Prateek Bansal is a postdoctoral research associate of the Transport Strategy Centre (TSC) within the Centre for Transport Studies (CTS) at Imperial College.
His current research interests are: a) Fast, scalable, and online inference in discrete choice models using variational Bayes; b) Causal inference methods in transit systems with structural correlations; c) Addressing endogeneity in choice models using entropy-based framework.
His doctoral research focused on advancing the estimation of discrete choice models, with their applications in travel behavior modelling. The key areas of contribution are semi-parametric heterogeneity, t-distributed error kernel, minorization-maximization algorithms, quadrature methods to approximate multi-dimensional integrals, and design of choice experiments.
He joined Prof. Dan Graham's group at the TSC in August 2019. Before joining Imperial College, he received PhD from Cornell University, MS from UT Austin, and B.Tech from IIT Delhi.
Bansal P, Raj A, Sinha RK, 2022, Correlates of the COVID-19 Vaccine Hesitancy Among Indians, Asia-pacific Journal of Public Health, Vol:34, ISSN:1010-5395, Pages:583-585
Bansal P, Horcher D, Graham D, 2022, A dynamic choice model to estimate the user cost of crowding with large scale transit data, Journal of the Royal Statistical Society Series A: Statistics in Society, Vol:185, ISSN:0964-1998
et al., 2021, A causal inference approach to measure the vulnerability of urban metro systems, Transportation, Vol:48, ISSN:0049-4488, Pages:3269-3300
et al., 2021, Evaluating the predictive abilities of mixed logit models with unobserved inter- and intra-individual heterogeneity, Journal of Choice Modelling, Vol:41, ISSN:1755-5345
et al., 2021, Willingness to pay and attitudinal preferences of Indian consumers for electric vehicles, Energy Economics, Vol:100, ISSN:0140-9883