Elastance control of a mock circulatory system for ventricular assist device test. - Yih-Choung Yu; Sriram Gopalakrishnan (ACC, 2009)

Automated learning of hierarchical task networks for controlling minecraft agents. - Chanh Nguyen; Noah Reifsnyder; Sriram Gopalakrishnan; Héctor Muñoz-Avila (CIG, 2017)

Recognizing Plans by Learning Embeddings from Observed Action Distributions. - Yantian Zha; Yikang Li 001; Sriram Gopalakrishnan; Baoxin Li; Subbarao Kambhampati (AAMAS, 2018)

Learning task hierarchies using statistical semantics and goal reasoning. - Sriram Gopalakrishnan; Héctor Muñoz-Avila; Ugur Kuter (AI Commun., 2018)

TGE-viz : Transition Graph Embedding for Visualization of Plan Traces and Domains. - Sriram Gopalakrishnan; Subbarao Kambhampati (CoRR, 2018)

Embedding Directed Graphs in Potential Fields Using FastMap-D. - Sriram Gopalakrishnan; Liron Cohen 002; Sven Koenig; T. K. Satish Kumar (SOCS, 2020)

Let Me At Least Learn What You Really Like: Dealing With Noisy Humans When Learning Preferences. - Sriram Gopalakrishnan; Utkarsh Soni (CoRR, 2020)

Model Minimization For Online Predictability. - Sriram Gopalakrishnan; Subbarao Kambhampati (CoRR, 2020)

Goal recognition via model-based and model-free techniques. - Daniel Borrajo; Sriram Gopalakrishnan; Vamsi K. Potluru (CoRR, 2020)

Integrating Planning, Execution and Monitoring in the presence of Open World Novelties: Case Study of an Open World Monopoly Solver. - Sriram Gopalakrishnan; Utkarsh Soni; Tung Thai; Panagiotis Lymperopoulos; Matthias Scheutz; Subbarao Kambhampati (CoRR, 2021)

Synthesizing Policies That Account For Human Execution Errors Caused By State-Aliasing In Markov Decision Processes. - Sriram Gopalakrishnan; Mudit Verma; Subbarao Kambhampati (CoRR, 2021)

Assignment and Prioritization of Tasks with Uncertain Durations for Satisfying Makespans in Decentralized Execution. - Sriram Gopalakrishnan; Daniel Borrajo (ICAPS, 2022)

Minimizing Robot Navigation Graph for Position-Based Predictability by Humans. - Sriram Gopalakrishnan; Subbarao Kambhampati (AAMAS, 2022)

pyRDDLGym: From RDDL to Gym Environments. - Ayal Taitler; Michael Gimelfarb; Sriram Gopalakrishnan; Xiaotian Liu; Scott Sanner (CoRR, 2022)

Methods and Mechanisms for Interactive Novelty Handling in Adversarial Environments. - Tung Thai; Mudit Verma; Utkarsh Soni; Sriram Gopalakrishnan; Ming Shen; Mayank Garg; Ayush Kalani; Nakul Vaidya; Neeraj Varshney; Chitta Baral; Subbarao Kambhampati; Jivko Sinapov; et al. (AAMAS, 2023)

Multi-Modal Financial Time-Series Retrieval Through Latent Space Projections. - Tom Bamford; Andrea Coletta; Elizabeth Fons; Sriram Gopalakrishnan; Svitlana Vyetrenko; Tucker Balch; Manuela Veloso (ICAIF, 2023)

Refined F5 Algorithms for Ideals of Minors of Square Matrices. - Sriram Gopalakrishnan; Vincent Neiger; Mohab Safey El Din (ISSAC, 2023)

On the Constrained Time-Series Generation Problem. - Andrea Coletta; Sriram Gopalakrishnan; Daniel Borrajo; Svitlana Vyetrenko (NeurIPS, 2023)

Refined $F_5$ Algorithms for Ideals of Minors of Square Matrices. - Sriram Gopalakrishnan; Vincent Neiger; Mohab Safey El Din (CoRR, 2023)

Methods and Mechanisms for Interactive Novelty Handling in Adversarial Environments. - Tung Thai; Ming Shen; Mayank Garg; Ayush Kalani; Nakul Vaidya; Utkarsh Soni; Mudit Verma; Sriram Gopalakrishnan; Chitta Baral; Subbarao Kambhampati; Jivko Sinapov; Matthias Scheutz (CoRR, 2023)

SafeAR: Towards Safer Algorithmic Recourse by Risk-Aware Policies. - Haochen Wu; Shubham Sharma; Sunandita Patra; Sriram Gopalakrishnan (CoRR, 2023)

SafeAR: Safe Algorithmic Recourse by Risk-Aware Policies. - Haochen Wu; Shubham Sharma; Sunandita Patra; Sriram Gopalakrishnan (AAAI, 2024)

Optimized Gröbner basis algorithms for maximal determinantal ideals and critical point computations. - Sriram Gopalakrishnan; Vincent Neiger; Mohab Safey El Din (ISSAC, 2024)

Synthetic Data Applications in Finance. - Vamsi K. Potluru; Daniel Borrajo; Andrea Coletta; Niccolò Dalmasso; Yousef El-Laham; Elizabeth Fons; Mohsen Ghassemi; Sriram Gopalakrishnan; Vikesh Gosai; Eleonora Kreacic; Ganapathy Mani; Saheed Obitayo; et al. (CoRR, 2024)

On the arithmetic complexity of computing Gröbner bases of comaximal determinantal ideals. - Sriram Gopalakrishnan (CoRR, 2024)

TRIP-PAL: Travel Planning with Guarantees by Combining Large Language Models and Automated Planners. - Tomás de la Rosa; Sriram Gopalakrishnan; Alberto Pozanco; Zhen Zeng; Daniel Borrajo (CoRR, 2024)

On Learning Action Costs from Input Plans. - Marianela Morales; Alberto Pozanco; Giuseppe Canonaco; Sriram Gopalakrishnan; Daniel Borrajo; Manuela Veloso (CoRR, 2024)

Robust and Efficient Fine-tuning of LLMs with Bayesian Reparameterization of Low-Rank Adaptation. - Ayan Sengupta; Vaibhav Seth; Arinjay Pathak; Natraj Raman; Sriram Gopalakrishnan; Tanmoy Chakraborty 002 (CoRR, 2024)

Robust and Efficient Fine-tuning of LLMs with Bayesian Reparameterization of Low-Rank Adaptation. - Vaibhav Seth; Ayan Sengupta; Arinjay Pathak; Aastha A K. Verma; Natraj Raman; Sriram Gopalakrishnan; Niladri Chatterjee; Tanmoy Chakraborty 002 (Trans. Mach. Learn. Res., 2025)

QBD-RankedDataGen: Generating Custom Ranked Datasets for Improving Query-By-Document Search Using LLM-Reranking with Reduced Human Effort. - Sriram Gopalakrishnan; Sunandita Patra (CoRR, 2025)

GenPlanX. Generation of Plans and Execution. - Daniel Borrajo; Giuseppe Canonaco; Tomás de la Rosa; Alfredo Garrachón Ruiz; Sriram Gopalakrishnan; Simerjot Kaur; Marianela Morales; Sunandita Patra; Alberto Pozanco; Keshav Ramani; Charese Smiley; Pietro Totis; et al. (CoRR, 2025)