50+

Publications in top-tier conferences and journals

ISCA, MICRO, ASPLOS, HPCA, etc.

15+

Brilliant researchers

With various backgrounds

5+

Active research projects

Embodied AI, 3D IC, RISCV, etc.

Research Areas

Computer Architecture

CPU micro-Architecture, GPU micro-Architecture, FPGA, Tensor Core, Domain Specific Accelerator, etc.

Artificial Intelligence

Machine Learning, Large Language Model (LLM), Quantization and Compression, Sparsity, Number-formats, AI-assisted design automation, etc.

VLSI & Design Automation

3D-IC, Process-in-Memory (PIM), Chiplet, Serdes, Interposers, Advanced Packaging Methods, EDA Softwares, Hardware Abstraction, etc.

Meet Our Team

World-class researchers pushing the boundaries of science and engineering

Principal Investigator

Yuan Xie

Yuan Xie

Chair Professor

Fang Professor of Engineering | Chair Professor | IEEE/ACM/AAAS Fellow

Postdoctoral Researchers

Chen Bai

Chen Bai

Postdoctoral Researcher

Chen Bai's research interests include computer architecture and electronic design automation. He received best paper awards from ICCAD 2021 and ISPD 2024.

Bangyan Wang

Bangyan Wang

Postdoctoral Researcher

Ceyu Xu

Ceyu Xu

Postdoctoral Researcher

Hao Yu

Hao Yu

Postdoctoral Researcher

Zhenhua Zhu

Zhenhua Zhu

Postdoctoral Researcher

Ph.D. Students

Xin Fan

Xin Fan

Ph.D. Student

Qi Liu

Qi Liu

Ph.D. Student

Shiyi Liu

Shiyi Liu

Ph.D. Student

My research focuses on technology-driven architecture design.

3D IC AI System
Ruyi Song

Ruyi Song

Ph.D. Student

Xiangfeng Sun

Xiangfeng Sun

Ph.D. Student

Xiangfeng Sun is an Ph.D. student at the Hong Kong University of Science and Technology specializing in computer architecture and VLSI. He aims for his research to be both meaningful and interesting.

Hongyi Wang

Hongyi Wang

Ph.D. Student

Hongyi Wang is currently a master student at Tsinghua University. His research interests include hardware-software co-design and FPGA-based accelerators. Hongyi Wang is set to join FACT Lab in 2025 to pursue his doctoral degree.

Yiran Xia

Yiran Xia

Ph.D. Student

Zhaohui Yang

Zhaohui Yang

Ph.D. Student

My research interests focus on quantum computer system design and fault-tolerant quantum computing, to bridge the gap between algorithms and bottom-layer physical devices.

Jiangnan Yu

Jiangnan Yu

Ph.D. Student

My research focuses on the relationship between Hardware Accelerators and High-Performance Computing (HPC).

Exchange Students

Ziyu Gu

Ziyu Gu

Exchange Student

Weikai Xu

Weikai Xu

Exchange Student

Recent Publications
(2026). PF-LLM: Large Language Model Hinted Hardware Prefetching. Proceedings of the 31th ACM International Conference on Architectural Support for Programming Languages and Operating Systems.
(2025). AccelStack: A Cost-Driven Analysis of 3D-Stacked LLM Accelerators. 2025 IEEE/ACM International Conference on Computer Aided Design (ICCAD).
(2025). LLM. 265: Video Codecs are Secretly Tensor Codecs. Proceedings of the 58th IEEE/ACM International Symposium on Microarchitecture® 🏆Best Paper Award.
(2025). H2-LLM: Hardware-Dataflow Co-Exploration for Heterogeneous Hybrid-Bonding-based Low-Batch LLM Inference. Proceedings of the 52nd Annual International Symposium on Computer Architecture. 🏆Best Paper Award.
Lab News & Updates

FACT Lab Celebrates Professor Yuan Xie's 2025 CCF Overseas Science and Technology Award

FACT lab is pleased to announce that Professor Yuan Xie has been awarded the 2025 “CCF Overseas Science and Technology Award” by the China Computer Federation (CCF). This prestigious award recognizes his outstanding contributions to integrated circuit chip design, computer architecture, and electronic design automation. Professor Xie’s work in translating research into industrial applications and nurturing talent through educational initiatives has significantly advanced the field of computer science in China.

Recent Posts

体系结构发展的风向标:ISCA 2025 会议总结

带你一览计算机体系结构顶会ISCA 2025的精彩内容!本文深入解读了AI加速器、存储系统、量子计算等前沿方向的最新研究成果,展示了体系结构领域的技术风向与未来趋势。

avatar
Zhenhua Zhu

苦苦寻觅的通用LLM压缩算法,居然一直潜伏在视频编码里!

LLM.265研究发现,视频编码器本身就是一种高效的大模型张量编码器。原本用于播放8K视频的现成视频编解码硬件,其实压缩AI模型数据的效率也非常高,甚至超过了许多专门为AI开发的方案。

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Ceyu Xu

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The Hong Kong University of Science and Technology,

Clear Water Bay,

Kowloon,

Hong Kong

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