Jinguo Liu
Chief Scientist at Hong Kong University of Science and Technology (Guangzhou)
Changzhou, Jiangsu, China
Summary
🤩
Rockstar🎓
Top SchoolJinguo Liu is a chief scientist and assistant professor with 11 years of experience at the intersection of quantum information and scientific computing, currently based in Changzhou and affiliated with HKUST (Guangzhou) and Jugsaw, Inc. He combines deep theoretical training (PhD in theoretical physics) with hands-on software engineering—contributing to prominent open-source projects like Zygote.jl (automatic differentiation) and Yao.jl (quantum algorithm framework), where he improved complex-number AD and core quantum operator implementations. His work spans academia and industry, from postdoctoral roles at Harvard and the Chinese Academy of Sciences to consultancy on stochastic optimizers for QuEra, reflecting fluency in both research and production-grade code. Notably, he helped develop differential quantum simulation toolchains and generic tensor-network methods, linking combinatorial optimization problems to quantum simulation techniques. Practical, curious, and multidisciplinary, he brings a rare blend of theoretical insight and low-level computational craftsmanship to quantum software and scientific computing.
11 years of coding experience
Doctor, Theoretical physics, Doctor, Theoretical physics at NanJing UniversityBachelor, Computer Software Engineering, Bachelor, Computer Software Engineering at NanJing institute of science and technology
Stackoverflow
705reputation
400kreached
12answers
0questions
Github Skills (24)
machine-learning10
julialang10
complex-numbers10
gradient10
automatic-differentiation10
compiler10
quantum-computing10
documentation10
julia10
linear-algebra9
sparse-matrix8
algorithms8
testing8
programming-language7
control-flow7
Programming languages (18)
Github contributions (5)
QuantumBFS/Yao.jl
Apr 2018 - Jan 2023
Extensible, Efficient Quantum Algorithm Design for Humans.
Role in this project:
Backend Developer & Documentation Specialist
Backend Developer & Documentation SpecialistContributions:1 release, 81 reviews, 426 commits in 4 years 9 months
Contributions summary:Jinguo primarily focused on developing features for the project and improving documentation, with a strong emphasis on the core aspects of the Yao.jl library, as seen in contributions to the testing and code structure. They implemented the foundations for handling general matrix operators and improving the efficiency of various quantum gate instructions. The user also contributed to the structure and documentation for the project.
quantum-computingquantum-algorithmsquantum-informationquantum-circuitmachine-learning
FluxML/Zygote.jl
Apr 2019 - Apr 2019
21st century AD
Role in this project:ML Engineer
ML EngineerContributions:5 commits, 4 PRs, 37 comments in 2 days
Contributions summary:Jinguo primarily focused on improving the Zygote.jl library, which provides automatic differentiation capabilities. Their contributions involved debugging and refining the core functionalities of the library, particularly relating to complex number differentiation (real, imag, and conj functions). They also addressed specific issues identified within the project, improving the performance and correctness of the automatic differentiation process for various operations and data structures.
control-flowautomatic-differentiationmachine-learningjulia-compilerjulia
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