Dr. Kuancheng Chen
Postdoc Quantum Computing
Educational Qualifications
PhD in Quantum Engineering
MSc in Advanced Materials Science and Engineering
Biography
Louis Chen is a postdoctoral researcher whose work lies at the intersection of quantum artificial intelligence and distributed quantum computing. His research focuses on algorithm-level frameworks for scalable quantum computation, including distributed quantum algorithms, heterogeneous quantum architectures, and fault-tolerant strategies tailored to networked quantum systems.
He received both his MSc and PhD from Imperial College London. His doctoral research spanned device-level quantum information processing and system-level design, providing a strong foundation for bridging quantum hardware constraints with advanced algorithmic and AI-driven methods.
Louis’s current research investigates how distributed quantum systems and quantum-AI models can be leveraged to address large-scale, real-world problems in optimization, machine learning, and quantum materials simulation. A particular focus is placed on distributed quantum error-correction codes, resource-aware fault-tolerant protocols, and learning-assisted quantum control for emerging quantum networks.
He has authored over 40 peer-reviewed publications in leading journals, including Physical Review Applied, Machine Learning: Science and Technology, Advanced Quantum Technologies, Materials for Quantum Technology, and Optics Express. His work has been recognized with the 2025 IEEE Quantum Technical Community Distinguished QCE Technical Paper Award and the IEEE QCE 2025 Best Paper Awards in both the Photonic Track and Quantum Application Track.
PhD in Quantum Engineering
Imperial College London
2024
MSc in Advanced Materials Science and Engineering
Imperial College London
2017
BSc in Chemistry
National Sun Yat-Sen University, Taiwan
2016
- Quantum artificial intelligence
- Distributed quantum computing
- Quantum optimization
- Quantum HPC
Postdoc
Quantum Computing Group (QC2), Hamad Bin Khalifa University
2026 - Present
Postdoc
Imperial QuEST, Imperial College London
2024 - 2026
Chen, K.-C., et al. (2025). Validating large-scale quantum machine learning: Efficient simulation of quantum support vector machines using tensor networks. Machine Learning: Science and Technology, 6(1), 015047.
Chen, K.-C., et al. (2025). Distributed quantum neural networks on distributed photonic quantum computing. In 2025 IEEE International Conference on Quantum Computing and Engineering (QCE) (Vol. 1). IEEE.
Chen, K.-C., et al. (2026). Adaptive resource orchestration for distributed quantum computing systems. IEEE Internet Computing.
Liu, C.-Y., et al. (2025). Quantum-enhanced parameter-efficient learning for typhoon trajectory forecasting. In 2025 IEEE International Conference on Quantum Computing and Engineering (QCE) (Vol. 1). IEEE.
Burt, F., Chen, K.-C., & Leung, K. K. (2026). A multilevel framework for partitioning quantum circuits. Quantum, 10, 1984.
Complete Publication Listing(s): Google Scholar
- 2025 IEEE QTC Distinguished QCE25 Technical Paper Award
- IEEE QCE 2025 Best Paper in Photonic Track and Quantum Application Track
- Imperial College Global Fellowship 2024
- Deloitte Climate Quantum Challenge First Prize
- The Blaise Pascal Quantum Challenge Third Prize
