Sabyasachi Chatterjee

Professor with a deep interest in the intricate world of statistics, Sabyasachi Chatterjee serves as an Assistant Professor at the University of Illinois Urbana-Champaign. With a robust academic foundation, he earned his PhD in Statistics from Yale University in 2014. His scholarly pursuits are centered around nonparametric signal estimation and shape-constrained estimation, delving into aspects such as monotonicity, convexity, and unimodality. Professor Chatterjee's research extends into the realms of statistical information theory, where he explores its applications across diverse fields. His work in imaging and signal processing has contributed significantly to advancements in these areas, while his insights into quantile regression and computational biology have opened new avenues for exploration and innovation. His contributions to the field are well-recognized, with his research being published in esteemed journals like the Annals of Statistics, the Journal of the American Statistical Association, and the IEEE Transactions on Information Theory. These publications underscore his commitment to advancing statistical methodologies and their practical applications. In addition to his research, Professor Chatterjee is dedicated to mentoring the next generation of statisticians. He is actively involved in teaching and guiding students, fostering an environment of curiosity and rigorous inquiry. His passion for statistics and its potential to solve complex problems is evident in his approach to both research and education. Through his work, Professor Chatterjee continues to push the boundaries of statistical science, contributing to the development of innovative solutions that address real-world challenges. His expertise and dedication make him a valuable asset to the academic community and beyond.