LLNL’s Kamath honored as 2023 SIAM fellow

The Society for Industrial and Applied Mathematics (SIAM), the world’s premier professional organization for applied mathematicians and computational scientists, has selected Lawrence Livermore National Laboratory research staff member Chandrika Kamath as a member of the SIAM fellows class of 2023.  

The prestigious fellow designation is a lifetime honorific title and honors SIAM members who have made outstanding contributions to fields served by the organization. Fellows are nominated by SIAM members and chosen annually by a 16-member selection committee.

“When I changed my field from parallel numerical algorithms to scientific data mining over 25 years ago, I wasn't sure how it would turn out; I have since worked on many interesting and challenging problems,” Kamath said. “Finding solutions and learning multiple disciplines in the process has been its own reward. Being selected a SIAM fellow is icing on the cake. I am honored, and grateful to all those who supported me along the way.”

Kamath has worked at LLNL since 1997, where she specializes in analyzing data from scientific simulations, experiments and observations. An expert in data mining, Kamath also has led projects analyzing uncertainty in additive manufacturing, improving large-scale data exploration and analysis, integrating wind energy on the power grid and on intelligent reduction of data from exascale simulations. Her expertise includes image and video processing, feature extraction, dimension reduction, pattern recognition, high performance computing and machine learning. Kamath’s current focus is on techniques for sampling and surrogate modeling, especially for small data sets in high dimensions.

"I am thrilled to have Chandrika honored in this way for her stellar career” said Bruce Hendrickson, LLNL’s associate director for Computing. “She has been a pioneer and leader in embracing data science for scientific and engineering applications.”

At LLNL, Kamath served as project lead and contributor for Sapphire, a project to develop scalable algorithms for the interactive exploration of large, complex multi-dimensional scientific data. The Sapphire team won an R&D 100 award in 2006.

Kamath is among the top 2% of the most cited researchers worldwide throughout their careers, according to Stanford University. She holds six patents in data mining and  organized various data mining workshops and conferences, including the SIAM Conference on Data Mining, where she served as the chair of the conference’s steering committee from 2007-2014. Her book, "Scientific Data Mining: A Practical Perspective," was published by SIAM in 2009. She also is one of the three founding editors-in-chief of the Wiley journal, Statistical Analysis and Data Mining, where she focused on the practical applications of data analysis techniques.

Prior to joining LLNL, Kamath was a consulting software engineer at Digital Equipment Corporation, developing high-performance mathematical software. She holds a Ph.D. and masters’ degree in computer science from the University of Illinois at Urbana-Champaign and earned her bachelor’s degree in electrical engineering from the Indian Institute of Technology in Bombay.

SIAM, the world’s largest scientific society devoted to applied mathematics, comprises more than 14,000 computational mathematicians, computer scientists, numerical analysts, engineers, statisticians, physicists, educators and students from more than 100 countries.

The goals of the fellows program are to honor SIAM members recognized by their peers as distinguished for their contributions to the discipline, to help make outstanding SIAM members more competitive for awards and honors, and support the advancement of SIAM members to leadership positions in their own institutions and in the broader society, according to the organization’s website.

For more, visit the website. See the announcement.