prajamitra

Name Card

Name: 
Prajamitra Bhuyan
Position: 
Assistant Professor
Academic Group: 
Operations Management
Phone No.: 
+91-33-24678300 Extn. No. 2023
Personal Details: 
I am an Assistant Professor in Statistics at the Indian Institute of Management, Calcutta. Prior to joining IIM Calcutta, I held a Lecturership in Mathematical Data Science at the Queen Mary University of London. Also, I was engaged with the data-centric engineering programme at the Alan Turing Institute. I held a postdoctoral position at the Imperial College London and National Postdoctoral Fellowship in India after completing PhD degree in Statistics from the Indian Statistical Institute. I have several years of industry experience as a Data Scientist in the Analytics sector, providing training and analytical solutions to global clients across industry verticals. I am passionate about solving real-world business problems and issues related to the humanitarian crisis.
Email (@iimcal.ac.in): 
prajamitra.bhuyan@iimcal.ac.in
URL: 
https://prajamitrabhuyan.wixsite.com/profile

Academics

Academic Background: 
PhD in Statistics, Indian Statistical Institute M.Stat, Indian Statistical Institute
Awards: 
Elected Member since 2019, International Statistical Institute. M. N. Murthy Memorial Prize : 2017-2018, awarded by Indian Statistical Institute for outstanding thesis in Applied Statistics. National Postdoctoral Fellowship, 2017, Science and Engineering Research Board, Government of India. Junior Research Fellowship, 2011, Indian Statistical Institute.

Experience

Consulting Interests: 
As a Data Scientist, my main consulting interest is in the Analytics sector to provide analytical solutions across industry verticals. I work across multiple functions in consulting, including advanced statistical modeling in different analytical domains using both structured and unstructured information with global organizations. I have established and headed an offshore credit risk modeling team and managed onsite projects in the UK and USA for premier banking and financial institutions.
Work Experience: 
Assistant Professor, Indian Institute of Management, Calcutta, 2022 - Present Lecturer in Mathematical Data Science, Queen Mary University of London, 2021 - 2022 Visiting Researcher, The Alan Turing Institute, 2018-2022 Research Scientist, Imperial College London, 2018 - 2021 National Postdoctoral Fellow, Indian Institute of Engineering Science and Technology (IIEST), Shibpur, 2017 - 2018 Consultant Statistician, Freelance, 2009 - 2017 Consultant, Price Waterhouse Coopers, 2007 - 2009 Risk Analyst, Genpact, 2006 - 2007 Statistical Analyst, Marketics, 2006

Research

Journal Publications: 
Ghosh S, Bhuyan P, Finkelstein M, 2022, On a bivariate copula for modeling negative dependence, Statistical Methods and Applications. Bhuyan P, McCoy E, Li H, Graham D J, 2021, Analysing causal effects of the London cycle superhighways on traffic congestion, Annals of Applied Statistics, Vol: 15 (4), Pages: 1999-2022. Jha J*, Bhuyan P*, 2021, Two-stage circular-circular regression with zero-inflation: application to medical sciences, Annals of Applied Statistics, Vol: 15 (3), Pages: 1343-1365. Nanda P, Bhuyan P, Dewanji A, 2021, Optimal replacement policy under cumulative damage model and strength degradation with applications, Annals of Operations Research, Vol: 315, Pages: 1345–1371. Bhuyan P, Ghosh S, Majumder P, Mitra M, 2020, A bivariate life distribution and notions of negative dependence, Stat, Vol: 9(1). Jha P, Banerjee S, Bhuyan P, Sudarshan M, Dewanji A, 2020, Elemental distribution in urban sediments of small waterbodies and its implications: a case study from Kolkata, India, Environmental Geochemistry and Health, Vol: 42, Pages: 461-482. Bhuyan P, 2019, Estimation of random-effects model for longitudinal data with nonignorable missingness using Gibbs sampling, Computational Statistics, Vol: 34, Pages: 1693-1710. Bhuyan P, Biswas J, Ghosh P, Das K, 2019, A Bayesian two-stage regression approach of analysing longitudinal outcomes with endogeneity and incompleteness, Statistical Modelling, Vol: 19, Pages: 157-173. Chatterjee K, Bhuyan P, 2019, On the estimation of population size from a post-stratified two-sample capture-recapture data under dependence, Journal of Statistical Computation and Simulation, Vol: 90, Pages: 819-838. Chatterjee K*, Bhuyan P*, 2019, On the estimation of population size from a dependent triple‐record system, Journal of the Royal Statistical Society: Series A (Statistics in Society), Vol: 182, Pages: 1487-1501. Bhuyan P, Mitra M, Dewanji A, 2018, Identifiability issues in dynamic stress-strength modeling, Annals of the Institute of Statistical Mathematics, Vol: 70, Pages: 63-81. Bhuyan P, Sengupta D, 2017, Estimation of reliability with semi-parametric modeling of degradation, Computational Statistics & Data Analysis, Vol: 115, Pages: 172-185, ISSN: 0167-9473. Bhuyan P, Dewanji A, 2017, Estimation of reliability with cumulative stress and strength degradation, Statistics, Vol: 51, Pages: 766-781. Bhuyan P, Dewanji A, 2017, Reliability computation under dynamic stress-strength modeling with cumulative stress and strength degradation, Communications in Statistics - Simulation and Computation, Vol: 46, Pages: 2701-2713. * contributed equally.
Conferences: 
Chattopadhyay N, Bhuyan P, 2020, Player selection strategy: a quantitative perspective, Proceedings of the 62nd ISI World Statistics Congresses: Contributed Paper Session, Vol-3.
Research Interests: 
My primary research interests lie broadly in statistical data science and methodology, motivated by real-life challenges arising from complex systems, social science and public policy. In particular, my doctoral work deals with computational and inferential issues in time-dependent stress-strength interference. In postdoctoral research, I worked on modeling and analysis of incomplete longitudinal data with missingness and zero-inflation. Currently, I am working on causal inference and its application in transport networks. I am also engaged in cross-disciplinary work, focusing on data-analytic settings in sports and environmental sciences.