Currently a Research Assistant Professor in the Department of Computer Science at Hong Kong Baptist University.
Research focuses on Quantum Machine Learning, spanning three main directions:
1. Variational Quantum Computing: Integrating machine learning theory with tensor network methods to enhance scalability, trainability, and noise resilience in quantum systems;
2. Quantum-Enhanced Machine Learning: Developing parameter-efficient fine-tuning strategies for large language models inspired by quantum principles and tensor networks;
3. Quantum Error Correction: Designing AI-driven error-correcting codes for quantum noise mitigation and fault tolerance.
This interdisciplinary approach bridges quantum physics and modern machine learning to transform computational paradigms in both quantum and classical domains.