Refereed Conferences/ Journals/ Workshop/ Technical Magazine Articles

• Mitigating Side Effects in Multi-Agent Systems Using Blame Assignment
Pulkit Rustagi, Sandhya Saisubramanian. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2025.
• Multi-Objective Planning with Contextual Lexicographic Reward Preferences
Pulkit Rustagi, Yashwanthi Anand , Sandhya Saisubramanian. Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2025.
• Verification and Validation of AI Systems Using Explanations
Saaduddin Mahmud, Sandhya Saisubramanian, Shlomo Zilberstein. In AAAI Fall Symposium on AI Trustworthiness and Risk Assessment for Challenging Contexts (ATRACC), 2024.
• Adaptive Feedback Selection for Learning to Avoid Negative Side Effects in Autonomous Agents
Yashwanthi Anand, Sandhya Saisubramanian. In Workshop on Reinforcement Learning Beyond Rewards, Reinforcement Learning Conference (RLC), 2024.
• User-Aligned Assessment of Agent Learning and Operation for Reliable Autonomy
Sandhya Saisubramanian. In AAAI Spring Symposium on User-Aligned Assessment of Adaptive AI Systems, 2024.
• Minimizing Negative Side Effects in Cooperative Multi-Agent Systems using Distributed Coordination
Moumita Choudhury, Sandhya Saisubramanian, Hao Zhang, Shlomo Zilberstein. In Proceedings of the 37th International FLAIRS Conference, 2024.
*Also appeared as an extended abstract in proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2024.
• Explanation-Guided Reward Alignment
Saaduddin Mahmud, Sandhya Saisubramanian, Shlomo Zilberstein. In Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI), 2023.
• REVEALE: Reward Verification and Learning Using Explanations
Saaduddin Mahmud, Sandhya Saisubramanian, Shlomo Zilberstein. AAAI Workshop on Artificial Intelligence Safety, 2023. Nominated for Best Paper Award.
• Planning and Learning for Non-Markovian Negative Side Effects using Finite State Controllers
Aishwarya Srivastava, Sandhya Saisubramanian, Praveen Paruchuri, Akshat Kumar, Shlomo Zilberstein. In Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI), 2023.
• Avoiding Negative Side Effects of Autonomous Systems in the Open World
Sandhya Saisubramanian, Ece Kamar, Shlomo Zilberstein. In the Journal of Artificial Intelligence Research (JAIR), 2022.
• Metareasoning for Safe Decision Making in Autonomous Systems
Justin Svegliato, Connor Basich, Sandhya Saisubramanian, Shlomo Zilberstein. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2022.
• Avoiding Negative Side Effects due to Incomplete Knowledge of AI Systems
Sandhya Saisubramanian, Shlomo Zilberstein, Ece Kamar. AI Magazine Winter 2022 edition, 2022.
• Learning to Generate Fair Clusters from Demonstrations
Sainyam Galhotra, Sandhya Saisubramanian, Shlomo Zilberstein. In Proceedings of AAAI/ACM Conference on Artificial Intelligence, Ethics and Society (AIES), 2021.
• Understanding User Attitudes Towards Negative Side Effects of AI Systems
Sandhya Saisubramanian, Shannon C. Roberts, Shlomo Zilberstein. In Proceedings of the ACM CHI Conference on Human Factors in Computing Systems, Late-Breaking Work Track, 2021.
• Mitigating Negative Side Effects via Environment Shaping (Extended Abstract)
Sandhya Saisubramanian, Shlomo Zilberstein. In Proceedings of the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2021. [full paper].
• Using Metareasoning to Maintain and Restore Safety for Reliably Autonomy
Justin Svegliato, Connor Basich, Sandhya Saisubramanian, Shlomo Zilberstein. IJCAI Workshop on Robust and Reliable Autonomy in the Wild (R2AW), 2021.
• Identifying Missing Features in State Representation for Safe Decision-Making
Minori Narita, Sandhya Saisubramanian, Roderic A. Grupen, Shlomo Zilberstein. ICML Workshop on Human-AI Collaboration in Sequential Decision-Making, 2021.
• A Multi-Objective Approach to Mitigate Negative Side Effects
Sandhya Saisubramanian, Ece Kamar, Shlomo Zilberstein. In Proceedings of 29th International Joint Conference on Artificial Intelligence (IJCAI), 2020. Distinguished paper award.
• Balancing the Tradeoff Between Clustering Value and Interpretability
Sandhya Saisubramanian*, Sainyam Galhotra*, Shlomo Zilberstein. In Proceedings of AAAI/ACM Conference on Artificial Intelligence, Ethics and Society (AIES), 2020.
(* equal contribution)
• Efficient Integration of Complementary Solvers for Quantum Circuit Compilation
Sandhya Saisubramanian, Minh Do, Jeremy Frank, Shlomo Zilberstein. ICAPS Workshop on Scheduling and Planning Applications (SPARK), 2020.
• Satisfying Social Preferences in Ridesharing Services
Sandhya Saisubramanian, Connor Basich, Shlomo Zilberstein, Claudia Goldman. In Proceedings of IEEE Intelligent Transportation Systems Conference (ITSC), 2019.
• Adaptive Outcome Selection for Planning With Reduced Models
Sandhya Saisubramanian, Shlomo Zilberstein. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019.
• Planning in Stochastic Environments with Goal Uncertainty
Sandhya Saisubramanian, Kyle Hollins Wray, Luis Pineda, Shlomo Zilberstein. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019.
• The Value of Incorporating Social Preferences in Dynamic Ridesharing
Sandhya Saisubramanian, Connor Basich, Shlomo Zilberstein, Claudia Goldman. ICAPS Workshop on Scheduling and Planning Applications (SPARK), 2019.
• Minimizing the Negative Side Effects of Planning with Reduced Models
Sandhya Saisubramanian, Shlomo Zilberstein. AAAI Workshop on Artificial Intelligence Safety, 2019.
• Planning Using a Portfolio of Reduced Models (Extended Abstract)
Sandhya Saisubramanian, Shlomo Zilberstein, Prashant Shenoy. In Proceedings of 17th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2018.
• Safe Reduced Models for Probabilistic Planning
Sandhya Saisubramanian, Shlomo Zilberstein. ICML/IJCAI/AAMAS Workshop on Planning and Learning (PAL), 2018.
• Optimizing Electric Vehicle Charging Through Determinization
Sandhya Saisubramanian, Shlomo Zilberstein, Prashant Shenoy. ICAPS Workshop on Scheduling and Planning Applications (SPARK), 2017.
• Risk Based Optimization for Emergency Medical Systems
Sandhya Saisubramanian, Pradeep Varakantham, Hoong Chuin Lau. In Proceedings of 29th AAAI Conference on Artificial Intelligence (AAAI), 2015.
• STREETS: Game-Theoretic Traffic Patrolling with Exploration and Exploitation
Matthew Brown, Sandhya Saisubramanian, Pradeep Varakantham, Milind Tambe. In Proceedings of Innovative Applications in Artificial Intelligence (IAAI) at 28th AAAI Conference on Artificial Intelligence, 2014.

Thesis

• Reliable Decision-Making with Imprecise Models (Doctoral Dissertation)

Sandhya Saisubramanian, University of Massachusetts Amherst.