Professors working in Multi-Agent Learning
Multi-Agent Learning, Professors
Hi there! 
I'm Rupali. I'm a second year Ph.D. student at Northeastern University, Boston supervised by
Chris Amato.
I find multi-agent problems very interesting and spend most of my time working on sovling such problems using reinforcement learning.
In my previous life, I completed my M.Sc. in Computer Science program at Université Laval and
Mila, Montreal
where my advisor was Audrey Durand.
My work during my masters focused on performative prediction in time series problems in healthcare and
I also spent some time working on problems in multi-agent reinforcement learning.
Previously, I worked as a Reinforcement Learning Consultant
and worked on several cool projects with many startups.
I also did some work on autonomous vehicles as a
Research Assistant at Indraprastha Institute of Technology Delhi
with Saket Anand.
I completed my B.Tech from Delhi Technological University with a major in Electronics and
Communication, where
S.Indu was my mentor.
On Stateful Value Factorization in Multi-Agent Reinforcement Learning
Enrico Marchesini, Andrea Baisero, Rupali Bhati, Christopher Amato
arXiv preprint
Scalable Approaches for a Theory of Many Minds
Maximilian P Touzel, Amin Memarian, Matthew D Riemer, Andrei Mircea, Andrew Robert Williams,
Elin Ahlstrand, Lucas Lehnert, Rupali Bhati, Guillaume Dumas, Irina Rish
Agentic Markets Workshop at ICML 2024
Curriculum Learning for Cooperation in Multi-Agent Reinforcement Learning
Rupali Bhati, SaiKrishna Gottipati, Cloderic Mars, Matthew E. Taylor
NeurIPS Agent Learning in Open-Endedness Workshop 2023
Performative Prediction in Time Series: A Case Study
Rupali Bhati, Jennifer Jones, Kristin Campbell, David Langelier, Anthony Reiman, Jonathan Greenland, Audrey Durand
NeurIPS Learning from Time Series for Health Workshop 2022
Summarizing Societies: Agent Abstraction in Multi-Agent Reinforcement Learning
Amin Memarian, Maximilian Puelma Touzel, Matthew D Riemer, Rupali Bhati, Irina Rish
ICLR From Cells to Societies: Collective Learning across Scales Workshop 2022
Interpret Your Care: Predicting the Evolution of Symptoms for Cancer Patients
Rupali Bhati, Jennifer Jones, Audrey Durand
AAAI Trustworthy AI for Healthcare Workshop 2022
CARL: Conditional-value-at-risk Adversarial Reinforcement Learning
Mathieu Godbout, Maxime Heuillet, Sharath Chandra, Rupali Bhati, Audrey Durand
AAAI Safe AI Workshop 2022
A Reinforcement Learning Approach to Jointly Adapt Vehicular Communications and Planning for Optimized Driving
Mayank K. Pal, Rupali Bhati, Anil Sharma, Sanjit K. Kaul, Saket Anand & P.B.Sujit
Intelligent Transportation Systems Conference 2018
News:
Jun 2024: Joined the MATS Program Cooperative AI stream working with Dr. Christian Schroeder de Witt.
Sep 2023: Awarded Khoury Distinguished Fellowship.
July 2023: First place for best Game AI Jam Project at the Summer School on AI and Games.
Sep 2022: Accepted to Google CS Research Mentorship 2022 Program.
May 2022: Nominated for Women in Artificial Intelligence Awards North America 2022.
Mar 2022: Awarded second place at Rendez-Vous IA Quebec 2022 with a cash prize of $1000.
Oct 2021: Abstract accepted at Montreal AI Symposium 2021.
About Me:
I'm a basketball fanatic and a Golden State Warriors supporter. I like to fiddle around with my drum set. Puzzles are my jam. I am a true believer of unicorns. 🦄
Recent posts
Paper Summary of Temporal Regularisation in Markov Decision Process [Thodoroff et al., 2018]
Summary of Temporal Regularisation in MDP by P.Thodoroff, A.Durand, J.Pineau, and D.Precup. Published at NeurIPS, 2018.
Professors working in Reinforcement Learning
Reinforcement Learning, Professors