| Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States EY Cramer, EL Ray, VK Lopez, J Bracher, A Brennen, ... Proceedings of the National Academy of Sciences 119 (15), e2113561119, 2022 | 172 | 2022 |
| Predicting Bike Usage for New York City's Bike Sharing System. D Singhvi, S Singhvi, PI Frazier, SG Henderson, E O'Mahony, DB Shmoys, ... AAAI Workshop: Computational Sustainability, 2015 | 149 | 2015 |
| Leveraging comparables for new product sales forecasting L Baardman, I Levin, G Perakis, D Singhvi Available at SSRN 3086237, 2017 | 68 | 2017 |
| The united states covid-19 forecast hub dataset EY Cramer, Y Huang, Y Wang, EL Ray, M Cornell, J Bracher, A Brennen, ... Scientific data 9 (1), 462, 2022 | 48 | 2022 |
| Learning personalized product recommendations with customer disengagement H Bastani, P Harsha, G Perakis, D Singhvi Manufacturing & Service Operations Management 24 (4), 2010-2028, 2022 | 38* | 2022 |
| COVID‐19: A multiwave SIR‐based model for learning waves G Perakis, D Singhvi, O Skali Lami, L Thayaparan Production and Operations Management 32 (5), 1471-1489, 2023 | 27* | 2023 |
| Dynamic pricing with unknown nonparametric demand and limited price changes G Perakis, D Singhvi Operations Research, 2023 | 13 | 2023 |
| COVID-19: Prediction, prevalence, and the operations of vaccine allocation A Bennouna, J Joseph, D Nze-Ndong, G Perakis, D Singhvi, OS Lami, ... Manufacturing & Service Operations Management 25 (3), 1013-1032, 2023 | 7* | 2023 |
| Leveraging the newsvendor for inventory distribution at a large fashion e-retailer with depth and capacity constraints G Perakis, D Singhvi, Y Spantidakis Available at SSRN 3632459, 2020 | 7 | 2020 |
| The role of optimization in some recent advances in data-driven decision-making L Baardman, R Cristian, G Perakis, D Singhvi, O Skali Lami, ... Mathematical Programming 200 (1), 1-35, 2023 | 4 | 2023 |
| Ancillary Services in Targeted Advertising: From Prediction to Prescription A Borenstein, A Mangal, G Perakis, S Poninghaus, D Singhvi, ... Manufacturing & Service Operations Management, 2023 | 3* | 2023 |
| Math programming based reinforcement learning for multi-echelon inventory management P Harsha, A Jagmohan, J Kalagnanam, B Quanz, D Singhvi Available at SSRN 3901070, 2021 | 3 | 2021 |
| Xstrees: A tree sampling framework for interpretable tree ensembles G Perakis, D Singhvi, O Skali-Lami Available at SSRN, 2019 | 3* | 2019 |
| First Delivery Gaps: A Supply Chain Lever to Reduce Product Returns in Online Retail G Perakis, D Singhvi Available at SSRN 3360554, 2019 | 2 | 2019 |
| Online Learning with Sample Selection Bias D Singhvi, S Singhvi Available at SSRN, 2022 | 1 | 2022 |
| A Data-driven Approach to Improve Artisans' Productivity in Distributed Supply Chains D Singhvi, S Singhvi, X Zhang Available at SSRN 4531090, 2023 | | 2023 |
| Combining math-programming and reinforcement learning for problems with known transition dynamics P Harsha, A Jagmohan, BL Quanz, D Singhvi US Patent App. 17/751,625, 2023 | | 2023 |
| Increasing Charity Donations: A Bandit Learning Approach D Singhvi, S Singhvi Increasing Charity Donations: A Bandit Learning Approach: Singhvi, Divya …, 2022 | | 2022 |
| Buying Cheap: Brand Switching During Economic Distress and Its Disparate Impact on Consumers S Dutta, D Singhvi, S Singhvi Buying Cheap: Brand Switching During Economic Distress and Its Disparate …, 2022 | | 2022 |
| Data-driven decision making in online and offline retail D Singhvi Massachusetts Institute of Technology, 2020 | | 2020 |
Georgia PerakisWilliam F. Pounds Professor of Operations Management and Operations ResearchVerified email at mit.edu
