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
Spline Quantile Regression
- Ta-hsin Li
- Nimrod Megiddo
- 2025
- arXiv
Sequential Uncertainty Quantification with Contextual Tensors for Social Targeting,
- Ide-San Ide
- Keerthiram Murugesan
- et al.
- 2024
- KAIS
Throughput-Optimal Scheduling via Rate Learning
- Panagiotis Promponas
- Victor Valls
- et al.
- 2024
- CDC 2024
Top-Down Finer-Scale CO2 Emission Across Nations
- 2024
- AGU 2024
WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models
- Jinghan Jia
- Jiancheng Liu
- et al.
- 2024
- NeurIPS 2024
Dense Associative Memory Through the Lens of Random Features
- Benjamin Hoover
- Duen Horng Chau
- et al.
- 2024
- NeurIPS 2024