• Developed and maintained an internal compiler for Arista’s networking

subsystems that parses and generates source code in C++ and Go

• Contributed in backend development for Redis driver and applied fuzzing techniques for testing

• Generated stats (miss/hit ratio, overall runtime) of Arista’s compiler cache and

uploaded to InfluxDB using Telegraf, Grafana

Lab Director: Dr. Marvin Andujar

Team Director: Sarah Garcia (PhD Student)

Project: Quantified-self. A project collaborating with a company called Diamond View to analyse different emotion using emotional recognition algorithm to classify spectators' reaction to a specific video

• Develop Rise 2.0- an IOS app to track the engagement score of users using Swift and connect the app to Firebase

• Write python/Swift scripts to extract the data from the G.tec and send it to Firebase, leverage OpenVibe framework as a medium

• Build Machine Learning model that leverage Reinforcement Learning and Convolutional Neural Network for emotion recognition

• Partner with Diamond View to conduct an IRB-approval study, a local company that focuses on analyzing human emotion