Who are we?

Note: please make sure to include the group mailing list in all correspondence rather than contacting individual members directly.


Indraneel Kasmalkar

Interests: Numerical Methods, Functional Analysis, Computational Cognitive Science

Xiaotong Suo

Interests: Statistics, Machine Learning

Anjan Dwaraknath

Interests: Numerical Linear Algebra, Optimization, Partial Differential Equations

Brad Nelson

Interests: Numerical Linear Algebra, Structured Matrices, Partial Differential Equations, Fast Algorithms for Scientific Computing

Austin Benson

Interests: Distributed Scientific Computing, Discrete Math

Nolan Skochdopole

Interests: Discrete Math, Complexity Theory, Graph Theory, Algorithms

Victor Minden

Interests: Scientific Computing, Linear Algebra, Optimization

Current Leadership

Ron Estrin

Interests: Numerical Linear Algebra, Optimization


Reza Zadeh

Reza Zadeh focuses on discrete applied mathematics, machine learning theory and applications, and large-scale distributed computing. He has built large-scale distributed algorithms for the singular value decomposition on Spark, built the machine learning behind Twitter's who-to-follow system, and created other large-scale distributed machine learning systems.

Stanford website

Margot Gerritsen

Margot Gerritsen's main interest is the design and analysis of efficient numerical solution methods for partial differential equations that arise in fluid dynamics. Her PhD thesis work emphasized mathematical techniques. Since, her focus has shifted to using such techniques for actual engineering applications.

Stanford Engineering profile

Michael Saunders

Saunders develops mathematical methods for solving large-scale constrained optimization problems and large systems of equations. He also implements such methods as general-purpose software to allow their use in many areas of engineering, science, and business. He is co-developer of the large-scale optimizers MINOS, SNOPT, SQOPT, PDCO and the linear equation solvers SYMMLQ, MINRES, MINRES-QLP, LSQR, LSMR, and LUSOL.

Stanford Engineering profile