About me
I am an Assistant Professor in the Faculty of Data Science at City University of Macau. My research focuses on Deep Learning Systems and Performance Optimization, with particular expertise in large-scale model training infrastructure and brain-inspired deep learning. I received my Ph.D. in Computer Science Engineering from the University of Texas at Arlington in 2023, where I specialized in Deep Learning Frameworks and GPU Computing. Prior to that, I earned my M.E. in Information, Production, and Systems from Waseda University and B.E. in Electronic Science and Engineering from Southeast University.
I am always looking for motivated graduate students with background in computer science, electronic engineering, or mathematics, working on research fields of 1) brain-inspired deep learning; 2) large-scale model training infrastructure; 3) deep learning applications for video generation.
Latest News
- May/2025: Our paper “Temporal Misalignment in ANN-SNN Conversion and Its Mitigation via Probabilistic Spiking Neurons”, working desperately hard with Velibor (MBZUAI), is accepted to ICML 2025.
- Jan/2025: Awarded a grant from the Science and Technology Development Fund (FDCT) of Macau - Scientific Research and Innovation Funding Scheme 2024 [0071/2024/ITP2] for “An Efficient Adaptive Automatic Parallelization Distributed Training Framework for Heterogeneous Computing Environments” (PI).
- Jul/2024: Our paper “FTBC: Forward Temporal Bias Correction for Optimizing ANN-SNN Conversion” is accepted to ECCV 2024.
- Dec/2023: Awarded a grant from the Science and Technology Development Fund (FDCT) of Macau - Scientific Research and Innovation Funding Scheme 2023 [0055/2023/ITP2] for “Enhancing Deep Learning System Resource Scheduling Efficiency through Preemptive Multitasking” (PI).