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Hi there! :wave:
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I'm Rupali. I'm a second year Ph.D. student at Northeastern University, Boston supervised by 
<a href="https://www.khoury.northeastern.edu/home/camato/#__utma=72955916.1937711.1696964788.1701737035.1701752961.25&__utmb=72955916.1.10.1701752961&__utmc=72955916&__utmx=-&__utmz=72955916.1701752961.25.8.utmcsr=google|utmccn=(organic)|utmcmd=organic|utmctr=(not%20provided)&__utmv=-&__utmk=18192703">Chris Amato.</a>
I find multi-agent problems 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 
<a href="https://mila.quebec/en/">Mila, Montreal</a> 
where my advisor was <a href="https://audur2.ift.ulaval.ca/">Audrey Durand.</a> 
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.
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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 <a href="https://www.iiitd.ac.in/anands"> Saket Anand</a>. 
I completed my B.Tech from Delhi Technological University with a major in Electronics and 
Communication, where 
<a href="https://dtu.irins.org/profile/66967">S.Indu</a> was my mentor. <br />
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<strong>Publications:</strong> <br />
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    <a href="https://openreview.net/pdf?id=NAQ9dxRpx3">
      Decentralized Asymmetric DQN: Decentralization without Factorization in Multi-Agent Reinforcement Learning </a> <br />
      <strong>Rupali Bhati*</strong>, Anurag Kadkol*, Andrea Baisero, Christopher Amato(*= equal contribution)<br />
  <i>RLC 2026</i>
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    <a href="https://openreview.net/pdf?id=r7bBk4Gkhx">
      Fixing Incomplete Value Function Decomposition for Multi-Agent Reinforcement Learning </a> <br />
      Andrea Baisero,<strong>Rupali Bhati</strong>, Shuo Liu, Aathira Sunil Pillai, Christopher Amato<br />
  <i>RLC 2026</i>
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    <a href="https://openreview.net/attachment?id=E9whrbtgUA&name=pdf">
      The Influence of Scaffolds on Coordination Scaling Laws in LLM Agents </a> <br />
      <strong>Rupali Bhati*</strong>, Mariana Meireles*, Niklas Lauffer†, Cameron Allen† (*= equal contribution, † equal advising)<br />
  <i>NeurIPS 2025 Scaling Environments for Agents Workshop</i>
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    <a href="https://arxiv.org/abs/2408.15381">
      On Stateful Value Factorization in Multi-Agent Reinforcement Learning</a> <br />
      Enrico Marchesini, Andrea Baisero,  <strong>Rupali Bhati</strong>, Christopher Amato <br />
  <i>AAMAS 2025</i>
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    <a href="https://cancer.jmir.org/2025/1/e74123/">
      Use of an Integrated Knowledge Translation Approach to Develop an Electronic Patient-Reported Outcome 
      System for Cancer Rehabilitation: Tutorial</a> <br />
      Christian Lopez, Sarah E Neil-Sztramko, Kristin L Campbell, David M Langelier, Tran Truong, 
      Yuliya Gavrylyuk, Pia Nyakairu, Laura Parente, Audrey Durand, Jackie L Bender, Gillian Strudwick, 
      <strong>Rupali Bhati</strong>, Jonathan Greenland, Tony Reiman, Jennifer M Jones<br />
  <i>JMIR Cancer 2025</i>
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    <a href="https://openreview.net/forum?id=P0oG5gDh6T">
      Scalable Approaches for a Theory of Many Minds</a> <br />
      Maximilian P Touzel, Amin Memarian, Matthew D Riemer, Andrei Mircea, Andrew Robert Williams,
      Elin Ahlstrand, Lucas Lehnert, <strong>Rupali Bhati</strong>, Guillaume Dumas, Irina Rish <br />
  <i>Agentic Markets Workshop at ICML 2024</i>
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    <a href="https://nips.cc/virtual/2023/79180">
      Curriculum Learning for Cooperation in Multi-Agent Reinforcement Learning</a> <br />
    <strong>Rupali Bhati</strong>, SaiKrishna Gottipati, Cloderic Mars, Matthew E. Taylor <br />
  <i>NeurIPS Agent Learning in Open-Endedness Workshop 2023</i>
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    <a href="https://openreview.net/forum?id=5PfL2FAfWG">
      Performative Prediction in Time Series: A Case Study</a> <br />
    <strong>Rupali Bhati</strong>, Jennifer Jones, Kristin Campbell, David Langelier, Anthony Reiman, Jonathan Greenland, Audrey Durand <br />
  <i>NeurIPS Learning from Time Series for Health Workshop 2022</i>
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  <a href="https://openreview.net/pdf?id=Sc9ESMyTZ9">
    Summarizing Societies: Agent Abstraction in Multi-Agent Reinforcement Learning</a> <br />
    Amin Memarian, Maximilian Puelma Touzel, Matthew D Riemer, <strong>Rupali Bhati</strong>, Irina Rish <br />
  <i>ICLR From Cells to Societies: Collective Learning across Scales Workshop 2022</i>
