Note: please make sure to include the group mailing list in all correspondence rather than contacting individual members directly.
Indraneel KasmalkarInterests: Numerical Methods, Functional Analysis, Computational Cognitive Science 

Xiaotong SuoInterests: Statistics, Machine Learning 

Anjan DwaraknathInterests: Numerical Linear Algebra, Optimization, Partial Differential Equations 

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

Austin BensonInterests: Distributed Scientific Computing, Discrete Math 

Nolan SkochdopoleInterests: Discrete Math, Complexity Theory, Graph Theory, Algorithms 

Victor MindenInterests: Scientific Computing, Linear Algebra, Optimization 
Ron EstrinInterests: Numerical Linear Algebra, Optimization 
Reza ZadehReza Zadeh focuses on discrete applied mathematics, machine learning theory and applications, and largescale distributed computing. He has built largescale distributed algorithms for the singular value decomposition on Spark, built the machine learning behind Twitter's whotofollow system, and created other largescale distributed machine learning systems. Stanford website 

Margot GerritsenMargot 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 SaundersSaunders develops mathematical methods for solving largescale constrained optimization problems and large systems of equations. He also implements such methods as generalpurpose software to allow their use in many areas of engineering, science, and business. He is codeveloper of the largescale optimizers MINOS, SNOPT, SQOPT, PDCO and the linear equation solvers SYMMLQ, MINRES, MINRESQLP, LSQR, LSMR, and LUSOL. Stanford Engineering profile 