I graduated Magna Cum Laude from Princeton University in 2019 with a B.S.E in computer science. I am passionate about advancing the state-of-art in computer vision and deep learning research, as well as reducing the computational and domain knowledge barriers that prevent large-scale production use of machine learning. I am currently an Applied Scientist at Amazon, and was formerly a software engineer in AWS AI.
My current research interests are in video understanding, with a particular emphasis on self-supervised video representation learning from multiple modalities. I see a future where computers are capable of human-like perception and visual reasoning.
I am fluent in English and Mandarin Chinese. My hobbies include tennis, ping pong, clarinet, nature walks, hacking, and writing.
Princeton University | 2015-2019
B.S.E. in Computer Science and Minor in Statistics and Machine Learning | Magna Cum Laude (High Honors)
Senior Thesis in Computer Vision advised by Prof. Jia Deng. Paper accepted to the 2020 IEEE Conference in Computer Vision.
Libraries: PyTorch, TorchScript, Tensorflow, OpenCV, Shiny
Web Development: Django, Express.js | HTML5, React, Hugo, Jekyll
Databases: MySQL, MongoDB, DynamoDB
Other: AWS, Docker, Git, UNIX, LaTeX, Leadership
Keywords: Computer Vision, Deep Learning, Research, Software Engineering, Data Visualization
- MAT 201: Multivariable Calculus (Fall 2015)
- MAT 202: Linear Algebra (Spring 2016)
- ORF 245: Statistics (Spring 2016)
- ORF 309: Probability and Stochastic Systems (Spring 2017)
- ORF 363: Convex Optimization (Fall 2018)
- COS 226: Algorithms and Data Structures (Spring 2016)
- COS 340: Reasoning about Computation (Spring 2017)
- COS 445: Economics and Computing (Spring 2018)
- COS 423: Theory of Algorithms (Spring 2019)
- COS 217: Programming Systems (Fall 2016)
- ELE 206: Logic Design (Fall 2016)
- COS 333: Advanced Programming Techniques (Spring 2018)
- COS 461: Computer Networks (Spring 2018)
- COS 418: Distributed Systems (Fall 2018)