Uber Advanced Technology Group

Software Engineering Intern• May 2019 - August 2019

I created an anomaly detection CNN model which detects if items are left behind in a self driving vehicle cabin. It achieved 98% accuracy, with around 1% false negatives. I deployed the model as a Golang service in Uber's production infrastructure, and I connected the service to S3 to store all the images that are passed through it to allow for further training samples. I also worked with decoding RTP VP8 video packets from Webrtc.

UCSF Imaging Center

Undergraduate Research Apprentice • September 2018 - May 2018

My main responsibility was creating an algorithm which identifies fat in cortical bone in a given FIESTA MR image set using image processing techniques. A few other tasks include building a filtering algorithm which identifies image frames where the cortical bone is blocked, writing a function to segment images into masks, and creating a script to give a score for a bone image based on the size of the pore and the distance from the pore to the center of the bone. Work was done in python and matlab. An example of my work is shown below in the projects section.

Vetter Software

Full Stack Intern • May 2018 - August 2018

I prototyped an offline mobile app of their current web application. It uses local storage to save patient information so that the app can be used without a wifi connection. I also created a check in app that clinics can use to save time inputting user information.