Kada Yang

M.S. Student in Quantum Science and Engineering

Shenzhen, China

Researching quantum machine learning, automated quantum measurement and control, quantum compilation, system learning, and tensor networks.

About Me

About Me

I am an M.S. student in Quantum Science and Engineering at SUSTech, focusing on quantum machine learning and automated quantum measurement and control. My research spans quantum compilation, quantum tomography, deep learning, and tensor networks, with experience at the Hefei National Laboratory - Shenzhen Base and the Institute of Computing Technology, Chinese Academy of Sciences. I enjoy turning theoretical ideas into efficient quantum algorithms and scalable computational methods.

Latest Articles

Recent research papers spanning quantum compilation, quantum measurement, machine learning, and tensor networks.

Machine-Learning-Based Prediction of Quantum Magic

Deep-learning research for predicting quantum-state magic from local measurements, with tensor-network simulation for larger quantum systems. Co-First Author.

Quantum Machine LearningDeep LearningTensor NetworksQuantum Magic

Project Introduction

Selected projects and ongoing work will be introduced here.

Project details are being prepared. Check back soon.

Education

  • Southern University of Science and Technology (SUSTech)

    Southern University of Science and Technology (SUSTech)

    M.S. in Quantum Science and Engineering · GPA 3.53/4.0 (Ranked 1st)

    Sep 2025 - Present
    • Shenzhen Institute for Quantum Science and Engineering
    • Top-Tier Academic Scholarship
    • Top-Tier Research Assistantship Stipend
  • Chongqing Jiaotong University

    Chongqing Jiaotong University

    B.Eng. in Artificial Intelligence · GPA 4.17/5.0 (Ranked 1st)

    Sep 2021 - Jun 2025
    • School of Information Science and Engineering
    • National Scholarship for Undergraduates
    • Chongqing Outstanding Individual in Science and Technology Innovation

Competition Awards

International, national, provincial and university-level achievements.按国际级、国家级、省部级与校级依次展示的竞赛成果。

Honors

This section is reserved for future honors and distinctions.

More honors will be added here.