A network congestion control approach to airport departure management. - Harshad Khadilkar; Hamsa Balakrishnan (ACC, 2012)

Optimal control of airport operations with gate capacity constraints. - Harshad Khadilkar; Hamsa Balakrishnan (ECC, 2013)

UrJar: A Lighting Solution using Discarded Laptop Batteries. - Vikas Chandan; Mohit Jain; Harshad Khadilkar; Zainul Charbiwala; Anupam Jain; Sunil Kumar Ghai; Rajesh Kunnath; Deva P. Seetharam (ACM DEV, 2014)

Algorithms for upgrading the resolution of aggregate energy meter data. - Harshad Khadilkar; Tanuja Ganu; Zainul Charbiwala; Chee Ming Lim; Sathyajith Mathew; Deva P. Seetharam (e-Energy, 2014)

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 (BuildSys, 2014)

DC Picogrids as power backups for office buildings. - Harshad Khadilkar; Vikas Chandan; Sandeep Kalra; Sunil Kumar Ghai; Zainul Charbiwala; Tanuja Ganu; Rajesh Kunnath; Chee Ming Lim; Deva P. Seetharam (SmartGridComm, 2014)

High Confidence Networked Control for Next Generation Air Transportation Systems. - Pangun Park; Harshad Khadilkar; Hamsa Balakrishnan; Claire J. Tomlin (IEEE Trans. Autom. Control., 2014)

Hybrid Communication Protocols and Control Algorithms for NextGen Aircraft Arrivals. - Pangun Park; Harshad Khadilkar; Hamsa Balakrishnan; Claire J. Tomlin (IEEE Trans. Intell. Transp. Syst., 2014)

Individual and Aggregate Electrical Load Forecasting: One for All and All for One. - Sambaran Bandyopadhyay; Tanuja Ganu; Harshad Khadilkar; Vijay Arya (e-Energy, 2015)

UrJar: A Device to Address Energy Poverty Using E-Waste. - Vikas Chandan; Mohit Jain; Harshad Khadilkar; Zainul Charbiwala; Anupam Jain; Sunil Kumar Ghai; Rajesh Kunnath; Deva P. Seetharam (e-Energy, 2015)

A Framework for Evaluating the Costs and Benefits of Instrumentation in Smart Home Systems. - Seema Nagar; Sandhya Aneja; Harshad Khadilkar; Sampath Dechu; Zainul Charbiwala (e-Energy, 2015)

Multi-User Energy Consumption Monitoring and Anomaly Detection with Partial Context Information. - Pandarasamy Arjunan; Harshad D. Khadilkar; Tanuja Ganu; Zainul M. Charbiwala; Amarjeet Singh 001; Pushpendra Singh 001 (BuildSys, 2015)

A socially aware incentive strategy for encouraging residential solar uptake in Brunei. - Harshad Khadilkar; Pratyush Kumar; Subendhu Rongali; Sampath Dechu; Pg Mohammad Iskandarbin Pg Hj Petra (SmartGridComm, 2015)

Modelling the impact of control strategy on stochastic delay propagation in transportation networks. - Harshad Khadilkar (ECC, 2016)

Unlocking the hidden potential of data towards efficient buildings: Findings from a pilot study in India. - Megha Nawhal; Heena Bansal; Ashok Pon Kumar; Vikas Chandan; Sridhar R; Babitha Ramesh; Sunil Kumar Ghai; Harshad Khadilkar; Deva P. Seetharam; Zainul M. Charbiwala; Vijay Arya; Amith Singhee (ISGT Europe, 2016)

SMOME: A framework for evaluating the costs and benefits of instrumentation in smart home systems. - Seema Nagar; Sandhya Aneja; Harshad Khadilkar; Sampath Dechu; Zainul Charbiwala (SmartGridComm, 2016)

Integrated Control of Airport and Terminal Airspace Operations. - Harshad Khadilkar; Hamsa Balakrishnan (IEEE Trans. Control. Syst. Technol., 2016)

Scheduling of vehicle movement in resource-constrained transportation networks using a capacity-aware heuristic. - Harshad Khadilkar (ACC, 2017)

Data-Enabled Stochastic Modeling for Evaluating Schedule Robustness of Railway Networks. - Harshad Khadilkar (Transp. Sci., 2017)

Learning representations for sentiment classification using Multi-task framework. - Hardik Meisheri; Harshad Khadilkar (WASSA@EMNLP, 2018)

An Imitation Learning Approach for Computing Anticipatory Picking Decisions in Retail Distribution Centres. - Vinita Baniwal; Chandrai Kayal; Dheeraj Shah; Padmakumar Ma; Harshad Khadilkar (ACC, 2019)

Actor Based Simulation for Closed Loop Control of Supply Chain using Reinforcement Learning. - Souvik Barat; Harshad Khadilkar; Hardik Meisheri; Vinay Kulkarni 001; Vinita Baniwal; Prashant Kumar; Monika Gajrani (AAMAS, 2019)

