Experience

  1. Research Assistant

    SSIL Lab, Illinois Institute of Technology

    Responsibilities include:

    • Designing and implementing VR applications in Unity3D, leveraging spatial computing and advanced motion planning on Oculus Quest to decode user behavior and cognitive states through motion dynamics.
    • Utilizing cutting-edge machine learning techniques to build intelligent systems that interpret and anticipate subtle cognitive states, advancing seamless human-computer interaction.
    • Conducting independent research initiatives encompassing participant recruitment, structured data collection, deep learning experimentation, and comprehensive result analysis.
  2. Lead Instructor

    Summer’24 National Coding Bootcamp, TCTM Kids IT Education

    TCTM offers quality IT education targeting students aged three to eighteen through a hybrid platform combining live instruction, classroom tutoring, and online learning. The company was founded in 2002, formerly known as Tarena International, Inc.

    Responsibilities include:

    • Led instruction for two intensive training camps, delivering seven classes to 210+ students aged 9 to 18, featuring an engaging, clear, and accessible teaching style.
    • Designed and taught a comprehensive curriculum spanning foundational C++ syntax to advanced algorithms and data structures, integrating cutting-edge computer technologies to inspire young students and cultivate their problem-solving skills.
  3. Research Intern

    Megvii Research (Formerly Face++)

    Responsibilities include:

    • Independently led a computer vision project that leveraged laser-illuminated wrist videos to estimate heart rate, integrating traditional digital image processing techniques with deep learning models to improve the accuracy of physiological measurements.
    • Investigated accelerating Neural Radiance Field (NeRF) training using PyTorch, improving computational efficiency in 3D scene reconstruction.
  4. Visiting Student

    VIPL Lab, Chinese Academy of Science

    Responsibilities include:

    • Researched on cervical spondylosis measurement using a U-Net-based model in PyTorch for segmentation and MMPose for pose estimation.
    • Achieved a 75% reduction in Cobb metric error (from 20° to 4.88°) through advanced image processing and model optimization, demonstrating expertise in computer vision and machine learning.
    • Collaborated with clinicians from Peking University Third Hospital to ensure accurate data labeling and validation.
    • Advisor: Prof. Xinhang Song

Education

  1. PhD Computer Science

    Illinois Institute of Technology
  2. BSc Computer Science

    Beijing Jiaotong University