I am a founding engineer at a full-stack AI startup called Pillar Advisors working on LLM, agentic, and machine learning-enabled automation within professional services including Tax and Accounting.
Previously, I have worked as a Machine Learning Engineer on topics ranging from large scale machine learning and model-based planning in systematic trading at Two Sigma, deep learning/computer vision, and reinforcemment learning from human feedback (RLHF) at Cognex, and academic research in reinforcement learning and robotics during my internship at NVIDIA, undergrad, master’s at Brown University.
I have also been an independent researcher at MLCollective, a non-profit machine learning research lab.
I graduated my Master’s in Computer Science at Brown University, supervised by George Konidaris, Stefanie Tellex, and James Tompkin, in May 2020. Previously, I was an undergraduate student at Brown University.
My goal is to research, develop, and create embodied Artificial Intelligence/Machine Learning algorithms and systems. My interests include (but are not limited to) Reinforcement Learning (RL), Planning/Reasoning, and Generative/World Modeling, with applications to real-world domains such as Robotics and Finance.
Check out my blog.
Publications
Visual Transfer for Reinforcement Learning via Wasserstein Domain Confusion
First Author, AAAI 2021
Advanced Autonomy on a Low-Cost Educational Platform
Robocup Best Paper Finalist, IROS 2019
PiDrone: An Autonomous Educational Drone using Raspberry Pi and Python
First Author, IROS 2018
Awards
Two Sigma Internal AI/LLM Hackathon Best Project
2023
National Science Foundation Graduate Research Fellowship (NSF GRFP)
Wrote about Uncertainty Quantification, Honorable Mention, 2020
RoboCup Best Paper Finalist
IROS 2019
Sigma Xi Scientific Research Honor Society
Elected 2019
Senior Prize and Academic Honors in Computer Science
Brown University, 2019
Michael Black Teaching Assistantship Award
Brown University, 2019
Outside of Computer Science, I teach Taekwondo at Columbia and climb rocks.