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<a href="https://drive.google.com/file/d/1eKKCIWBTzmwJIyuiqLR1fikDLmUz9F1H/view?usp=sharing">
  Interpret Your Care: Predicting the Evolution of Symptoms for Cancer Patients</a> <br />
  <strong>Rupali Bhati</strong>, Jennifer Jones, Audrey Durand <br />
<i>AAAI Trustworthy AI for Healthcare Workshop 2022</i>
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<a href="https://arxiv.org/pdf/2109.09470.pdf">
  CARL: Conditional-value-at-risk Adversarial Reinforcement Learning</a> <br />
  Mathieu Godbout, Maxime Heuillet, Sharath Chandra, <strong>Rupali Bhati</strong>, Audrey Durand  <br />
<i>AAAI Safe AI Workshop 2022</i>
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<a href="https://ieeexplore.ieee.org/abstract/document/8569484">
A Reinforcement Learning Approach to Jointly Adapt Vehicular Communications and Planning for Optimized Driving</a> <br />
Mayank K. Pal, <strong>Rupali Bhati</strong>, Anil Sharma, Sanjit K. Kaul, Saket Anand & P.B.Sujit <br />
<i>Intelligent Transportation Systems Conference 2018</i>
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<strong>News:</strong> <br />
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  <ins>May 2025</ins>: Started <a href="https://humancompatible.ai/">CHAI</a> internship with <a href="https://niklaslauffer.github.io/">Niklas Lauffer</a>.<br />
  <ins>Jun 2024</ins>: Joined the <a href="https://www.matsprogram.org/">
    MATS Program</a> Cooperative AI stream working with Dr. Christian Schroeder de Witt.<br />
  <!-- <ins>Nov 2023</ins>: Awarded Scholarship for NeurIPS registration by ALOE Workshop.<br /> -->
  <!-- <ins>Oct 2023</ins>:  -->
  <!-- <ins>"Curriculum Learning for Cooperation in Multi-Agent Reinforcement Learning"</ins> accepted at  -->
  <!-- <a href="https://sites.google.com/view/aloe2023/home"> -->
    <!-- Agent Learning in Open-Endedness Workshop</a> at NeurIPS 2023.<br /> -->
  <ins>Sep 2023</ins>: Awarded Khoury Distinguished Fellowship.<br />
  <!-- <ins>Sep 2023</ins>: Started Ph.D. at Northeastern University.<br /> -->
  <ins>July 2023</ins>: First place for best Game AI Jam Project at the Summer School on AI and Games. <br />
  <!-- <ins>May 2023</ins>: Awarded Scholarship to attend the 
   <a href="https://www.cooperativeai.com/summer-school/2023">
    Cooperative AI Summer School.</a> <br /> -->
  <!-- <ins>Apr 2023</ins>: Awarded Sony Interactive Entertainment Scholarship to attend the 
   <a href="https://school.gameaibook.org/#:~:text=The%205th%20International%20Summer%20School,at%20the%20Microsoft%20Research%20Campus!">
    Summer School on AI and Games.</a> <br /> -->
  <!-- <ins>Jan 2023</ins>: Started internship at AI Redefined working with <a href="https://drmatttaylor.net/">
    Matthew E. Taylor.</a> <br /> -->
  <!-- <ins>Oct 2022</ins>: 
  <ins>"Performative Prediction in Time Series: A Case Study"</ins> accepted at 
    Learning from Time Series for Health Workshop at NeurIPS 2022.<br /> -->
  <ins>Sep 2022</ins>: Accepted to <a href="https://research.google/outreach/csrmp/">
    Google CS Research Mentorship 2022 Program.</a><br />
  <ins>May 2022</ins>: Nominated for <a href="https://www.womeninai.co/waiawardsna">
    Women in Artificial Intelligence Awards North America 2022.</a><br />
  <!-- <ins>Mar 2022</ins>: <a href="https://openreview.net/pdf?id=Sc9ESMyTZ9">
    "Summarizing Societies: Agent Abstraction in Multi-Agent Reinforcement Learning "</a> accepted at
    ICLR From Cells to Societies: Collective Learning across Scales Workshop 2022. <br /> -->
  <ins>Mar 2022</ins>: Awarded second place at 
  <a href="https://www.quebecinternational.ca/en/rendez-vous-ia"> Rendez-Vous IA Quebec 2022</a> with 
  a cash prize of $1000. <br />
  <!-- <ins>Dec 2021</ins>: <a href="https://taih21.github.io/CameraReady/20/CameraReady/Bhati.pdf">
  "Interpret Your Care: Predicting the Evolution of Symptoms for Cancer Patients"</a> accepted at
  Trustworthy AI for Healthcare Workshop at AAAI 2022.<br />
  <ins>Dec 2021</ins>: <a href="https://arxiv.org/pdf/2109.09470.pdf">
    "CARL: Conditional-value-at-risk Adversarial Reinforcement Learning"</a> accepted at
    Safe AI Workshop at AAAI 2022.<br /> -->
  <ins>Oct 2021</ins>: Abstract accepted at Montreal AI Symposium 2021. <br />
  <!-- <ins>Sep 2020</ins>: Joined the M.Sc. in Computer Science program at Université Laval. <br /> -->
  <!-- <ins>July 2019</ins>: Attended <a href="https://rlss.inria.fr/">Reinforcement Learning Summer School, Lille, France</a> -->
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<strong>About Me:</strong> <br />
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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. 🦄
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