Sharmistha Guha

Assistant Professor

Department of Statistics

Texas A&M University

A list of my publications is available via my Google Scholar page, and my research codes can be accessed via my GitHub page (link provided here).

Contact:

Department of Statistics

Texas A&M University

3143 TAMU

College Station, TX 77843

Office: 459D Blocker

Email: sharmistha@tamu.edu

My research focuses on developing Bayesian methods for analyzing and interpreting complex, high-dimensional structured data. I apply these methods across diverse fields like neuroscience, driven by the challenges in analyzing multimodal neuroimaging data (e.g., dMRI, fMRI), and in network security. I develop models and use object-oriented data analysis techniques that integrate heterogeneous, complex data types, such as networks and functional data. My research also includes methodologies for causal inference, record linkage, and data privacy, with applications in financial and social sciences.

I believe that addressing challenging applied questions drives the development of better statistical methods, advancing scientific knowledge for the benefit of humanity. Collaborating with domain experts and methodological researchers is key to this goal, and I find great satisfaction in such partnerships.

My work has been recognized with the 2022 Blackwell-Rosenbluth award, which "aims at recognizing outstanding junior Bayesian researchers based on their overall contribution to the field and to the community," as well as an Honorable Mention in the 2021 Savage Award Competition (Applied Methodology). The Savage Award, conferred by the International Society for Bayesian Analysis (ISBA), "is bestowed each year to outstanding doctoral dissertations in Bayesian econometrics and statistics."

I am deeply passionate about teaching and training the next generation of statisticians and practitioners, and hence place special emphasis on computational skills and reproducible research in my courses. I believe in the amalgamation of research and education missions, and actively involve my students (both undergraduate and graduate) in my research group. In recognition of my ongoing efforts towards undergraduate research mentorship and sponsorship, I have been awarded the DeBakey Executive Research Leader certificate by the Texas A&M University.

News:

Sep 2024: Delivered an invited talk at Los Alamos National Lab (LANL) as an Information Science and Technology Institute Distinguished Faculty Fellow at LANL.
Aug 2024: Delivered an invited talk in the workshop titled "Challenges in Neuroimaging Data Analysis" at the Institute for Mathematical and Statistical Innovation (IMSI) at the University of Chicago.
Aug 2024: Delivered an invited talk in the session organized by j-ISBA titled "Blackwell-Rosenbluth Award" at the Joint Statistical Meetings (JSM) at Portland, OR.
Jun 2024: Received NSF-DMS grant No. 2413721 for proposal titled "New Directions in Bayesian Heterogeneous Data Integration: Methods, Theory and Applications."
Jun 2024: First PhD student Mr. Jose Rodriguez-Acosta named one of the 2024 NSF Graduate Research Fellows which will fund his graduate studies. The five-year fellowship, which is considered the most prestigious graduate fellowship offered by the National Science Foundation, provides three years of financial support along with assistance with tuition and fees to support his continued academic study and recognize his demonstrated potential to be a high achieving scientist. Here is the news feed at Texas A&M College of Arts & Sciences. Congrats Jose!
Jul 2023: Delivered an invited talk in the session titled "Recent Advances in Bayesian Statistics by j-ISBA Blackwell-Rosenbluth Award Winners" at the International Statistical Institute (ISI) World Congress at Ottawa, CA. Here is the message from the ISBA president regarding this event.
Mar 2023: Received an IMS New Researcher Travel Award conferred by the Institute of Mathematical Statistics.
Jan 2023: Received a DeBakey Executive Research Leader certificate awarded by the Texas A&M University in recognition of my ongoing efforts towards undergraduate research mentorship and sponsorship.
Nov 2022: Received a 2022 Blackwell-Rosenbluth award, awarded by the International Society for Bayesian Analysis, which "aims at recognizing outstanding junior Bayesian researchers based on their overall contribution to the field and to the community." Duke Statistical Science press release.
Oct 2022: Participated in the 2022 National Institute of Statistical Sciences (NISS) Virtual Academic Career Fair.
Oct 2022: Served as a panelist in the Aggie Data Science Club Research Panel. This is an event organized by the Aggie Data Science Club, with undergraduate students from different majors as members, the goal being to make them aware of how data science is applied to different subjects and learn about various research opportunities.
June 2022: Received a Texas A&M University College of Arts & Sciences Merger Type-I Grant ($10,000) for grant titled "Novel Methods for Imaging Data from Multiple Modalities" with Co-Investigator Jessica Bernard, Associate Professor, Department of Psychological and Brain Sciences at Texas A&M University.
June 2022: Undergraduate team member Jacob Pagel received a Statistics Summer Undergraduate Research Fellowship ($1,500) from the Texas A&M University College of Arts & Sciences. Congratulations Jacob!!
May 2022: Undergraduate team member Jacob Pagel received a Fellowship to attend the NIH-funded Colorado Summer Institute in Biostatistics (CoSIBS) program (Summer 2022) at the University of Colorado Anschutz Medical Campus, Aurora, CO. Congratulations Jacob!!
Sep 2021: Joined the Statistics Department at Texas A&M University an an assistant professor (tenure track).
Jul 2021: Received an Honorable Mention in the 2021 Savage Award Competition (Applied Methodology) for my Ph.D. dissertation "On Bayesian Methods in Network Regression." The Savage Award, conferred by the International Society for Bayesian Analysis (ISBA), and is "bestowed each year to outstanding doctoral dissertations in Bayesian econometrics and statistics."