A Reinforcement Learning Framework for Container Selection and Ship Load Sequencing in Ports. - Richa Verma; Sarmimala Saikia; Harshad Khadilkar; Puneet Agarwal; Gautam Shroff; Ashwin Srinivasan 001 (AAMAS, 2019)

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 001 (MABS, 2019)

Reinforcement Learning for Multi-Objective Optimization of Online Decisions in High-Dimensional Systems. - Hardik Meisheri; Vinita Baniwal; Nazneen N. Sultana; Balaraman Ravindran; Harshad Khadilkar (CoRR, 2019)

Accelerating Training in Pommerman with Imitation and Reinforcement Learning. - Hardik Meisheri; Omkar Shelke; Richa Verma; Harshad Khadilkar (CoRR, 2019)

A rolling horizon optimisation model for consolidated hump yard operational planning. - Sumit Raut; Sudhir K. Sinha; Harshad Khadilkar; Shripad Salsingikar (J. Rail Transp. Plan. Manag., 2019)

A Scalable Reinforcement Learning Algorithm for Scheduling Railway Lines. - Harshad Khadilkar (IEEE Trans. Intell. Transp. Syst., 2019)

Optimising Lockdown Policies for Epidemic Control using Reinforcement Learning. - Harshad Khadilkar; Tanuja Ganu; Deva P. Seetharam (CoRR, 2020)

SIBRE: Self Improvement Based REwards for Reinforcement Learning. - Somjit Nath; Richa Verma; Abhik Ray; Harshad Khadilkar (CoRR, 2020)

Reinforcement Learning for Multi-Product Multi-Node Inventory Management in Supply Chains. - Nazneen N. Sultana; Hardik Meisheri; Vinita Baniwal; Somjit Nath; Balaraman Ravindran; Harshad Khadilkar (CoRR, 2020)

A Generalized Reinforcement Learning Algorithm for Online 3D Bin-Packing. - Richa Verma; Aniruddha Singhal; Harshad Khadilkar; Ansuma Basumatary; Siddharth Nayak; Harsh Vardhan Singh; Swagat Kumar; Rajesh Sinha (CoRR, 2020)

Sample Efficient Training in Multi-Agent Adversarial Games with Limited Teammate Communication. - Hardik Meisheri; Harshad Khadilkar (CoRR, 2020)

SIBRE: Self Improvement Based REwards for Adaptive Feedback in Reinforcement Learning. - Somjit Nath; Richa Verma; Abhik Ray; Harshad Khadilkar (AAMAS, 2021)

Revisiting State Augmentation methods for Reinforcement Learning with Stochastic Delays. - Somjit Nath; Mayank Baranwal; Harshad Khadilkar (CIKM, 2021)

Anticipatory Decisions in Retail E-Commerce Warehouses using Reinforcement Learning. - Omkar Shelke; Vinita Baniwal; Harshad Khadilkar (COMAD/CODS, 2021)

FoLaR: Foggy Latent Representations for Reinforcement Learning with Partial Observability. - Hardik Meisheri; Harshad Khadilkar (IJCNN, 2021)

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 (WSC, 2021)

School of hard knocks: Curriculum analysis for Pommerman with a fixed computational budget. - Omkar Shelke; Hardik Meisheri; Harshad Khadilkar (CoRR, 2021)

Fast Approximate Solutions using Reinforcement Learning for Dynamic Capacitated Vehicle Routing with Time Windows. - Nazneen N. Sultana; Vinita Baniwal; Ansuma Basumatary; Piyush Mittal; Supratim Ghosh; Harshad Khadilkar (CoRR, 2021)

Performance improvement of reinforcement learning algorithms for online 3D bin packing using FPGA. - Kavya Borra; Ashwin Krishnan; Harshad Khadilkar; Manoj Nambiar 001; Ansuma Basumatary; Rekha Singhal; Arijit Mukherjee (AIMLSystems, 2022)

Identifying efficient curricula for reinforcement learning in complex environments with a fixed computational budget. - Omkar Shelke; Hardik Meisheri; Harshad Khadilkar (COMAD/CODS, 2022)

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 (IJCNN, 2022)

A Novel Data Augmentation Technique for Out-of-Distribution Sample Detection Using Compounded Corruptions. - Ramya Hebbalaguppe; Soumya Suvra Ghosal; Jatin Prakash; Harshad Khadilkar; Chetan Arora 001 (ECML/PKDD (3), 2022)

A Learning Based Framework for Handling Uncertain Lead Times in Multi-Product Inventory Management. - Hardik Meisheri; Somjit Nath; Mayank Baranwal; Harshad Khadilkar (CoRR, 2022)

Solving the capacitated vehicle routing problem with timing windows using rollouts and MAX-SAT. - Harshad Khadilkar (CoRR, 2022)

