My research interests lie at the interface of artificial intelligence and operations research, on algorithm design and mathematical models for resource planning and scheduling problems in logistics, transportation, and related domains. Recently, I became interested in solving combinatorial optimisation problems with hybrid classical-quantum and quantum-inspired algorithms. A common thread running through my research is to go beyond publications to build novel software tools, a number of which have been field-tested and deployed in industry.
Website: http://www.mysmu.edu/faculty/hclau/
Selected publications:
- Light Cone Cancellation for Variational Quantum Eigensolver in Solving Noisy Max-Cut. Sci Rep 16, 9597 (2026). https://doi.org/10.1038/s41598-025-31798-1
- Hybrid Learning and Optimization methods for solving Capacitated Vehicle Routing Problem. I: Proceedings of AAAI 2026 Workshop on Quantum Computing and Artificial Intelligence, Springer Communications in Computer and Information Science, volume 2872. http://arxiv.org/abs/2509.15262
- Implementing Slack-Free Custom Penalty Function for QUBO on Gate-Based Quantum Computers. In: Proceedings of the IEEE Quantum Computing and Engineering Conference (QCE), 2025. https://arxiv.org/abs/2504.12611v2
- Quantum Enhanced-Simulation Based Optimization for Newsvendor Problems. In: Proceedings of the IEEE Quantum Computing and Engineering Conference (QCE), Montreal, Canada, 2024. https://arxiv.org/abs/2403.17389
- A Feasibility-Preserved Quantum Approximate Solver for the Capacitated Vehicle Routing Problem. Quantum Information Processing, Issue 8 (2024). https://arxiv.org/abs/2308.08785