Education

  • 2023 - present
    Ph.D, Computer Science, UC Berkeley
    • Ph.D. student advised by Professor Sergey Levine. Please see my research page for details.
    • Selected courses:
      Deep Reinforcement Learning Computer Vision Machine Learning Systems Convex Optimization
  • 2019 - 2023
    Sc.B., Applied Mathematics & Computer Science, Brown University
    • GPA: 4.0 / magna cum laude / CS Honors / Sigma Xi
    • CS courses:
      Advanced Deep Learning (grad level) Machine Learning Computer Vision Collaborative Robotics (grad level) Computer Systems Software Engineering Multiprocessor Syncrhonization
    • Applied Math courses:
      Recent Applciations of Computational Probability and Statistics Pattern Theory Honors Statistical Inference Computational Linear Algebra Applied ODE/PDE Honors Calculus and Linear Algebra

Honors and Awards

    • Best Paper Award at RSS 2025 Robot Evaluation Workshop
    • Berkeley College of Engineering Fellowship
    • Brown University magna cum laude, CS Honors, CS Senior Prize, Sigma Xi
    • Placed 227th (top 5%) in Putnam 2019, top 3 at Brown
    • 2nd Place in Hartshorn-Hypatia Math Contest
    • Brown UTRA research scholarship
    • only recipient of Yongren Full Fellowship at PROMYS (2018)
    • Provincial Top 1% in Chinese Physics Olympiad
    • Regional Top 10 & International Top 100 in Physics Bowl
    • Finalist in High School Mathematical Contest in Modeling (HiMCM)

Experience

  • May 2025 - Present
    Research Intern, Physical Intelligence
    Robot Learning
    • Exciting things to share soon!
  • Jan 2021 - May 2023
    Undergraduate Researcher, Brown University
    Research Reinforcement Learning Machine Learning/AI Python Pytorch
  • Jan 2022 - May 2022
    Head Teaching Assistant, Brown University
    Autograder Python Management Course Development
    • Managed a team of 20 teaching assistants and organized the course logistics for 200 students, and handled communication between the professor, teaching assistants, and students.
    • Built auto-grading pipeline for 12 coding assignments on Gradescope and enabled students to see code correctness shortly after handin.
    • Answered questions through weekly TA hours and the online discussion platform Edstem.
  • July 2021 - Aug 2021
    Natural Language Processing Engineer Intern, Zencastr Inc.
    Machine Learning NLP MongoDB Python C++
    • Engineered and deployed a web app with websockets and FastAPI that allows users to edit (faulty) audio-to-text automatic transcriptions and provides a faster editing experience by intelligently recommending potentially incorrect segments: the recommendations are made by finding similar occurrences of user-made edits throughout the audio file with Keyword Spotting using language and acoustic models from Kaldi and Vosk-api.
    • Sped up Keyword Spotting 2x using multithreaded offline-decoding in Python and Shell; sped up automatic speech recognition 5x using WeNet architecture (written in C++) and Speech Activity Detection models from Kaldi; model is pushed to production.
    • Implemented a thread-safe MongoDB store with asyncio and motor to store user-made edits in the backend.
  • Dec 2020 - Jan 2021
    Machine Learning Engineer Intern, Zencastr Inc.
    Machine Learning NLP data augmentation CNN Keras Python
    • Built a CNN in Keras that classifies audio files into speech, music, laughter, or noise with 93% accuracy; trained using audio data crawled from YouTube using youtube-dl and augmented by adding noise, changing pitch, and stretching time.
    • Aligned audio-to-text transcriptions from DeepSpeech and Webspeech API using dynamic time warping and grapheme confusion.
    • Built a private Python package of machine learning utility scripts hosted on GitHub with Continuous Integration.

Techinical Skills

  • Python PyTorch TensorFlow/Keras C Docker MongoDB Java JavaScript React MATLAB Assembly x86-64 Scala ReasonML C#