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.

About Me
Latest Articles
Recent research papers spanning quantum compilation, quantum measurement, machine learning, and tensor networks.

Multiparticle entanglement of nuclear spins in silicon
Nature Communications research on preparing and characterizing nine classes of four-qubit entanglement in a silicon nuclear-spin platform. Second Author.

Optimal quantum overlapping tomography: Theory and experiment
Physical Review Applied research combining optimized measurement schemes with deep learning to recognize four-qubit entanglement from partial measurements. Second Author.
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.
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)
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
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.