Zhimu Yang

Zhimu Yang

Theoretical Computer Science

Open to research opportunities

Research Interests
  • Algorithms & Complexity
  • Quantum Computing
  • Machine Learning
☙ ❖ ❧

I am an student fundamentally driven by a rational pursuit of the essence of mathematics and computation. My work lies at the intersection of Theoretical Computer Science (TCS), Quantum Computing, and Artificial Intelligence. I view scientific research as a pure endeavor to advance human knowledge—an evolution of axioms dedicated to the progress of civilization, strictly for all humankind.

I am currently seeking opportunities to deepen my training and contribute to research in theoretical computer science, whether through a research internship or doctoral study.

Education & Training

Hong Kong University of Science and Technology (Guangzhou) Jul 2025 - Mar 2026
Research Intern | Supervisor: Xin Wang
Quantum Science Center of Guangdong-HongKong-Macao Greater Bay Area Dec 2024 - Jun 2025
Research Intern | Supervisor: Shenggen Zheng
Communication University of China Sep 2021 - Jul 2025
Bachelor of Science in Artificial Intelligence

Research Experience

Quantum Compilation Quantum Circuit Compilation for Silicon Architectures Jul 2025 - Mar 2026
Hong Kong University of Science and Technology (Guangzhou)
Independently designed pattern-based compilation algorithms for silicon quantum computers with crossbar architectures. Investigated and mathematically resolved underlying structural defects in quantum circuits.
Dynamic Quantum Systems Compilation of Dynamic Quantum Systems Dec 2024 - Jun 2025
Quantum Science Center of Guangdong-HongKong-Macao Greater Bay Area
Developed core compilation frameworks for dynamic quantum systems, focusing on optimizing instruction sets for QCCD ion trap architectures and dynamic neutral atom arrays.
Quantum Neural Networks Theoretical Analysis of QNN Universal Approximation Property Sep 2024 - Present
Communication University of China | Graduation Project
Proved the overarching linearity of QNNs concerning data encoding components, demonstrating that modifying U-gates and measurements is insufficient to guarantee universal approximation.
GNN Expressivity Expressivity of Polynomial Networks and Graph Neural Networks Dec 2023 - Present
Communication University of China
Proposed TaylorKAN and mathematically demonstrated its equivalence to Polynomial Networks. Developed FSX, formulating Shapley value computations via graph cooperative game theory.
Quantum Information Workshop on Fundamentals and Frontiers Dec 2023
Hainan University | Center for Theoretical Physics
Focused on quantum networks, quantum error correction, and quantum optics.
Quantum Open Systems Training Course on Quantum Open Systems Theory Nov 2023
Beijing Computational Science Research Center (CSRC)
Explored quantum dissipative systems, dissipative theory, and the central spin model.
Neural Modeling Training Course on Neural Computational Modeling Sep 2023
Peking University
Studied neuron and synaptic models, building dynamic neural networks.
Generative AI Generative Model of Chinese Paintings Feb 2022 - Aug 2022
Communication University of China, MIPG
Evaluated the architectural limitations and multimodal generative capabilities of GAN models, alongside other generative frameworks (CycleGAN, DRIT, Diffusion).