Arka Banerjee is a Ph.D. candidate at the Indian Institute of Technology Kanpur in the Department of Mathematics and Statistics. Studying Markov Chain Monte Carlo (MCMC) sample quality by computationally efficient estimation of the asymptotic covariance matrices in the multidimensional MCMC setup is the main focus of his doctoral thesis. He has published in reputed journals and has participated in and presented papers at national and international conferences.

Arka holds a bachelor’s and a master’s in statistics from the University of Calcutta. Before joining IIT Kanpur, he was a data analyst at Infosys Limited for a year where he worked on a financial modeling project that dealt with the prediction of default payments in a banking institution.

As a Fulbright-Nehru Doctoral Research fellow at the University of Minnesota, Arka is exploring the computationally efficient and optimized procedures in the estimation of asymptotic covariance matrices in MCMC for a better understanding of MCMC sample quality. During his grant period, he will be studying MCMC sample quality in a high dimensional setting. Arka enjoys travelling and cooking different culinary dishes.