A Novel Data Augmentation Technique for Out-of-Distribution Sample Detection using Compounded Corruptions. - Ramya S. Hebbalaguppe; Soumya Suvra Goshal; Jatin Prakash; Harshad Khadilkar; Chetan Arora 001 (CoRR, 2022)

Scalable multi-product inventory control with lead time constraints using reinforcement learning. - Hardik Meisheri; Nazneen N. Sultana; Mayank Baranwal; Vinita Baniwal; Somjit Nath; Satyam Verma; Balaraman Ravindran; Harshad Khadilkar (Neural Comput. Appl., 2022)

Follow your Nose: Using General Value Functions for Directed Exploration in Reinforcement Learning. - Durgesh Kalwar; Omkar Shelke; Somjit Nath; Hardik Meisheri; Harshad Khadilkar (AAMAS, 2023)

Classifier Design for Decentralised Sensing with Digital Communication. - Gauri Garg; Harshad Khadilkar; Ankur A. Kulkarni; Aditya A. Paranjape (CDC, 2023)

Using Contrastive Samples for Identifying and Leveraging Possible Causal Relationships in Reinforcement Learning. - Harshad Khadilkar; Hardik Meisheri (COMAD/CODS, 2023)

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 (COMAD/CODS, 2023)

Reinforcement Replaces Supervision: Query focused Summarization using Deep Reinforcement Learning. - Swaroop Nath; Pushpak Bhattacharyya; Harshad Khadilkar (EMNLP, 2023)

Supplementing Gradient-Based Reinforcement Learning with Simple Evolutionary Ideas. - Harshad Khadilkar (CoRR, 2023)

Using Linear Regression for Iteratively Training Neural Networks. - Harshad Khadilkar (CoRR, 2023)

Using General Value Functions to Learn Domain-Backed Inventory Management Policies. - Durgesh Kalwar; Omkar Shelke; Harshad Khadilkar (CoRR, 2023)

Multi-Agent Learning of Efficient Fulfilment and Routing Strategies in E-Commerce. - Omkar Shelke; Pranavi Pathakota; Anandsingh Chauhan; Harshad Khadilkar; Hardik Meisheri; Balaraman Ravindran (CoRR, 2023)

ORCHID: Offline RL for Control of HVAC in Buildings using Historical and Low-Fidelity Simulation Data. - Richa Verma; Srikar Babu Gadipudi; Srinarayana Nagarathinam; Harshad Khadilkar (AIMLSystems, 2024)

DCT: Dual Channel Training of Action Embeddings for Reinforcement Learning with Large Discrete Action Spaces. - Pranavi Pathakota; Hardik Meisheri; Harshad Khadilkar (AAMAS, 2024)

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 (COMAD/CODS, 2024)

Deep reinforcement learning approach for routing and scheduling of trains at railway station. - Sudhir R. Shetiya; Shripad Salsingikar; Harshad Khadilkar (COMAD/CODS (December), 2024)

Guiding Offline Reinforcement Learning Using a Safety Expert. - Richa Verma; Durgesh Kalwar; Harshad Khadilkar; Balaraman Ravindran (COMAD/CODS, 2024)

Linear-Time Optimal Deadlock Detection for Efficient Scheduling in Multi-Track Railway Networks. - Hastyn Doshi; Ayush Tripathi; Keshav Agarwal; Harshad Khadilkar; Shivaram Kalyanakrishnan (IJCAI, 2024)

Leveraging Domain Knowledge for Efficient Reward Modelling in RLHF: A Case-Study in E-Commerce Opinion Summarization. - Swaroop Nath; Tejpalsingh Siledar; Sankara Sri Raghava Ravindra Muddu; Rupasai Rangaraju; Harshad Khadilkar; Pushpak Bhattacharyya; Suman Banerjee; Amey Patil; Sudhanshu Shekhar Singh; Muthusamy Chelliah; Nikesh Garera (CoRR, 2024)

Transformers are Expressive, But Are They Expressive Enough for Regression? - Swaroop Nath; Harshad Khadilkar; Pushpak Bhattacharyya (CoRR, 2024)

DeepClean: Integrated Distortion Identification and Algorithm Selection for Rectifying Image Corruptions. - Aditya Kapoor; Harshad Khadilkar; Jayavardhana Gubbi (CoRR, 2024)

Agent-Temporal Credit Assignment for Optimal Policy Preservation in Sparse Multi-Agent Reinforcement Learning. - Aditya Kapoor; Sushant Swamy; Kale-ab Abebe Tessera; Mayank Baranwal; Mingfei Sun 001; Harshad Khadilkar; Stefano V. Albrecht (CoRR, 2024)

TAR2: Temporal-Agent Reward Redistribution for Optimal Policy Preservation in Multi-Agent Reinforcement Learning. - Aditya Kapoor; Kale-ab Abebe Tessera; Mayank Baranwal; Harshad Khadilkar; Stefano V. Albrecht; Limin Sun 001 (CoRR, 2025)