Wei Xiangqing

Wei Xiangqing

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Wei Xiangqing

I am currently a research assistant at Chiba University, Japan. My research focuses on AI accelerator architecture, reinforcement-learning-driven scheduling, and hardware-software co-design for neural network accelerators.

My current research interests include reinforcement learning based scheduling for NPU architectures, tile-level execution optimization for CNN accelerators, sparse neural network acceleration, and FPGA-based hardware validation.

Academic Background

Research Assistant
Chiba University, Japan
Research area: AI accelerators, NPU scheduling, reinforcement learning, FPGA-based accelerator design.

Master’s Degree in Integrated Circuit Engineering
Guizhou University, China
Research area: RISC-V processor design, integer execution units, Booth multiplication, SRT division, and digital circuit design.

Research Interests

  • AI hardware architecture
  • NPU and FPGA-based DNN acceleration
  • Reinforcement learning for accelerator scheduling
  • Tile-level DAG modeling and scheduling optimization
  • Hardware-software co-design
  • FPGA-based accelerator validation

Research Experience

My recent work focuses on xxxxxx.

Skills

  • Programming: Python, C/C++, SystemVerilog, Verilog
  • Hardware design: RTL design, FPGA prototyping, digital IC design
  • Research: reinforcement learning, DNN accelerator design, computer architecture

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