resume

Education

  • 2021-2025
    MEng of Electrical and Information Engineering
    Imperial College London, London, UK
    • Final Year Project "Efficient Compression of Large Language Models for Edge Devices through Tensor Decompositions", supervised by Prof. Danilo Mandic
    • Top 5%, Dean's list in Years 1 and 2 and 3
    • Main moduels
      • Probability and Stochastic Processes
      • Optimisation
      • Statistical Signal Processing and Inference
      • Deep Learning
      • Computer Vision
      • Machine learning
      • Advanced Computer Architecture
      • Control Systems
      • Signals and Systems
  • 2019-2021
    A Levels & IGCSE
    Jinling High School, Nanjing, China
    • 4 A*s in Further Maths, Maths, Physics and Chemistry
    • Accumulative marks Top 1 in China -- 2020 Cambridge Outstanding Learner Award (Best Across Three)

Work & Research Experience

  • 2024.04 - 2024.09
    CPU Design Internship
    arm, Cambridge, UK
    • Helped Central Engineering team design and develop a co-processor that accelerates matrix multiplication for machine learning tasks.
    • Captured RTL events for performance modeling.
    • Optimised decoders for better power, performance, and area (PPA) trade-off.
  • 2024.03 - 2024.09
    Part-time Machine Learning Undergraduate Researcher
    Imperial College London, London, UK
    • Utilised Graph Neural Network (GNN) to model multiphase fluid flow dynamics for CO2 geological storage, hydrogen storage, and fuel cells using real experimental data
  • 2023.07 - 2023.09
    Undergraduate Research Opportunities Program (UROP)
    Imperial College London, London, UK.
    • Developed a colour-tracking 4-DOF robotic arm using remote control within ROS2 framework.
    • Derived forward and inverse kinematics and integrated a USB camera as a sensor within feedback loop.
    • Utilised a Raspberry Pi for motor control via UART, implemented a remote controller and conducted stability analysis.
  • 2023.09 - 2024.04
    UNDERGRADUATE TEACHING ASSISTANT (UTA)
    Imperial College London, London, UK
    • Mentored and supported junior students during the classes and labs of the following modules.
      • Deep learning (ELEC60009/70061)
      • Machine learning (ELEC60019/70059)
      • Mathematics 1A (ELEC40012A)
      • Probability and Statistics (ELEC50011B)
      • Control systems (ELEC50004)
  • 2022.07 - 2022.09
    Software Engineer
    Evotrack, London, UK
    • Analysed usage data of E-vehicles charging stations in Paris and ran k-means clustering to divide stations into clusters.
    • Achieved 90% accuracy in station utilization prediction using Gradient Boosting models.

Honors and Awards

Other Interests

  • Hobbies: Violin, Badminton, etc.