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.
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
李萌
助理教授、研究员、博雅青年学者
李萌，北京大学人工智能研究院和集成电路双聘助理教授、研究员、博雅青年学者。他的研究兴趣集中于高效、安全的多模态人工智能加速算法和芯片，旨在通过算法到芯片的跨层次协同设计和优化，为人工智能构建高能效、高可靠、高安全的算力基础。