معرفی
Sayar Karmakar is an Assistant Professor in the Department of Statistics at the University of Florida. His research focuses on time series analysis, high-dimensional statistics, econometrics, and neural networks. He holds a B.Stat and M.Stat from the Indian Statistical Institute and a PhD in Statistics from the University of Chicago. Dr. Karmakar has served on editorial boards of journals like Statistical Papers and Sankhya A, and has received grants from NSF and AMS Simons, totaling over $200,000. His work spans theoretical contributions in posterior consistency, time-varying models, and applied research in cyberbullying analysis and climate change.
Education
- B.Stat, Indian Statistical Institute (Kolkata)
- M.Stat, Indian Statistical Institute (Kolkata)
- PhD in Statistics, University of Chicago
Research Interests
Dr. Karmakar’s research explores dependence structures in data, including time series (stationary/non-stationary), econometric models (GARCH/ARCH), neural networks, and spatial/spatiotemporal systems. His work emphasizes robust statistical methods, such as change-point detection, posterior consistency, and model-free predictions. Recent projects include analyzing cryptocurrency volatility, climate risks in financial markets, and cyberbullying trends during the pandemic.
Grants & Awards
- NSF DMS Grant (ATD Program: $200,000, 2021-2024)
- AMS Simons Travel Grant (2021-2024)
- Early Career Advisory Board Member, Journal of Multivariate Analysis
Teaching
He has taught courses at the University of Florida (Probability, Time-Series Forecasting) and University of Chicago (Statistical Methods, Probability Theory). He was nominated as Best Tutor in Statistics at the University of Chicago (2014-2016).
Labs & Collaborations
Dr. Karmakar collaborates with researchers in epidemiology, cybersecurity, and climate science. His lab focuses on developing algorithms for large geospatial datasets and analyzing complex systems like cryptocurrency networks and disease propagation.
