Bio

I am a second year Master's student in the Computer Science Department at Stanford.

I conduct research in the Stanford ML Group with Professor Andrew Ng on developing machine learning techniques for healthcare and education.

Research

Here are some my research projects at Stanford and UCSB.


MURA - Large Dataset for Abnormality Detection in Musculoskeletal Radiographs

Ongoing project with Pranav Rajpurkar and Professor Matt Lungren, Professor Andrew Ng

Released a large dataset of musculoskeletal radiographs for an abnormality detection computer vision task. The dataset contains over 40,000 images of the upper extremeties which were manually annotated by board-certified radiologists as normal or abnormal.

Project WebpagePaper (ARXIV)

ChexNet - Radiologist-Level Pneumonia Detection

Ongoing project with Pranav Rajpurkar and Professor Matt Lungren, Professor Andrew Ng

Developed an algorithm that can detect pneumonia from chest radiographs at the level of practicing radiologists. Our model, CheXNet, is a 121-layer convolutional neural network trained on ChestX-ray14, the largest publicly available chest X-ray dataset.

Project WebpagePaper (ARXIV)

Chemotherapy-induced Heart Failure

Ongoing project with Pranav Rajpurkar and Professor Andrew Ng

Building a risk model for the onset of heart failure due to chemotherapy treatment. The model is trained on electronic health record data and will alert oncologists when their patients are showing signs of cardiotoxicity, allowing them to alter treatment and save patient lives.

Blog Post

Child Language Learning

From September 2015 to June 2016 with Daniel Spokoyny and Professor Fermín Moscoso del Prado Martín

Applied dynamical systems and causal modeling techniques to linguistic data to understand the underlying complex nonlinear patterns of language development in children. UCSB Undergrad Research Colloquium Best Humanities Research Prize Winner.

Paper (Cognitive Science)Paper (ACL)PosterSenior Thesis

Teaching

AI in Healthcare Bootcamp Winter 2018

Quarter-long bootcamp with Anand Avati, Pranav Rajpurkar and several professors

Co-organized a quarter-long, 13-student bootcamp at Stanford covering advanced techniques at the intersection of artificial intelligence and healthcare.

Bootcamp Webpage

AI in Healthcare Bootcamp Fall 2017

Quarter-long bootcamp with Anand Avati, Pranav Rajpurkar and Professor Nigam Shah, Professor Andrew Ng

Co-organized a quarter-long, 6-student bootcamp at Stanford covering advanced techniques at the intersection of artificial intelligence and healthcare.

Bootcamp Webpage

ML, NLP, DL Course

Quarter-long course with Daniel Spokoyny and Professor Ömer Egecioglu, Professor Murat Karaorman

Co-designed a quarter-long course at UCSB providing an overview of machine learning, natural language processing, and deep learning.

Course Webpage

Industry Experience

MicrosoftSummer 2017

Data Scientist Intern, Market Intelligence

Built a large scale, unsupervised query embedding model to learn information-rich embeddings. Improved market intellgience platform by integrating deep learning tools into the insights pipeline.

MicrosoftSummer 2016

Software Engineering Intern, Bing Predicts

Created a model to predict the MTV Video Music Awards’s using Bing search and social data.

MicrosoftSummer 2015

Software Engineering Intern, Satori (Knowledge Graph)

Developed an algorithm to detect subtle entity relations in an immense ontology and rank them by novelty. Increased run-time by two orders of magnitude.

Education

Stanford

Master's in Computer Science

4.00 / 4.00 GPA

UCSB

Bachelor's in Mathematics, Bachelor's in Computer Science

3.97 / 4.00 GPA