Home > Academics > Academic Units > School of Management > Vinod Gupta School of Management > Sushil Punia
I work in the areas of decision analytics, operations and supply chain management, and public sector operations research. I have specific research interests in building forecasting and optimization (a.k.a. predictive and prescriptive analytics) decision models using data-driven optimization and machine learning.
My present focus is to address contemporary strategic and operational issues related to resource allocation and last-mile services delivery in healthcare, and urban logistics and mobility sectors.
From predictive to prescriptive analytics: A data-driven multi-item newsvendor model by Punia S., Singh S. P., Madaan J. Decision Support Systems 136 - (2020)
A cross-temporal hierarchical framework and deep learning for supply chain forecasting by Punia S., Singh S. P., Madaan J. Computers & Industrial Engineering 149 - (2021)
Deep learning with long short-term memory networks and random forests for demand forecasting in multi-channel retail by Punia S., Nikolopoulos K. , Singh S. P., Madaan J. , Litsiou K. International Journal of Production Research 58 4964-4979 (2020)
Forecasting and planning during a pandemic: COVID-19 growth rates, supply chain disruptions, and governmental decisions by Nikolopoulos K., Punia S. , Schäfers A. , Tsinopoulos C. , Vasilakis C. European Journal of Operational Research 290 99-115 (2021)
Predictive analytics for demand forecasting: A deep learning-based decision support system by Punia S., Shankar S. Knowledge-Based Systems 258 109956-109956 (2022)
Effective, Efficient, and Equitable Allocations of Vaccines: A Strategic Decision Framework and a Multi-level Planning Model for National Vaccination Programs INDIAN COUNCIL OF SOCIAL SCIENCE RESEARCH
Ridership Forecasting in Public Transit Systems for Effective Operations Management SPONSORED RESEARCH and INDUSTRIAL CONSULTANCY (SRIC)
Soumita Rakshit
Area of Research: Operations Management and Analytics