I'm an undergraduate Computer Science student at UC Berkeley
where I had the pleasure of being advised by Professor Trevor Darrell and Dr. Amir Bar.
I'm interested in computer vision, robotics, and deep learning. I am primarily interested in enabling high level planning for robotics. Some of my work is highlighted below.
We present EgoPet, a new egocentric video dataset of animals. We create a variety of tasks to learn from animals such as Visual Interaction Prediction, Locomotion Prediction, and Vision to Proprioception.
Class Projects
EgoPet Locomotion Prediction Text-Conditioned Extension
Spring 2024
PDF
CS280 is the graduate computer vision course at UC Berkeley. For my CS280 final project, I worked on a text-conditioned extension to the Locomotion Prediction task in my EgoPet paper.
Efficient Mitigation of Bus Bunching through Setter-Based Curriculum Learning
Fall 2023
PDF
CS285 is the graduate Deep Reinforcement Learning course at UC Berkeley. For my CS285 final project, I worked on implementing various deep-reinforcement learning algorithms for learning a bus policy to avoid bus bunching. I explored the impact of Domain Randomization on training such a policy.
Using Deep Learning to Distinguish Facial Bone Structure of Genders
Fall 2022
CS182 is the Deep Learning course at UC Berkeley. Designed a deep neural network for classifying gender from CT scans, achieving an accuracy of approximately 80%. Implemented and analyzed Grad-Cam visualizations in order to determine facial features.
As an academic intern for CS61B, the Data Structures and Algorithms course at UC Berkeley, I aided students during lab and office hours on various projects and homework. Created lab slides and code demonstrations which I presented in lab.
Website template taken from Jon Barron at source code. Thank you!