The Statistics Seminar speaker for Wednesday, November 28, 2018, is Moulinath Banerjee, Professor of Statistics at the University of Michigan. He graduated from the Department of Statistics at the University of Washington, Seattle, under the supervision of Professor Jon A. Wellner. Prior to graduate study at the University of Washington, he completed both his Bachelors and Masters in Statistics at the Indian Statistical Institute, Kolkata.
Prof. Banerjee's research interests are in the fields of non-standard problems, empirical process theory, threshold and boundary estimation, and graphical networks. His main contributions to date are in the areas of inference under shape-restrictions, investigation of non-differentiable models in low and high-dimensional settings and inference in the setting of designed multistage procedures. Prof. Banerjee is the recipient of the 2011 IISA Young Investigators Award, and a fellow of both the IMS (Institute of Mathematical Statistics) and ASA (American Statistical Association).
Talk: Non-Standard Asymptotics in High Dimensions: Manski’s Maximum Score Estimator Revisited