About

I’m a Postdoctoral researcher at Brown University working with Serena Booth. My research involves leveraging insights from behavior science to improve how artificial agents assist human decision-makers. My daily toolkit includes (but is not limited to) reinforcement learning, user studies, and probabilistic models.

I completed my PhD in Computer Science at Harvard University and was co-advised by Finale Doshi-Velez and Susan Murphy.

Research

Publications

• When and Why Hyperbolic Discounting Matters for Reinforcement Learning Interventions. Ian M Moore, Eura Nofshin, Siddharth Swaroop, Susan Murphy, Finale Doshi-Velez, Weiwei Pan. Reinforcement Learning Journal 2025.
• Reinforcement Learning Interventions on Boundedly Rational Human Agents in Frictionful Tasks. Eura Nofshin, Siddharth Swaroop, Weiwei Pan, Susan Murphy, and Finale Doshi-Velez. International Conference on Autonomous Agents and Multiagent Systems 2024.
• AMBER: An Entropy Maximizing Environment Design Algorithm for Inverse Reinforcement Learning. Paul Nitschke, Lars Lien Ankile, Eura Shin, Siddharth Swaroop, Finale Doshi-Velez, Weiwei Pan. ICML Workshop on Models of Human Feedback for AI Alignment 2024. (Mentorship role).
• Online Model Selection by Learning how Compositional Kernels Evolve. Eura Shin, Predag Klasnja, Susan Murphy, and Finale Doshi-Velez. Transactions on Machine Learning Research 2023.
• Discovering User Types: Mapping User Traits by Task-Specific Behaviors in Reinforcement Learning Lars L. Ankile, Brian S. Ham, Kevin Mao, Eura Shin, Siddharth Swaroop, Finale Doshi-Velez, Weiwei Pan. ICML Workshop on AI and HCI 2023. Best paper nomination. (Mentorship role).
• Modeling Mobile Health Users as Reinforcement Learning Agents. Eura Shin, Siddharth Swaroop, Weiwei Pan, Susan Murphy, and Finale Doshi-Velez. AAAI Workshop on AI for Behavior Change 2023. Contributed talk.
• Online Structural Kernel Selection for Mobile Health. Eura Shin, Predag Klasnja, Susan Murphy, and Finale Doshi-Velez. ICML Workshop in Interpretable Machine Learning for Healthcare 2021.
• Design and Evaluation of a Hair Combing System Using a General-Purpose Robotic Arm. Nathaniel Dennler, Eura Shin, Maja Matarić, Stefanos Nikolaidis. International Conference on Intelligent Robots and Systems (IROS) 2021.
• Untangling the seasonal dynamics of plant-pollinator communities. Bernat Bramon Mora, Eura Shin, Paul J CaraDonna, Daniel B Stouffer. Nature Communications 2020.

Invited Talks

• “Modeling mHealth Users for AI Interventions”. Biodesign Lab, Harvard University, July 2023.
• Invited Talk at “AI for health behavior change” workshop. Persuasive Technology conference, Eindhoven, April 2023.

Teaching and Mentorship

I am a teaching fellow and course developer for CS290A & CS290B: Effective Research Practices & Academic Culture (Fall 2022 - Spring 2023). We are currently working on making the teaching materials available online. In Spring 2022, I served as a teaching fellow for STAT234: Sequential Decision Making.

I serve as a direct research mentor for a number of undergraduate and master’s students in the intersection of reinforcement learning and human-computer interaction.

I’ve developed the material for a number of guest lectures on Machine Learning, Reinforcement Learning, and Research Skills:

• How to conduct a literature search. CS290 Fall 2022. Detailed course plan here and guide here.
• Hieararchical Reinforcement Learning. STAT234 Spring 2022. Slides here.

Outreach

Leadership I was one of the founding member of the University of Kentucky ACM-W chapter. During this time, I created a series of introductory CS workshops for high-school students from counties in Kentucky without a computer science class/program.

Talks and workshops

• I was a mentor for the Women in Data Science (WiDS) Cambridge datathon workshop in Spring 2020.
• I gave a joint talk titled “What is Machine Learning?” at Harvard’s WECode 2023.