Yulin Fu
Doctoral Candidate in Computer Science
University of Auckland / Auckland, New Zealand
Advised by Dr. Sean Longyu Ma (Main Supervisor) / Associate Professor Bruce Sham (Co-supervisor)
PhD student in Computer Science at the University of Auckland. My research focuses on hardware acceleration for deep learning — including FPGA-based edge AI systems, high-level synthesis (HLS) automation, and FPGA-driven LLM acceleration.
Research interests
- FPGA-based Hardware Acceleration
- Edge AI Systems
- Neural Network Accelerators
- High-Level Synthesis (HLS)
- LLM Acceleration
Experience timeline
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Sep 2025 — present
PhD, Computer Science
University of Auckland / Auckland, New Zealand
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Mar 2023 — Sep 2025
M.Sc., Computer Science
University of Auckland / Auckland, New Zealand
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Sep 2019 — Jun 2023
B.E., Computer Science
Northeast Forestry University / Harbin, China
Recent news
All news →- Participated in the University of Auckland Open Day 2026
- SGRM accepted at FPT 2026
- Attended the 8th Beijing Zhiyuan Conference
- Presented at MCSoC 2025
- Online presentation at GCCE 2025
Selected publications
All publications →-
RedPIM: An Efficient PIM Accelerator Design with Reduced Analog-to-Digital Conversions
J. Li, Y. Fu, S. Longyu, et al.
ACM Transactions on Design Automation of Electronic Systems, 2026
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SGRM: Sensitivity-Guided Resource Minimization for FIFO Design Space Exploration in HLS Dataflow Designs
Y. Fu, J. Zhu, J. Li, et al.
The 2026 International Conference on Field Programmable Technology (FPT 2026), 2026
Accepted
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An Efficient FPGA-Based Edge AI System for Railway Fault Detection
Y. Fu, D. Yan, J. Li, et al.
IEEE Consumer Electronics Magazine, 2025