Hi, and welcome!
I’m a Ph.D. candidate in computer science at the Multi-modal Learning, Interaction, and Perception (MuLIP) Lab at Tufts University, where I’m jointly advised by Professor Jivko Sinapov and Professor Matthias Scheutz. My research lies at the intersection of neuro-symbolic AI, reinforcement learning, and robotics—with a core focus on building intelligent agents that adapt and thrive effectively in dynamic, real-world environments.
Before Tufts, I completed my Master’s in Computer Science at Washington State University, where I worked on computer vision and machine learning for agricultural robotics under Professor Matthew E. Taylor. I also conducted research at the CASAS lab with Professor Diane J. Cook, developing AI systems in healthcare robotics.
Broadly, my goal is to create autonomous robots capable of handling the unexpected—machines that not only assist with everyday tasks but continuously learn and improve by observing our daily lives. I dream of a future where robots are not just tools, but intuitive lifelong collaborators in our homes and workplaces.
[May 2025]: I will attend ICRA-2025 in Atlanta, GA, and present our work on FLEX: A Framework for Learning Robot-Agnostic Force-based Skills Involving Sustained Contact Object Manipulation.
[January 2025]: I will attend AAAI-2025 in Philadelphia and present our work on a Neurosymbolic Cognitive Architecture for handling Open-World Novelty.
[December 2024]: I am collaborating with Professor Matthias Scheutz on an ONR (Naval Research) grant to develop force-based learning and RL methods that enable robots to adapt quickly to novel situations. For this work, we will use SPOT robots as testing platforms.
[October 2024]: We began work on a collaborative project with NASA, Tufts, UMass Amherst, and MIT focused on detecting and characterizing anomalies using drone flight systems.
[Summer 2024]: I am teaching Introduction to Data Structures to undergraduates and graduate students in the CS department at Tufts University.
[May 2024]: Our work on Novelgym: A Flexible Ecosystem for Hybrid Planning and Learning Agents Designed for Open Worlds was presented at AAMAS-2024 in Auckland, NZ.