CV

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Contact Information

Name Zhenyuan Zhang
Professional Title Ph.D. Student
Email zzhangko@connect.ust.hk

Professional Summary

Ph.D. student in Artificial Intelligence at HKUST, working on computer vision and deep learning.

Experience

  • 2025 - Present

    Beijing, China

    Research Assistant
    GIGA
    Supervised by Zheng Zhu. Working on motion generation and VLA.
    • Contributed to Motion-R1, a text-to-motion generation framework combining Chain-of-Thought reasoning and reinforcement learning.
    • Led MotionCoT Data Engine for automated motion-stage annotation via LLMs.
    • Extended the GRPO method to motion synthesis.
  • 2024 - 2025

    Hong Kong

    Research Assistant
    The Hong Kong University of Science and Technology
    Supervised by Prof. Wenhan Luo.
    • Implemented real-time inference acceleration for talking head generation models using TensorRT and ONNX Runtime.
    • Developed deep learning models for object detection (YOLO) and multi-object tracking (DeepSORT).
    • Achieved real-time inference on NVIDIA Jetson Orin platforms using ROS.
    • Enhanced multi-sensor fusion algorithms (LiDAR-camera fusion).

Education

  • 2025 - Present

    Hong Kong

    Ph.D.
    The Hong Kong University of Science and Technology (HKUST)
    Artificial Intelligence
    • Supervisor: Prof. Yike Guo
  • 2021 - 2025

    Nanjing, Jiangsu, China

    Ph.D. Student (Direct Entry)
    Nanjing University of Science and Technology (NJUST)
    Computer Science and Technology
    • Supervisor: Prof. Jianfeng Lu
  • 2017 - 2021

    Nanjing, Jiangsu, China

    B.Eng.
    Nanjing University of Science and Technology (NJUST)
    Software Engineering
    • GPA: 3.48/4.00 (Rank: 4/114, Core Course GPA: 3.72/4.00)
    • Supervisor: Prof. Jianfeng Lu

Skills

Programming Languages (): Python, C/C++, MATLAB
Frameworks & Tools (): PyTorch, ROS, TensorRT, ONNX, Docker, NumPy, SciPy, Pandas, Matplotlib

Languages

Chinese : Native speaker
English : IELTS 6.5

Interests

Computer Vision: Image Restoration, Face Restoration, Adversarial Robustness, Motion Generation, World Models