| 2025 | CIKM | Efficiency Boost in Decentralized Optimization: Reimagining Neighborhood Aggregation with Minimal Overhead. | Durgesh Kalwar, Mayank Baranwal, Harshad Khadilkar |
| 2025 | IJCNLP | AURA-QG: Automated Unsupervised Replicable Assessment for Question Generation. | Rajshekar K, Harshad Khadilkar, Pushpak Bhattacharyya |
| 2024 | COMAD | A Learning Approach for Discovering Cost-Efficient Integrated Sourcing and Routing Strategies in E-Commerce. | Omkar Shelke, Pranavi Pathakota, Anandsingh Chauhan, Hardik Meisheri, Harshad Khadilkar, Balaraman Ravindran |
| 2024 | COMAD | Deep reinforcement learning approach for routing and scheduling of trains at railway station. | Sudhir R. Shetiya, Shripad Salsingikar, Harshad Khadilkar |
| 2024 | COMAD | Guiding Offline Reinforcement Learning Using a Safety Expert. | Richa Verma, Durgesh Kalwar, Harshad Khadilkar, Balaraman Ravindran |
| 2024 | IJCAI | Linear-Time Optimal Deadlock Detection for Efficient Scheduling in Multi-Track Railway Networks. | Hastyn Doshi, Ayush Tripathi, Keshav Agarwal, Harshad Khadilkar, Shivaram Kalyanakrishnan |
| 2023 | COMAD | Using Contrastive Samples for Identifying and Leveraging Possible Causal Relationships in Reinforcement Learning. | Harshad Khadilkar, Hardik Meisheri |
| 2023 | COMAD | Learning to Minimize Cost to Serve for Multi-Node Multi-Product Order Fulfilment in Electronic Commerce. | Pranavi Pathakota, Kunwar Zaid, Anulekha Dhara, Hardik Meisheri, Shaun D'Souza, Dheeraj Shah, Harshad Khadilkar |
| 2023 | EMNLP | Reinforcement Replaces Supervision: Query focused Summarization using Deep Reinforcement Learning. | Swaroop Nath, Pushpak Bhattacharyya, Harshad Khadilkar |
| 2022 | COMAD | Identifying efficient curricula for reinforcement learning in complex environments with a fixed computational budget. | Omkar Shelke, Hardik Meisheri, Harshad Khadilkar |
| 2022 | IJCNN | Gatekeeper: A deep reinforcement learning-cum-heuristic based algorithm for scheduling and routing trains in complex environments. | Deepak Mohapatra, Ankush Ojha, Harshad Khadilkar, Supratim Ghosh |
| 2021 | CIKM | Revisiting State Augmentation methods for Reinforcement Learning with Stochastic Delays. | Somjit Nath, Mayank Baranwal, Harshad Khadilkar |
| 2021 | COMAD | Anticipatory Decisions in Retail E-Commerce Warehouses using Reinforcement Learning. | Omkar Shelke, Vinita Baniwal, Harshad Khadilkar |
| 2021 | IJCNN | FoLaR: Foggy Latent Representations for Reinforcement Learning with Partial Observability. | Hardik Meisheri, Harshad Khadilkar |
| 2021 | WSC | A Simulation Driven Optimization Algorithm for Scheduling Sorting Center Operations. | Supratim Ghosh, Aritra Pal, Prashant Kumar, Ankush Ojha, Aditya A. Paranjape, Souvik Barat, Harshad Khadilkar |
| 2019 | MABS | Reinforcement Learning of Supply Chain Control Policy Using Closed Loop Multi-agent Simulation. | Souvik Barat, Prashant Kumar, Monika Gajrani, Harshad Khadilkar, Hardik Meisheri, Vinita Baniwal, Vinay Kulkarni |
| 2014 | SENSYS | Collaborative energy conservation in a microgrid. | Mohit Jain, Harshad Khadilkar, Neha Sengupta, Zainul Charbiwala, Kushan U. Tennakoon, Rodzay bin Haji Abdul Wahab, Liyanage Chandratilake De Silva, Deva P. Seetharam |