Texas A&M statistician Irina Gaynanova has been selected to receive the American Statistical Association’s 2018 David P. Byar Young Investigator Award, presented by the ASA Biometrics Section to honor the top original manuscript submitted by a new researcher for presentation at the Joint Statistical Meetings.
The annual award commemorates David Byar, a renowned biostatistician who made significant contributions to the development and application of statistical methods, in addition to mentorship of junior researchers, during his career at the National Cancer Institute. Gaynanova’s first-place paper, which addresses collaborative research with Columbia University’s Gen Li, is titled “Structural Learning and Integrative Decomposition of Multi-View Data.”
Gaynanova, an assistant professor of statistics who joined the Texas A&M Department of Statistics in 2015, will be presented with the award at the ASA Biometrics Section’s reception at the Joint Statistical Meetings 2018, set for July 28 through August 2 in Vancouver. As the 2018 recipient, she will receive $1,000 to offset the cost of presenting her paper during a Biometrics Section sponsored-topic-contributed session at JSM 2018 as well as an additional $1,000 prize from the section.
Gaynanova’s research interests converge at the intersection of applied, computational and theoretical statistics — specifically, high-dimensional data analysis, machine learning, multivariate analysis, computational statistics and statistical methods for analyzing biological data. In general, she seeks to develop new statistical methodology that is both computationally efficient and theoretically sound in order to help solve challenging problems across a broad range of disciplines.
A member of the ASA as well as the Institute of Mathematical Statistics, Gaynanova has worked on a variety of applied problems thus far in her career, including classification of leukemia patients based on DNA methylation profiles, control of false discovery rates in sample size calculations and study of antibiotic molecular actions based on the metabolic profiles. Since 2017, she has served as principal investigator on a three-year National Science Foundation grant to study scalable methods for classifying heterogeneous high-dimensional data.
“Dr. Gaynanova has been involved in a variety of prominent projects involving high-dimensional inference,” said Dr. Valen E. Johnson, professor and head of Texas A&M Statistics. “This award recognizes her outstanding contributions for the analysis of multi-view data, or data collected on the same subject using different sources. Such data has become increasingly common in a numerous fields, including such diverse areas as genomics, neurosciences and wearable technologies. The methodology exposed in her article with Gen Li is likely to have very broad application.”
Gaynanova received both her master’s of science (2013) and Ph.D. in statistics (2015) from Cornell University after earning a master’s in science with honors in applied mathematics and computer science from Lomonosov Moscow State University (2004). She also spent an exchange semester studying applied mathematics at Technical University of Munich in 2007-2008. During her time at Cornell, Gaynanova served as a statistical consultant assisting students and faculty with statistics-related issues as well as a research assistant developing statistical methods for analysis of biological data.
Gaynanova’s private sector experience in Moscow prior to coming to Cornell included yearlong stints as a senior specialist in the Balancing Marketing Division of the OJSC Trading System Administration, where she monitored the Russian wholesale electricity and power balancing market and performed quality control (2009-2010) and as a junior statistician in the Census Division responsible for survey design, census data analysis, error rate estimation and quality control performance (2008-2009).
Click here to learn more about Gaynanova and her teaching, research and professional service.
For additional information about the American Statistical Association or the Biometrics Section, go to http://www.amstat.org/.
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Contact: Shana K. Hutchins, (979) 862-1237 or email@example.com or Dr. Irina Gaynanova, (979) 845-3141 or firstname.lastname@example.org