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publications
Exploiting Relational Planning and Task-Specific Abstractions for Multiagent Reinforcement Learning in Relational Domains
Published in Cooperative Multi-Agent Systems Decision-Making and Learning Workshop, 2024
This is the workshop version of the MaRePReL framework published later.
Recommended citation: Singh, Ranveer, Nikhilesh Prabhakar, Sriraam Natarajan, and Prasad Tadepalli. "Exploiting Relational Planning and Task-Specific Abstractions for Multiagent Reinforcement Learning in Relational Domains." (2024).
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Combining Planning and Reinforcement Learning for Solving Relational Multiagent Domains
Published in AAMAS, 2025
This paper is about solving relational multiagent domains using MaRePReL.
Recommended citation: Nikhilesh Prabhakar, Ranveer Singh, Harsha Kokel, Sriraam Natarajan, and Prasad Tadepalli. 2025. Combining Planning and Reinforcement Learning for Solving Relational Multiagent Domains. In Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems (AAMAS '25). International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC, 1708–1717.
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LLM-Guided Causal Bayesian Network Construction for Pediatric Patients on ECMO
Published in Artificial Intelligence in Medicine, 2025
Combining LLMs with data refinement on data of pediatric patients on ECMO to learn Causal Bayesian Network for Patients on ECMO
Recommended citation: Mathur, S. et al. (2025). LLM-Guided Causal Bayesian Network Construction for Pediatric Patients on ECMO. In: Bellazzi, R., Juarez Herrero, J.M., Sacchi, L., Zupan, B. (eds) Artificial Intelligence in Medicine. AIME 2025. Lecture Notes in Computer Science(), vol 15735. Springer, Cham. https://doi.org/10.1007/978-3-031-95841-0_48
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LLMs for Causal Reasoning in Medicine? A Call for Caution
Published in IJCAI workshop on User-Aligned Assessment of Adaptive AI Systems, 2025
This is the workshop version of the manuscript published at CODS 2025
Recommended citation: Mathur, Saurabh, Ranveer Singh, Michael Skinner, Predrag Radivojac, David M. Haas, Lakshmi Raman, and Sriraam Natarajan. "LLMs for Causal Reasoning in Medicine? A Call for Caution." In IJCAI 2025 Workshop on User-Aligned Assessment of Adaptive AI Systems.
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EHR Sampling Interval Bias Detection and Burden of Blood Pressure Excursions: Implications for Clinical Decision Support and Model Validity in Pediatric ECMO
Published in Information, 2026
The difference in Hypotension and Hypertension for patients on ECMO across different sampling rates
Recommended citation: Shah, Neel, Ethan Sanford, David R. Busch, Ranveer Singh, Saurabh Mathur, Jayesh Sharma, Philip Reeder, Sriraam Natarajan, and Lakshmi Raman. 2026. "EHR Sampling Interval Bias Detection and Burden of Blood Pressure Excursions: Implications for Clinical Decision Support and Model Validity in Pediatric ECMO" Information 17, no. 2: 135. https://doi.org/10.3390/info17020135
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talks
Talk 1 on Relevant Topic in Your Field
Published:
This is a description of your talk, which is a markdown file that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
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This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Student Intern
Undergraduate, Fintricks Consultancy Services, 2019
Worked as a student intern at Fintricks, a local Delhi trading firm, to develop statistical models to select better mutual fund policies using temporal modelling of high-frequency stock data. Additionally, worked on converting MS Excel-based workloads to ones based on SQL for better integration with Python and other scripting languages.
Teaching Assistant
PhD, The University of Texas at Dallas, Computer Science Department., 2021
Worked as a Teaching Assistant for CS 4141 Digital Logic Lab, where I conducted lab sessions, taught and demonstrated experiments along with their underlying concepts, and graded student work. Instructed over 800 students over two years.
Research Assistant
PhD, The University of Texas at Dallas, Computer Science Department., 2023
Working as an RA as part of my PhD. I have been funded by the NIH, primarily focusing on clinical AI in data-scarce domains.