Imperial College London
Guest Lecturer · Imperial QuESTDistributed quantum computing, quantum algorithms, quantum software, compilation, and benchmarking.
CV
Academic CV
Curriculum vitae
Research profile of Dr Kuan-Cheng (Louis) Chen across quantum algorithms, distributed quantum computing, quantum machine learning, photonic quantum computing, quantum-HPC benchmarking, and practical quantum sensing technologies.
Quantum AI Scientist Quantum algorithms, learning, software, and systems
Global R&D Industrial quantum workflows and benchmarking
Policy-making Quantum technology regulation and translation
Current roles
Appointments
JIJ Europe Ltd.
Global R&D ManagerIndustrial quantum algorithms, benchmarking, quantum-HPC workflows, quantum optimisation, and quantum machine learning applications.
HBKU QC2
Research ProfessorQuantum large language models, quantum data-centric machine learning, and quantum AI workflows for scientific and engineering applications.
Academic training
Education
Ph.D. Quantum Engineering
Imperial College London
Visiting Researcher
Technical University of Munich
M.Sc. Quantum Engineering
Imperial College London
Exchange Study in Quantum Chemistry
Tsinghua University
B.Sc. Chemistry; Double Major in Business / Financial Engineering
National Sun Yat-sen University
Research scope
Research interests
Distributed quantum computing Quantum networks Quantum machine learning Photonic quantum computing Quantum-HPC benchmarking Tensor-network simulation Quantum circuit compilation Resource estimation Early fault-tolerant quantum computing Quantum optimisation Quantum finance Power systems Practical quantum sensing technologies Spin–acoustic interfaces
Recognition
Honours and awards
QTC Distinguished Paper Award / Best Paper
IEEE QCE 2025.
John Matthey Prize
2025 doctoral research recognition.
Imperial Global Fellow
Selected for international collaboration and research impact.
TSMC Research Prize
Recognition for research excellence.
National PhD Scholarship — Taiwan
Competitive national merit-based funding for doctoral study.
Hackathon awards
IBM Quantum Hackathon 1st; Deloitte Quantum Climate Challenge 1st; Xanadu QHack 2nd; Blaise Pascal Quantum Challenge 3rd; MIT iQuHack 3rd.
Funding
Selected grants and funding
Imperial QuEST Seed Funding
Realizing Quantum Optical Neural Networks through Programmable Photonic Processors, 2024.
Imperial QuEST Seed Funding
Distributed Photonic Quantum Neural Networks for Distributed Learning in Medical Neuroimaging, 2025.
Imperial–TUM Global Fellows Fund
Quantum Software for Distributed Quantum Computing.
ICoNYCh Exchange Fund
Quantum Machine Learning in Quantum–HPC.
Service
Professional activities
Editorial and reviewing
Editor for APL Machine Learning Quantum Artificial Intelligence Special Topic. Reviewer for quantum, AI, computational intelligence, and conference venues including IEEE QCE, ICASSP, IJCNN, ICMLA, and ICALP.
Workshop organisation
INFOCOM QuNAP Workshop 2025; ISCAS Special Session 2025; IEEE QAI Special Session 2025; QCNC QC4C3 2026; IEEE QCE QuBench 2026.
Policy and mentorship
Contributor to quantum technology regulation activities. Mentor through IBM Quantum, QOSF, QWorld QIntern, and Imperial Quantum Technology Society.
Invited talks
DCTL Manchester 2025; ICS Salt Lake City 2025; Quantum Innovation Summit Dubai 2024; MRS Cancun 2023.
Technical profile
Skills
Programming
Python, C/C++, Julia, MATLAB, Java, R, LaTeX, Linux.
Quantum SDKs
Qiskit, Cirq, PennyLane, Pytket, CUDA-Q.
Machine learning and HPC
PyTorch, TensorFlow, tensor networks, CUDA, cuTensorNet, MPI.
Simulation and devices
Gem5, TCAD, SPICE, microwave and electron-paramagnetic-resonance instrumentation.
Selected work
Research outputs
Publication archive and open research profile
The complete publication archive and selected work are available through the publications page and Google Scholar profile.