Principal Members

The Analysis + Data group is led by seven mathematical scientists: Bala Krishnamoorthy, Haijun Li, Charles Moore, Alexander Panchenko, and Kevin Vixie, Matt Sottile and Yuan Wang. We are focused on theory and applications: analysis for its own sake, and the study of data analysis challenges with special interest in the interface between data analysis and mathematical analysis.

The group was formed in the spring of 2014.


Bala Krishnamoorthy


Bala is an expert in optimization, computational topology, intersections of these with analysis and a very wide range of applications.

Link to Bala’s Analysis+Data Webpage here
Link to Bala’s WSU webpage here

Haijun Li


Haijun is a probabilist with wide ranging interests. His current, main interest isĀ  high-dimensional risk analysis, which is at the intersection of probability, statistics, game theory and optimization.
Link to Haijun’s Analysis + Data Webpage here
Link to Haijun’s WSU webpage here

Charles Moore


Moore was originally trained in the UCLA analysis group after which he spent many years at Kansas State University. His interests include harmonic analysis, PDE and probability.

Link to Charles’ Analysis + Data webpage here
Link to Charles’ WSU webpage here

Alexander Panchenko


Alex explores the intersection of nonlinear analysis and physics for ideas to exploit for a wide range of mathematical challenges.

Here is a link to Alexander’s Analysis + Data webpage: link
Here is a link to Alexander’s WSU webpage: link

Matt Sottile


Matt Sottile is a computer scientist and applied mathematician interested in a variety of areas ranging from functional languages and domain specific languages to image analysis and statistics. He is the founder of Sailfan Research, a data science company in Portland, Oregon, an adjunct faculty member of the WSU EECS department and a principal Scientist at Galois, also in Portland, Oregon.

Link to Matt’s Analysis + Data Webpage here
Link to Matt’s webpage here

Kevin R. Vixie


Kevin came to analysis through an interest in data analysis and inverse problems. His chance meeting with David Caraballo in a short course on nonlinear control theory had a deep and lasting impact; not only did David and Kevin become friends, Kevin was also drawn into David’s area of geometric measure theory. Studying Evans and Gariepy’s Measure Theory and Fine Properties of Functions, working with Bill Allard, leading a team exploiting analysis for data challenges and a host of other influences have all been very important to the formation of his current perspective and focus.

Link to Kevin’s Analysis + Data Webpage here
Link to Kevin’s CGAD Webpage hereĀ 

Yuan Wang


Yuan is a statistical working on the analysis of complex data objects including images, curves, and trees for regression, classification, and prediction. She also works in wireless communication system design and passive radar network.

Link to Yuan’s Analysis + Data webpage: link
Here is a link to Yuan’s WSU webpage: link