Undergrad Research Assistant

Experiences

Worked in the Google Accelerated Science Team at Google AI where we collaborated with chemists and biologists in universities/labs to accelerate drug discoveries with image based cell screening
Developed a Generative Adversarial Network based model remove batch-to-batch effect in cell imaging including dye intensity, imaging device, lighting condition etc. The multi-domains transformation significantly improve downstream analysis by removing the batch effect biases.
Opened source the implementations and contributed to Tensorflow and Tensorflow Model

Worked on various research topics in bioinformatics and computational chemistry using a data driven neural network approach with Prof. Jian Peng
Research topics include protein sequence profiling, protein structure contact prediction, and graph based neural network for molecule property prediction and model interpretability

Summer 2016: created and designed an internal tool for mobile developers to investigate UI test failures in full speed by aggregating and synchronizing logs and videos with React.js front-end and Python/Go back-end
Summer 2017: built model to estimate the trip states (e.g. parking, waiting etc) for Uber Eats couriers, and developed a Kernel Conditional Random Field library drawing interest from multiple teams and won the first prize for Uber’s first internal machine learning poster session

Conducted interdisciplinary research in computer science, biology and natural language processing with Prof. Pengyu Hong
Develop statistical machine learning model and engineer neural network to solve some challenging problems in protein structure understanding in biology and discourse parsing in linguistic
Selected as Jerome A. Schiff Undergraduate Fellows for my thesis