Math’s Mayya Zhilova Gets Early CAREER Boost from National Science Foundation

Award-winning plan will study challenging problems in contemporary statistics and data science, and includes mentorship and educational activities for junior researchers and high school students.

March 7, 2021

An assistant professor in the School of Mathematics is receiving a 2021 National Science Foundation Faculty Early Career Development Program (NSF CAREER) Award for research into promising aspects of statistical analysis, and for her outreach and mentorship plans for students and high schoolers from underrepresented communities.

Mayya Zhilova’s NSF project, “New Challenges in High-Dimensional and Nonparametric Statistics,” will “address challenging open questions in high-dimensional and nonparametric statistics motivated by practical applications in finance, engineering, and life sciences,” as Zhilova writes in her abstract.

Contemporary problems concerned with analysis of complex and high-dimensional data sets require to address numerous questions about fundamental concepts in statistics, data science, and related fields. This is particularly relevant for high-dimensional and nonparametric statistics. In high-dimensional statistics, one studies problems involving data sets with a large complexity or dimensionality that can be much larger than an amount of available information. Methods that are used in nonparametric statistics typically impose much weaker assumptions on a statistical model than the parametric statistics does. In general, this leads to a smaller modeling error and to a broader range of applications, or real-life problems, where these methods can be used. 

Zhilova adds in her abstract: “The project is focused on development of new methods of statistical inference for complex data sets providing high accuracy and explicit theoretical guarantees. This includes (i) development of a novel framework for statistical inference that will considerably extend the range of applicability of some of the major statistical methods; (ii) studies of performance of resampling methods in a high-dimensional framework; and (iii) studies of intrinsic properties of high-dimensional models that ensure good performance of the statistical methods.”

The educational aspect of Zhilova’s NSF CAREER project includes mentorship of graduate and undergraduate students, summer camps in statistics and data science for STEM-oriented high school students, and a workshop/graduate school offering on high-dimensional statistics and learning theory for junior researchers. Zhilova notes that special attention will be given to supporting students and researchers from underrepresented minorities.

The NSF CAREER Program is one of the Foundation’s most prestigious awards in support of early-career faculty who have the potential to serve as academic role models in research and education, and to lead advances in the mission of their department or organization. The NSF notes that activities pursued by early-career faculty recipients should build a firm foundation for a lifetime of leadership in integrating education and research.

Zhilova began work at the School of Mathematics at Georgia Tech in 2016, and is an affiliate faculty member of the Center for Machine Learning at Georgia Tech and the Transdisciplinary Research Institute for Advancing Data Science (TRIAD). Before coming to Atlanta, Zhilova was a researcher at the Weierstrass Institute for Applied Analysis and Stochastics, and at the School of Business and Economics at the Humboldt University of Berlin. She received her M.S. from the Lomonosov Moscow State University, and her Ph.D. from the Humboldt University of Berlin.

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Renay San Miguel
Communications Officer II/Science Writer
College of Sciences