About

At the intersection of minds and machines

My research sits at the intersection of machine learning, robotics, and cognitive science. At Tufts, I study how passive brain signals can support implicit human-in-the-loop reinforcement learning.

Advised by Dr. Jivko Sinapov and Dr. Robert Jacob, I develop RL frameworks that align agent behavior with user goals and expectations through brain-computer interfaces (BCI).

  • Human-Robot Interaction
  • Brain-Computer Interfaces
  • Reinforcement Learning
  • Cognitive Science
Background

Path to Tufts

  • 2022–

    Joined Tufts as a Computer Science post-baccalaureate / Master’s student. As a DREAM Fellow, I began working in robotics and RL with Dr. Sinapov’s lab, where I am now a PhD candidate.

  • 2021

    Computational biology research intern at Michigan State University with Dr. Arjun Krishnan.

  • 2018–22

    B.S. in Neuroscience, Lafayette College. Undergraduate researcher in the BCI lab advised by Dr. Lisa Gabel and Dr. Yih-Choung Yu.

Selected work

Recent projects

Offline NEURO-LOOP

Brain signals for human-in-the-loop RL from an offline dataset

Mapping fNIRS to Agent Performance

Towards reinforcement learning from neural feedback

SpheroHunter

Tracking under occlusion in maze environments
Current work

Upcoming projects

NEURO-LOOP

Multimodal biosignals for human-in-the-loop RL in real-time