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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 note
Orit Davidovich
02 Feb 2023
New tensor algebra changes the rules of data analysis
Research
Lior Horesh
08 Jul 2021
7 minute read
Ralph Gomory receives the Vannevar Bush Award: The pioneer of applied math
News
Katia Moskvitch
18 May 2021
10 minute read
- Mathematical Sciences
- Quantum
IBM-Stanford team’s solution of a longstanding problem could greatly boost AI
Research
Mark Squillante and Soumyadip Ghosh
16 Dec 2020
6 minute read
- Mathematical Sciences
- Neuro-symbolic AI

Publications

Stable iterative refinement for solving linear systems with inaccurate computation
- - Chai Wah Wu
  - Mark Squillante
  - et al.
- 2026
- J. Comput. Appl. Math.
Modern Methods in Associative Memory
- - Dmitry Krotov
  - Benjamin Hoover
  - et al.
- 2025
- ICML 2025
POKE: A Compact and Efficient PKE from Higher-dimensional Isogenies
- - Andrea Basso
  - Luciano Maino
- 2025
- Eurocrypt 2025
Integer Programming Based Methods and Heuristics for Causal Graph Learning
- - Sanjeeb Dash
  - Joao Goncalves
  - et al.
- 2025
- AISTATS 2025
Hybrid Bayesian Optimization with DIRECT
- - Hongsheng Liu
  - Dzung Phan
- 2025
- SDM 2025
Convergence-Guaranteed Elastic Net Graphical Model Estimation with Applications to Anomaly Localization
- - Dzung Phan
  - Matt Menickelly
  - et al.
- 2025
- SDM 2025

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