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 production pipelines in systematic trading at Two Sigma, deep learning/computer vision applications at Cognex, and reinforcement learning and robotics research during my internship at NVIDIA, undergrad, master’s.

I have also been a 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 as well as intern at NVIDIA and Cognex.

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, Finance, and Healthcare.

I’ve just started writing about my thoughts. 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

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Outside of Computer Science, I do things like teaching Taekwondo at Columbia and rock climbing.