Research
Research overview
My research focuses on embodied robotics, scientific computing, and AI-assisted engineering, with an emphasis on building physically grounded, reliable systems that integrate perception, optimisation, and efficient computation. I am particularly interested in learning-based robotic control, programming by demonstration, and algorithmic frameworks that connect data-driven methods with principled models.
Selected projects
Research experience
University College London
UK, 01/2025 – 03/2025Developed an innovative robotic-assisted surgical workflow for conformal bone tumour resection。
University College London
UK, 09/2024 – 05/2025Developed a robot programming by demonstration (PbD) framework that generalises manipulation skills from multiple human demonstrations.
University College London
UK, 01/2024Bio-signal Based Human–Machine Interface. Designed an EMG-based human–machine interface for measuring muscle activity and enabling control of external devices.
IT & research tools
Technical skills
Programming: Python, C++, C, MATLAB, SQL, JavaScript
Robotics & simulation: ROS, URDF, robot kinematics and dynamics, motion planning, sensor fusion
Machine learning: Convolutional neural networks, probabilistic learning, optimisation (BFGS), learning-based control
Scientific computing: Numerical methods for PDEs, HRSC schemes, MPI, OpenMP, CUDA
Hardware & systems: Analogue and digital circuit design, FPGA (Quartus), ADC/DAC, EMG signal processing
Tools: Linux, Git, SolidWorks, EPLAN Electric P8