# About Me

### Short Bio

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.

### Education

**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.

### Resume/CV

[My CV]

### Skills

**Programming Languages**: Python, Java, R, Javascript, Go, OCaml, MatLab, C/C++

**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

### Coursework

**Machine Learning**

- ORF 350: Big Data (Spring 2017)

- COS 429: Computer Vision (Fall 2018)

- COS 529: Graduate Computer Vision (Spring 2019)

**Mathematics**

- 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)

**Theory**

- 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)

**Systems**

- 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)

**Applied**

- QCB 455: Introduction to Genomics and Computational Molecular Biology (Fall 2017)

- COS 326: Functional Programming (Fall 2017)

- COS 432: Information Security (Fall 2017)