Training and experience

Education and Experience

My background spans computer science, machine learning, control systems, and applied AI, with research experience in LLMs, telecommunications, XR, digital twins, and web graphics systems.

Education

Academic background

Ph.D. in Computer Science

McGill University, Montreal, Canada

Supervisor: Prof. Xue Liu. Affiliation: Mila - Quebec AI Institute.

Visiting Student

Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates

Machine learning research.

M.Sc. in Computing

Imperial College London, London, United Kingdom

Focus on machine learning, neural networks, and applied AI systems.

Exchange Program

Columbia University, New York, United States

Coursework in English, Statistical Inference, and Time Series Analysis.

Bachelor of Engineering in Automation

Xi'an Jiaotong University, Xi'an, China

Capstone project on vehicle chassis detection using multi-sensor fusion.

Research Experience

Experience

Research Intern, Canada AI

Montreal, Canada

Research mentor: Dr. Di Wu. Digital twins and multi-agent reinforcement learning for autonomous control in data-center environments.

Student Researcher, Samsung Research America

Remote

Manager: Dr. Jianzhong (Charlie) Zhang. Entity extraction, knowledge graph construction, and structured information extraction for telecom-oriented LLM and RAG systems.

Research Intern, Samsung AI Center - Montreal

Montreal, Canada

AI methods for wireless networks, 5G/XR applications, edge intelligence, and wireless-network optimization.

Research Intern, Xi'an GrapeCity I.T. Inc.

Xi'an, China

Developed and optimized browser-based 3D graphics components with WebGL and WebAssembly.

Awards

Honors

  • Graduate Excellence Award, McGill University, 2022-2026
  • Second Prize, Robocon Contest, 2016-2017
  • First Prize, China Undergraduate Mathematical Contest in Modeling, 2016

Skills

Technical focus

  • Python
  • C/C++
  • JavaScript
  • TypeScript
  • PyTorch
  • LLM fine-tuning
  • RLHF
  • Multi-agent RL
  • RAG
  • Knowledge graphs
  • Docker
  • Linux