Sakai
- et al.
- 2025
- ICASSP 2025
Epigraph Based Multilevel Optimization (EMO) for Enhancing Chain-of-Thought Reasoning Capabilities
- Songtao Lu
- Yanna Ding
- et al.
- 2025
- ICASSP 2025
On Representations of Mean-Field Variational Inference
- Soumyadip Ghosh
- Yingdong Lu
- et al.
- 2025
- Journal of Applied Analysis
On The Variance of Schatten 𝑝-Norm Estimation with Gaussian Sketching Matrices
- Lior Horesh
- Vasileios Kalantzis
- et al.
- 2025
- Monte Carlo Methods Appl.