experience

Education

  • 2025.09 - Present

    Stanford, CA

    Master of Science
    Stanford University
    M.S. Computer Science | Specialized in Artificial Intelligence
  • 2022.09 - 2025.06

    La Jolla, CA

    Bachelor of Science
    University of California, San Diego
    B.S. Computer Science | Regents Scholar | Summa Cum Laude

Experience

Industry

  • 2026.09 - 2026.12
    Machine Learning Intern
    Gridmatic
    • Incoming Fall 2026 - ML Models for Grid Forecasting
  • 2026.06 - 2026.09
    Software Engineer Intern
    Meta
    • Incoming Summer 2026 - Instagram Recommendation
  • 2023.04 - 2025.06
    Machine Learning Engineer Intern
    Qualcomm Institute
    Python, PyTorch, Unreal Engine, Kubernetes, Docker, C++
    • Co-developing interactive 3D avatars of historical figures, driven by large language models, text-to-speech / animation pipeline, and Unreal Engine 5. Co-developing Climate Games, an educational video game, to raise awareness on climate change and archaeology. Both projects were presented at ASOR 2024 Annual Meeting.
    • Developed a real-time audio-to-face pipeline that receives audio input from text-to-speech and uses NVIDIA Audio2Face through Rest API to animate facial movements on a 3D avatar. Further researched and developed our own multimodal co-speech gesture generation model for holistic body animation.
    • Developed an Unreal plugin for real-time speech gesture generation and player communication. The plugin supports seamless communication in multiplayer gameplay and between Unreal Engine and external AI models.
  • 2022.03 - 2022.06
    Software Engineer Intern
    Nearal
    Kotlin, Android Studio
    • Developed various features for Nearal’s Android application, including a dynamic onboarding screen, a floating login interface, and an improved sign-up process, using Kotlin and Android Studio.
    • Refined multiple app fragments, ensuring optimal functionality for both logged-in and logged-out users, and resolved critical issues such as photo display inconsistencies and profile identification.

Research

  • 2025.09 - Present
    Graduate Researcher
    Stanford Vision and Learning Lab | Advisor: Prof. Jiajun Wu
    Python, PyTorch, Swift
    • Researching cost-effective multi-view capturing systems for high-fidelity 3D / 4D reconstruction.
  • 2023.06 - 2025.06
    Undergraduate Researcher
    Hao Su Lab | Advisor: Prof. Hao Su
    Python, PyTorch, JAX, Gymnasium, Docker, Kubernetes
    • Researched demo-guided deep reinforcement learning methods to effectively solve long-horizon, sparse tasks. Co-authored paper Reverse Forward Curriculum Learning accepted in ICLR 2024.
    • Benchmarked various state-of-the-art demonstration-guided deep RL methods, including RLPD, IQL, etc., on ManiSkill2, D4RL, and Meta-World tasks. Performed experiments on Kubernetes cluster using Docker.
    • Adapted TD-MPC2 to Maniskill3 CPU/GPU vectorized environments and visual (rgb) based RL.
    • Developed and optimized implementations of TD-MPC2 and SAC in JAX, achieving a 5x reduction in training time in comparison to previous PyTorch implementations.
    • Proposed a RL method leveraging layer-wise freezing and a latent state replay buffer to enhance both sample and wall-time efficiency and wall-time in visual and continual learning tasks. Results demonstrated a 2x reduction in training time on ManiSkill3.

Teaching

  • 2024.01 - 2025.03
    Instructional Assistant
    UCSD Department of Computer Science and Engineering (CSE)
    • Assisted in the instruction of CSE 152A: Intro to Computer Vision during Winter quarters of 2024 and 2025.

Awards

Skills

Programming Languages
Java
Python
C/C++
CUDA
SQL
LaTeX
Shell
Developer Tools
Git
Docker
Kubernetes
Unreal Engine 5
Library
PyTorch
Numpy
JAX
Domain Knowledge
Reinforcement Learning
Computer Vision
Machine Learning
Computer Graphics