Four Papers Accepted in DATE'2025

Four papers, including 3 on efficient AI and 1 on privacy-preserving AI, are accepted by DATE'2025 as regular papers.

Last updated on Nov 13, 2024

Papers on privacy-preserving AI:

  • FLASH: An Efficient Hardware Accelerator Leveraging Approximate and Sparse FFT for Homomorphic Encryption

Papers on efficient AI:

  • LightMamba: Efficient Mamba Acceleration on FPGA with Quantization and Hardware Co-design
  • SCALES: Boost Binary Neural Network for Image Super-Resolution with Efficient Scalings
  • Compact Non-Volatile Lookup Table Architecture based on Ferroelectric FET Array through In-Situ Combinatorial One-Hot Encoding for Reconfigurable Computing
Conference
Meng Li
Meng Li
Assistant Professor

I am currently a tenure-track assistant professor jointly affiliated with the Institute for Artificial Intelligence and School of Integrated Circuits in Peking University. My research interests focus on efficient and secure multi-modality AI acceleration algorithms and hardwares.

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