About
Highly motivated Ph.D. student in Robotics with a profound commitment to advancing robotics foundation models by integrating cognitive and athletic intelligence. Leveraging expertise in deep learning, computer vision, and control systems, I aim to revolutionize modern industry and society through innovative robotic solutions. My research focuses on complex manipulation tasks, teleoperation, and real-time visual perception, consistently driving impactful contributions to the field.
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Work
Tsinghua University, Institute for AI Industry Research (AIR)
Research Intern
National University of Singapore, School of Computing
Research Intern
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Education
Robotics
The Hong Kong University of Science and Technology
Electrical and Computer Engineering
Georgia Institute of Technology
Mechanical Engineering
Qingdao University
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Awards
National Scholarship
Awarded for outstanding academic achievement as part of the top 1% of the graduating class.
Special Prize
Recognized for exceptional performance in the Material Handling Robot competition, demonstrating superior engineering and problem-solving skills.
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Publications
Taming VR Teleoperation and Learning from Demonstration for Multi-Task Bimanual Table Service Manipulation
ICRA 2025 WBCD Challenge
DexSinGrasp: Learning a Unified Policy for Dexterous Object Singulation and Grasping in Densely Cluttered Environments
R-AL Submission
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Languages
Mandarin
English
Cantonese
German
Japanese
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Skills
Programming & Tools
Python, PyTorch, C/C++, Isaac Gym, MATLAB/Simulink, ROS, Cmake, LaTeX, Solidworks
ML & Decision Making
Imitation Learning, Reinforcement Learning, LLM/VLM, Deep Learning, Machine Learning
Control & Actuation
Nonlinear control, Disturbance rejection control, Dynamics modeling, Linear Systems and Control
Computer Vision
Digital Image Processing, Monocular Depth Estimation, Video Inpainting, Stereo Vision Odometry, Object Recognition
Robotics Frameworks
ROS (Robot Operating System)
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Projects
ICRA WBCD Challenge
Participated in the ICRA WBCD Challenge, a prestigious robotics competition, achieving recognition for innovative solutions in bimanual manipulation.
Monocular Depth Estimation - FADE Ain't Depth Estimation
A deep learning project focused on enhancing monocular depth estimation using large-scale networks and advanced boosting methods.
C++ Simulation, Games and Visualization
Engaged in multiple C++ projects focusing on simulation, game development, and visualization, showcasing expertise in OpenGL and SFML.
An Attention-Based Video Inpainting Technique for Wire-Removal Scenarios
Developed an innovative autoencoder-based video inpainting model specifically designed for wire-removal in cinematic applications.
An ORB-based Stereo Vision Odometry (Undergrad thesis)
Designed and implemented PyVO, a Python-based visual stereo odometer, as part of an undergraduate thesis project.
The 6th National Engineering Training Competition - Material Handling Robot
Built an STM32-based Mecanum Wheel robot for a national engineering competition, focusing on material handling and object recognition.
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