Strong activity rules for iterative combinatorial auctions. - Pavithra Harsha; Cynthia Barnhart; David C. Parkes; Haoqi Zhang (Comput. Oper. Res., 2010)

Optimal sizing of energy storage for efficient integration of renewable energy. - Pavithra Harsha; Munther A. Dahleh (CDC/ECC, 2011)

A Framework for the Analysis of Probabilistic Demand Response Schemes. - Pavithra Harsha; Mayank Sharma; Ramesh Natarajan; Soumyadip Ghosh (IEEE Trans. Smart Grid, 2013)

Special Issue of INFORMS Journal on Applied Analytics - Analytics Behind Designing and Managing Omni-channel Supply Chains. - Burcu B. Keskin; Pavithra Harsha (INFORMS J. Appl. Anal., 2019)

Dynamic Pricing of Omnichannel Inventories. - Pavithra Harsha; Shivaram Subramanian; Joline Uichanco (Manuf. Serv. Oper. Manag., 2019)

A Practical Price Optimization Approach for Omnichannel Retailing. - Pavithra Harsha; Shivaram Subramanian; Markus Ettl (INFORMS J. Optim., 2019)

Designing Price Incentives in a Network with Social Interactions. - Maxime C. Cohen; Pavithra Harsha (Manuf. Serv. Oper. Manag., 2020)

A Data-Driven Approach to Personalized Bundle Pricing and Recommendation. - Markus Ettl; Pavithra Harsha; Anna Papush; Georgia Perakis (Manuf. Serv. Oper. Manag., 2020)

Math Programming based Reinforcement Learning for Multi-Echelon Inventory Management. - Pavithra Harsha; Ashish Jagmohan; Jayant R. Kalagnanam; Brian Quanz; Divya Singhvi (CoRR, 2021)

Demand Modeling in the Presence of Unobserved Lost Sales. - Shivaram Subramanian; Pavithra Harsha (Manag. Sci., 2021)

A Prescriptive Machine-Learning Framework to the Price-Setting Newsvendor Problem. - Pavithra Harsha; Ramesh Natarajan; Dharmashankar Subramanian (INFORMS J. Optim., 2021)

Hierarchy-guided Model Selection for Time Series Forecasting. - Arindam Jati; Vijay Ekambaram; Shaonli Pal; Brian Quanz; Wesley M. Gifford; Pavithra Harsha; Stuart Siegel; Sumanta Mukherjee; Chandra Narayanaswami (CoRR, 2022)

Learning Personalized Product Recommendations with Customer Disengagement. - Hamsa Bastani; Pavithra Harsha; Georgia Perakis; Divya Singhvi (Manuf. Serv. Oper. Manag., 2022)

End-to-End Learning for Optimization via Constraint-Enforcing Approximators. - Rares Cristian; Pavithra Harsha; Georgia Perakis; Brian Leo Quanz; Ioannis Spantidakis (AAAI, 2023)

Hierarchical Proxy Modeling for Improved HPO in Time Series Forecasting. - Arindam Jati; Vijay Ekambaram; Shaonli Pal; Brian Quanz; Wesley M. Gifford; Pavithra Harsha; Stuart Siegel; Sumanta Mukherjee; Chandra Narayanaswami (KDD, 2023)

An Optimistic-Robust Approach for Dynamic Positioning of Omnichannel Inventories. - Pavithra Harsha; Shivaram Subramanian; Ali Koc; Mahesh Ramakrishna; Brian Quanz; Dhruv Shah; Chandra Narayanaswami (CoRR, 2023)

Inter-Series Transformer: Attending to Products in Time Series Forecasting. - Rares Cristian; Pavithra Harsha; Clemente Ocejo; Georgia Perakis; Brian Quanz; Ioannis Spantidakis; Hamza Zerhouni (CoRR, 2024)

Leveraging Interpretability in the Transformer to Automate the Proactive Scaling of Cloud Resources. - Amadou Ba; Pavithra Harsha; Chitra Subramanian (CoRR, 2024)

Optimal Workload Placement on Multi-Instance GPUs. - Bekir O. Turkkan; Pavankumar Murali; Pavithra Harsha; Rohan R. Arora; Gerard Vanloo; Chandra Narayanaswami (CoRR, 2024)

Deep Policy Iteration with Integer Programming for Inventory Management. - Pavithra Harsha; Ashish Jagmohan; Jayant Kalagnanam; Brian Quanz; Divya Singhvi (Manuf. Serv. Oper. Manag., 2025)

Efficient End-to-End Learning for Decision-Making: A Meta-Optimization Approach. - Rares Cristian; Pavithra Harsha; Georgia Perakis; Brian Quanz (CoRR, 2025)

Aligning Learning and Endogenous Decision-Making. - Rares Cristian; Pavithra Harsha; Georgia Perakis; Brian Quanz (CoRR, 2025)