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Wu Man  呉 漫

Researcher Number 30965330
Other IDs
  • ORCIDhttps://orcid.org/0000-0002-8459-2028
Affiliation (Current) 2026: 慶應義塾大学, 理工学研究科(矢上), 特任助教
Affiliation (based on the past Project Information) *help 2026: 慶應義塾大学, 理工学研究科(矢上), 特任助教
2024: 慶應義塾大学, 理工学研究科(矢上), 研究員
2023: 慶應義塾大学, 理工学研究科(矢上), 特任助教
2022: 慶應義塾大学, 理工学研究科(矢上), 研究員
Review Section/Research Field
Principal Investigator
Basic Section 60090:High performance computing-related / 1001:Information science, computer engineering, and related fields
Keywords
Principal Investigator
Edge intelligence / Spiking neural netwrok / Accelerator / Neural network / Calculator-free / Hyper-parallel / Computing architecture / Multi-tenant / Generative model / Accelarators … More / Low latecny / Spiking neural network / NN Accelarators / Low-Latency / Edge AI / Energy Efficiency / NoC Design / DiaNet / Co-Design / SNN Accelerator Less
  • Research Projects

    (2 results)
  • Research Products

    (7 results)
  •  Memory- and Compute-Efficient LLM Decoding Accelerator with DRAM-PIM Optimized by Cross-Bank SchedulingPrincipal Investigator

    • Principal Investigator
      呉 漫
    • Project Period (FY)
      2026 – 2028
    • Research Category
      Grant-in-Aid for Early-Career Scientists
    • Review Section
      Basic Section 60090:High performance computing-related
    • Research Institution
      Keio University
  •  Hyper-Parallel Calculator-Free Neural Network Accelerator for Edge AI ApplicationsPrincipal Investigator

    • Principal Investigator
      Wu Man
    • Project Period (FY)
      2022 – 2024
    • Research Category
      Grant-in-Aid for Research Activity Start-up
    • Review Section
      1001:Information science, computer engineering, and related fields
    • Research Institution
      Keio University

All 2024 2023 2022

All Journal Article Presentation

  • [Journal Article] Quantitative evaluation of molecular generation performance of graph-based GANs2024

    • Author(s)
      Zhang Jinli、Wang Zhenbo、Jiang Zongli、Wu Man、Li Chen、Yamanishi Yoshihiro
    • Journal Title

      Software Quality Journal

      Volume: - Issue: 2 Pages: 791-819

    • DOI

      10.1007/s11219-024-09671-7

    • Peer Reviewed / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-22K21285, KAKENHI-PROJECT-23KF0063
  • [Presentation] GKF-mQA: Generative Knowledge Fusion Based on Large Language Models for Enhancing Medical Question Answering2024

    • Author(s)
      Man Wu
    • Organizer
      Advanced Data Mining and Applications (ADMA 2024)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-22K21285
  • [Presentation] Training Low-Latency Spiking Neural Network with Orthogonal Spiking Neurons2023

    • Author(s)
      Man WU
    • Organizer
      In 2023 21st IEEE Interregional NEWCAS Conference (NEWCAS)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-22K21285
  • [Presentation] Training a General Spiking Neural Network with Improved Efficiency and Minimum Latency2023

    • Author(s)
      Man WU
    • Organizer
      Proceedings of the 15th Asian Conference on Machine Learning, PMLR
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-22K21285
  • [Presentation] Mode Collapse Alleviation of Reinforcement Learning-based GANs in Drug Design2023

    • Author(s)
      Man WU
    • Organizer
      2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-22K21285
  • [Presentation] Exploring the Feasibility of Transformer Based Models on Question Relatedness2022

    • Author(s)
      Honglin Shu; Pei Gao; Ziwei Yang; Chen Li; Man Wu
    • Organizer
      IEEE HPCC-2022 24th International Conference on High Performance Computing and Communications
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-22K21285
  • [Presentation] Learning Local Representation by Gradient-Isolated Memorizing of Spiking Neural Network2022

    • Author(s)
      Man Wu, Zheng Chen, Yunpeng Yao
    • Organizer
      IEEE HPCC-2022 24th International Conference on High Performance Computing and Communications
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-22K21285

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