Song Han

Assistant Professor, MIT EECS


  • Anycost GANs for Interactive Image Synthesis and Editing
    J. Lin, R. Zhang, F. Ganz, S. Han, J. Zhu

  • Efficient and Robust LiDAR-Based End-to-End Navigation
    Z Liu, A. Amini, S. Zhu, S. Karaman, S. Han, D. Rus

Past publications at Stanford:


  • On-device Intelligence Workshop at MLSys’20, Organizing Committee
  • ICCAD’19, Program Committee
  • ICLR’19, Area Chair
  • HPCA’18, Program Committee

Invited Talks

Efficient AI on the edge, auto AI; model compression, gradient compressioncompact model design, sparsity, auto pruning,  auto quantization, neural architecture search, efficient video recognition, efficient 3D point cloud, efficient transformer, specialized model, sparse hardware accelerator, accelerating compressed NN, FPGA.

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