SparQuant: Accelerating Large Language Models via Integrated Quantization and Unstructured Sparsity
Conference · CCF-B · Accepted

GPU Architecture Researcher
MetaX · AI Research Institute (光启智能研究院)
I am joining MetaX as a GPU Architecture Researcher at the AI Research Institute. I received my Ph.D. in Microelectronics from HKUST (Guangzhou), my M.S. in Fundamental Mathematics from Capital Normal University, and my B.S. in Information and Computing Science from Beijing Jiaotong University.
My research centers on software systems for high-performance heterogeneous computing across the full stack, including programming systems, compilers, runtimes, libraries, and application-level optimization. I develop efficient and scalable GPU solutions for data-intensive and irregular workloads.
Conference · CCF-B · Accepted
† Equal contribution
Conference · CCF-B
Journal · CCF-A
Conference · CCF-C
Conference · CCF-A

Huawei Suzhou Research Institute
Built and optimized video codecs, CUDA/VIC image processing, composition, and OSD pipelines.

University of Massachusetts Lowell
Researched GPU runtime optimizations for large-scale graph traversal and developed XBFS.
HKUST (Guangzhou)
Teaching Assistant
University of Massachusetts Lowell
Teaching Assistant