Bhaswar Bhattacharya

Education

Ph.D. in Statistics, Stanford University, 2016
Master of Statistics (M. Stat.), Indian Statistical Institute, 2011
Bachelor of Statistics (B. Stat.), Indian Statistical Institute, 2009

Bhaswar B. Bhattacharya and Sumit Mukherjee (2017), Inference in Ising models, Bernoulli, (to appear).

Bhaswar B. Bhattacharya and Sumit Mukherjee (2017), Degree sequence of random permutation graphs, Annals of Applied Probability, (to appear).

Bhaswar B. Bhattacharya, Persi Diaconis, Sumit Mukherjee (2017), Universal limit theorems in graph coloring problems with connections to extremal combinatorics, Annals of Applied Probability, (to appear).

Bhaswar B. Bhattacharya (2017), Collision times in multicolor urn models and sequential graph coloring with applications to discrete logarithms, Annals of Applied Probability, (to appear).

Artitra Banik, Bhaswar B. Bhattacharya, Sandip Das, Satyaki Mukherjee (Work In Progress), The discrete Voronoi game in R2.

Deepan Basu, Kinjal Basu, Bhaswar B. Bhattacharya, Sandip Das (2016), Almost empty monochromatic triangles in planar point sets, Discrete Applied Mathematics, 210, pp. 207213.

Bhaswar B. Bhattacharya (Under Review), Distribution of twosample tests based on geometric graphs and applications.

Bhaswar B. Bhattacharya (Under Review), Power of graphbased twosample tests.

Bhaswar B. Bhattacharya, Shirshendu Ganguly, Xuancheng Shao, Yufei Zhao (Under Review), Upper tails for arithmetic progressions in a random set.

Bhaswar B. Bhattacharya and Subhabrata Sen (2016), High temperature asymptotics of orthogonal meanfield spin glasses, Journal of Statistical Physics, 162, pp. 6380.

Past Courses

STAT431 STATISTICAL INFERENCE

Graphical displays; one and twosample confidence intervals; one and twosample hypothesis tests; one and twoway ANOVA; simple and multiple linear leastsquares regression; nonlinear regression; variable selection; logistic regression; categorical data analysis; goodnessoffit tests. A methodology course. This course does not have business applications but has significant overlap with STAT 101 and 102.

STAT511 STATISTICAL INFERENCE

Graphical displays; one and twosample confidence intervals; one and twosample hypothesis tests; one and twoway ANOVA; simple and multiple linear leastsquares regression; nonlinear regression; variable selection; logistic regression; categorical data analysis; goodnessoffit tests. A methodology course.

STAT970 MATHEMATICAL STATISTICS

Decision theory and statistical optimality criteria, sufficiency, point estimation and hypothesis testing methods and theory.

STAT991 SEM IN ADV APPL OF STAT

This seminar will be taken by doctoral candidates after the completion of most of their coursework. Topics vary from year to year and are chosen from advance probability, statistical inference, robust methods, and decision theory with principal emphasis on applications.

Knowledge @ Wharton

Making Statistics Work in the Real World, Knowledge @ Wharton 06/29/2017