Professor Angshuman Roy has BStat and MStat degrees from Indian Statistical Institute, Kolkata. He has his PhD in statistics from the same institute. In his PhD, he investigated measuring and testing association among random variables. After completing PhD, he visited ISI Kolkata for a while and researched on change-point detection in high-dimensional data. After that, he went to University of Haifa for post-doctorate where he worked on an order-restricted inference problem.

His primary research interest lies in the field of multivariate statistics, especially in measuring association among random variables and in causal inference. He is also interested in the topics of statistical learning.

• Dawn, T., Roy, A., Manna, A., and Ghosh, A. K. (2021) Some clustering-based change-point detection methods applicable to high dimension, low sample size data. Journal of Multivariate Analysis, Communicated. https://arxiv.org/abs/2111.14012.
• Roy, A., and Ghosh, A. K. (2020) Some tests of independence based on maximum mean discrepancy and ranks of nearest neighbors, Statistics and Probability Letters, 164, 108793.
• Roy, A., Das, K., Sarkar S., and Ghosh, A.K. (2020) Some tests of mutual independence among several random vectors using ranks of nearest neighbors. Journal of Statistical Computation and Simulation, 91(9), 1890-1906.
• Roy, A., Sarkar, S., Ghosh, A. K., and Goswami, A. (2020) On some consistent tests of mutual independence among several random vectors of arbitrary dimensions, Statistics and Computing, 30(6), 1707-1723.
• Roy, A. (2020) Some copula-based tests of independence among several random variables having arbitrary probability distributions, Stat, 9(1), e263.
• Roy, A., Ghosh, A. K., Goswami, A., and Murthy, C. A. (2020) Some new copula based distribution-free tests of independence among several random variables, Sankhya: Series A, 1-41.