Sushil Punia

Title : Assistant Professor
Email Address :
Contact No : +91-9643-264474


  • Nikolopoulos, K., Punia, S., Schäfers, A., Tsinopoulos, C., & Vasilakis, C. (2021). Forecasting and planning during a pandemic: COVID-19 growth rates, supply chain disruptions, and governmental decisions. European Journal of Operational Research, 290(1), 99–115.

  • Shankar, S., Punia, S., & Ilavarasan, P. V. (2021). Deep learning-based container throughput forecasting: A triple bottom line approach. Industrial Management & Data Systems, 121(10), 2100–2117.

  • Punia, S., Singh, S., & Madaan, J. (2020). From predictive to prescriptive analytics: A data-driven multi-item newsvendor model. Decision Support Systems, 136, 113340.

  • Punia, S., Nikolopoulos, K., Singh, S. P., Madaan, J. K., & Litsiou, K. (2020). Deep learning with long short-term memory networks and random forests for demand forecasting in multi-channel retail. International Journal of Production Research, 58(16), 4964–4979.

  • Punia, S., Singh, S. P., & Madaan, J. K. (2020). A cross-temporal hierarchical framework and deep learning for supply chain forecasting. Computers & Industrial Engineering, 149, 106796.

  • Shankar, S., Punia, S., Singh, S. P., & Dong, J. (2020). Trajectory of research on maritime transportation in the era of digitization. Benchmarking: An International Journal, ahead-of-print(ahead-of-print).

  • Tiwari, P., Ilavarasan, P. V., & Punia, S. (2019). Content analysis of literature on big data in smart cities. Benchmarking: An International Journal, 28(5), 1837–1857.

  • Shankar, S., Ilavarasan, P. V., Punia, S., & Singh, S. P. (2019). Forecasting container throughput with long short-term memory networks. Industrial Management & Data Systems, 120(3), 425–441.

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