Two College of Science faculty have been selected as 2021 recipients of the National Science Foundation Faculty Early Career Development (CAREER) Award, a prestigious honor intended to help kick-start the careers of promising junior faculty members.
Dr. Irina Gaynanova, assistant professor of statistics, and Dr. Matthias S. Maier, assistant professor of mathematics, are the first investigators to receive the coveted accolade this year within the college, which has seen 10 of its researchers recognized since 2017, according to Texas A&M Science administrators and NSF online awards database records.
Gaynanova’s proposal, titled “Next-Generation Methods for Statistical Integration of High-Dimensional Disparate Data Sources” and funded at a projected total amount of $400,000 for the next five years through the Division of Mathematical Sciences’ Statistics Program, will develop a robust framework suitable for integrating, matching, aggregating and assessing multi-view data, or data collected on the same subject using different sources, primarily multi-omics and wearable technologies. Such data generated by the countless devices that dominate our daily lives has become increasingly common in and critical to myriad multidisciplinary areas, including genomics, neuroscience and biotechnology.
Maier’s proposal, titled “Robust and High-Performance Computational Methods for Simulating Metamaterial-Based Optical Devices,” will be funded through the Division of Mathematical Sciences’ Computational Mathematics Program at $470,414 for the next five years. He will use novel computational approaches to simulate metamaterial-based optical devices and optical geometries to manipulate light on a microscopic scale in research that will enable the broader scientific community to perform direct numerical simulations of optical devices and help bridge the gap between physical theory and optical device engineering.
Gaynanova, who joined the Texas A&M Department of Statistics in 2015, received both her master of science (2013) and Ph.D. in statistics (2015) from Cornell University after earning a master of science with honors in applied mathematics and computer science from Lomonosov Moscow State University (2004) and working in Moscow’s private sector as a senior specialist in the Balancing Marketing Division of the OJSC Trading System Administration (2009-2010) and a junior statistician in the Census Division of the AC Nielsen (2008-2009). Her research, which focuses on the development of statistical methods for analysis of modern high-dimensional biomedical data, is at the intersection of applied, computational and theoretical statistics — the fundamental underpinning for developing new statistical methodology that is both computationally efficient and theoretically sound in order to help solve challenging problems across a broad range of disciplines. Prior to earning the CAREER Award, she served as a principal investigator on a three-year NSF grant to study scalable methods for classifying heterogeneous high-dimensional data (2017-2020). In addition, she is a member of the NSF-funded Texas A&M Research Institute for Foundations of Interdisciplinary Data Science (FIDS) as well as a principal investigator for a 2020 Texas A&M Presidential Transformational Teaching Grant funded through the President’s Excellence Fund.
A member of the American Statistical Association (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. She was recognized with the ASA’s 2018 David P. Byar Young Investigator Award. Last month, Gaynanova was an invited guest for a Pod of Asclepius healthcare technology video podcast highlighting her team’s analysis of continuous glucose monitoring (CGM) data, available via YouTube and PodBean. The team featured one graduate student and five undergraduate students whose collective work through the Aggie Research Project resulted in the June 2020 release of a list of public CGM datasets and an open-source software package iglu that helps researchers and clinicians interpret blood glucose data.
“The 21st century has seen the explosion of data that is now available for any individual: genetics data, physical activity data, neuroimaging data, etc.,” Gaynanova said. “Different types of data present complementary information on a person’s health, but the existing tools focus on one data type at a time, leading to a very narrow view of the biological system. In my research, I develop statistical tools that combine information across data types leading to improved understanding of biological system, and ultimately improved prediction of health outcomes. I am thrilled to receive an NSF CAREER Award, as it will allow me to develop the so-much-needed quantitative tools for making sense out of multi-layered complex biomedical data, engage even further in collaborative work with domain scientists, and mentor the next generation of statisticians.”
Maier joined the Texas A&M Department of Mathematics faculty in 2018 after spending three years at the University of Minnesota as an assistant professor. He received his doctorate in mathematics from Heidelberg University in 2015 as well as master’s degrees in both mathematics and physics there in 2011. His research at Texas A&M focuses on computational mathematics ranging from multiscale effects and methods to computational fluid dynamics and finite element methods. Since 2019, Maier has served as a principal investigator on a previous three-year NSF grant supporting his research to simulate multiscale effect in optical metamaterials. He also was a co-principal investigator for a 2019 Texas A&M Triads for Transformation grant funded through the President’s Excellence Fund.
In addition to creating a high-performance finite-element solver for the compressible Navier-Stokes and Euler equations known as ryujin, Maier has been a contributor to the Finite Element Toolkit Gascoigne 3D since 2011. For the past 10 years, he also has been a principal developer and project administrator for deal.II, an open-source modeling software library initially developed by former Texas A&M mathematician Wolfgang Bangerth that helps researchers across the world harness the power of supercomputers to provide more accurate pictures of complex problems and processes in a host of vital areas, from the environment and energy to healthcare. Several of Maier’s most recent computations also are featured on his YouTube channel.
“My principal field of research lies in the analysis and simulation of problems with two-scale and multiscale phenomena,” Maier said. “These are challenging modeling and simulation problems where relevant physical processes act on highly different length and time scales. An example are metamaterial-based optical devices that have made the dream of manipulating the laws of optics on the nanoscale a near reality. My NSF CAREER Award proposal aims at addressing a critical need for developing robust and controllable numerical schemes that can reliably predict the optical response of such complex microscale geometries.”
Each year, the NSF presents an estimated 500 CAREER awards totaling around $250 million to early career faculty at U.S. institutions of higher learning, museums, observatories, research laboratories, professional societies, and similar organizations associated with research or educational activities.
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