Personal Information

I am a Research Assistant Professor in the Department of Computer Science at Hong Kong Baptist University, Hong Kong. Previously, I earned my Ph.D. in Electrical and Computer Engineering from the Georgia Institute of Technology, where I was advised by Prof. Chin-Hui Lee and Prof. Xiaoli Ma in the Speech and Signal Processing group. Before entering academia, I worked as a Research Software Development Engineer at Microsoft Research's Deep Learning Technology Center, following a Master's degree in Electrical Engineering from the University of Washington. I am the recipient of the prestigious IEEE SPS Signal Processing Letters Best Paper Award in 2025. 

My current research focuses on Quantum Machine Learning, with an emphasis on developing scalable and noise-resilient quantum learning frameworks for noisy intermediate-scale quantum devices. My work spans two closely related directions: (1) Tensor-Structured Variational Quantum Computing: Integrating machine learning theory, tensor network representations, and quantum optimization to address fundamental challenges in expressivity, trainability, and noise robustness of variational quantum circuits; (2) AI-driven Quantum Error Suppression: Leveraging reinforcement learning and graph-based methods to design adaptive strategies for mitigating noise and improving the reliability of quantum systems. My research has been featured in top-tier journals in Quantum Information and recognized with the first prize in the Xanadu Quantum Machine Learning Research Award. 

Research Grants

1. PI on the Quantum Machine Learning project (12203124), HK Research Grants Council, 2025.01--2026.12 

2. Co-PI on the Quantum Finance project (R6010-23), HK Research Impact Fund, 2024.07--2028.12

Teaching

1. COMP7035: Python for Data Analytics and Artificial Intelligence, Lecturer for FALL'23, 24, HKBU

2. COMP7180: Quantitative Methods for Data Analytics and Artificial Intelligence, Lecturer for FALL'24, HKBU