Sriram Ganapathi Subramanian

Assistant Professor, Computer Science, Carleton University

Joined

September 2020

Names

Sriram Ganapathi Subramanian (Preferred)

Emails

****@uwaterloo.ca (Confirmed)

****@vectorinstitute.ai (Confirmed)

****@cunet.carleton.ca (Confirmed)

Personal Links

Career & Education History

Assistant Professor

Computer Science, Carleton University (carleton.ca)

2025 – Present

Postdoc

Vector Institute (vectorinstitute.ai)

2022 – 2024

PhD student

Electrical and Computer Engineering, University of Waterloo (uwaterloo.ca)

2018 – 2022

MS student

Electrical and Computer Engineering, University of Waterloo (uwaterloo.ca)

2016 – 2018

Undergrad student

Remote Sensing, Anna University (annauniv.edu)

2012 – 2016

Advisors, Relations & Conflicts

Postdoc Advisor

Pascal Poupart

2022 – Present

Postdoc Advisor

Sheila Mcilraith

2022 – Present

PhD Advisor

Kate Larson

2018 – 2022

PhD Advisor

Mark Crowley

2016 – 2022

Expertise

multi agent systems

reinforcement learning

game theory

machine learning

2018 – Present

Publications

Learning to Negotiate via Voluntary Commitment
Shuhui Zhu, Baoxiang Wang, Sriram Ganapathi Subramanian, Pascal Poupart
- CoCoMARL 2025 Poster
- Readers: Everyone
Evaluating Generalization Capabilities of LLM-Based Agents in Mixed-Motive Scenarios Using Concordia
Chandler Smith, Marwa Abdulhai, Manfred Diaz, Marko Tesic, Rakshit Trivedi, Sasha Vezhnevets, Lewis Hammond, Jesse Clifton, Minsuk Chang, Edgar A. Duéñez-Guzmán, John P Agapiou, Jayd Matyas, Danny Karmon, Beining Zhang, Jim Dilkes, Akash Kundu, Jord Nguyen, Emanuel Tewolde, Jebish Purbey, Ram Mohan Rao Kadiyala et al. (66 additional authors not shown)
- NeurIPS 2025 Datasets and Benchmarks Track poster
- Readers: Everyone
Learning to Negotiate via Voluntary Commitment
Shuhui Zhu, Baoxiang Wang, Sriram Ganapathi Subramanian, Pascal Poupart
- AISTATS 2025 Poster
- Readers: Everyone
A Comprehensive Survey on Inverse Constrained Reinforcement Learning: Definitions, Progress and Challenges
Guiliang Liu, Sheng Xu, Shicheng Liu, Ashish Gaurav, Sriram Ganapathi Subramanian, Pascal Poupart
- Accepted by TMLR
- Readers: Everyone
How Useful is Intermittent, Asynchronous Expert Feedback for Bayesian Optimization?
Agustinus Kristiadi, Felix Strieth-Kalthoff, Sriram Ganapathi Subramanian, Vincent Fortuin, Pascal Poupart, Geoff Pleiss
- AABI 2024
- Readers: Everyone
Confidence Aware Inverse Constrained Reinforcement Learning
Sriram Ganapathi Subramanian, Guiliang Liu, Mohammed Elmahgiubi, Kasra Rezaee, Pascal Poupart
- ICML 2024 Poster
- Readers: Everyone
ChemGymRL: An Interactive Framework for Reinforcement Learning for Digital Chemistry
Chris Beeler, Sriram Ganapathi Subramanian, Kyle Sprague, Colin Bellinger, Mark Crowley, Isaac Tamblyn
- NeurIPS2023-AI4Science Poster
- Readers: Everyone
Demonstrating ChemGymRL: An Interactive Framework for Reinforcement Learning for Digital Chemistry
Chris Beeler, Sriram Ganapathi Subramanian, Kyle Sprague, Colin Bellinger, Mark Crowley, Isaac Tamblyn
- AI4Mat-2023 Poster
- Readers: Everyone
Two-Level Actor-Critic Using Multiple Teachers
Su Zhang, Srijita Das, Sriram Ganapathi Subramanian, Matthew E. Taylor
- Accepted by TMLR
- Readers: Everyone
Learning from Multiple Independent Advisors in Multi-agent Reinforcement Learning
Sriram Ganapathi Subramanian, Matthew E. Taylor, Kate Larson, Mark Crowley
- 2023 (modified: 17 Apr 2023)
- CoRR 2023
- Readers: Everyone

View all 30 publications

Co-Authors

View all 126 co-authors