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.
Kazemzadeh K, Bansal P, 2021, Electric bike navigation comfort in pedestrian crowds, Sustainable Cities and Society, Vol:69, ISSN:2210-6707
Bansal P, Krueger R, Graham DJ, 2021, Fast Bayesian estimation of spatial count data models, Computational Statistics & Data Analysis, Vol:157, ISSN:0167-9473, Pages:1-19
et al., 2021, Fuel economy valuation and preferences of Indian two-wheeler buyers, Journal of Cleaner Production, Vol:294, ISSN:0959-6526
et al., 2021, A causal inference approach to measure the vulnerability of urban metro systems, Transportation, ISSN:0049-4488