• 3.91/4.00 GPA in the last two years of study
• Activities: WATonomous: Self-Driving Car Design Team
• Relevant Coursework: Distributed Computing, Reinforcement Learning, Concurrent Programming, Operating Systems, Computational Statistics, Optimization, Databases, Machine Learning, Algorithms

September 2022 - December 2022

Worked on the Path Perception team of the Autonomous Vehicles division. Specifically, I worked on helping the team with improvements to the PathNet DNN. See the following video of PathNet in action:

May 2021 - August 2021, January 2022 - May 2022 (Return intern)

Worked on the Parking Perception team of the Autonomous Vehicles division. Specifically, I worked on helping the team with improvements to the ParkNet DNN. See the following video of ParkNet in action:

December 2018 - Present

I worked on a data pipeline to extract, normalize and visualize multiplexed imaging data to aid pathology researchers in identifying trends from tissue imaging. I also built an unsupervised grid segmentation algorithm for MIBI data to automatically segment cells and other structures.

August 2020 – December 2020, January 2020 – April 2020 (Return intern)

I worked on developing deep learning language models applied to the problem of anomaly detection in software logs. Specifically, I fine-tuned BERT, a transformer developed by Google AI, to generate log message embeddings and leveraged ensemble methods to develop a high-accuracy anomaly detector. I also built the training, inference and evaluation pipelines for this model and worked on deploying it to aid technical support specialists.

May 2019 - August 2019

I worked on native camera acquisition for Android phones using Android NDK and developed an automated exposure algorithm to prioritize shutter speed for improved object tracking accuracy. I also built a VR application designed for mobile phones and published it to the App Store and Google Play Store.