Vision:

  • "I want to understand how the brain works, not just from a philosophy perspective, not just in a general way, but in a detailed nuts and bolts mathematical and engineering ways. My desire is not only to understand what intelligence is and how the brain works, but how to build machines that work in the same way. I want to build truly intelligent machines." inspired by J. Hawkins.

Interests:

  • Representation Learning: If there exsits the unified theory in machine learning, computer vision, and pattern recognition, I believe in that it MUST be representation learning. Under the framework of representation learning,
    • trying to explore and understand the mechanism and way of encoding sensory data employing by our brain;
    • developing unsupervised and weakly supervised deep learning methods with high interpretability in result and structure;
    • designing new methods for subspace learning, clustering, dimension reduction, and manifold learning.
    • revisiting transfer learning, metric learning, etc;
  • Differentiable Programming: The basic idea is to treat neural network as a language to describe the physical variables and their relationships.

Awards and Honors:

  • Top 200 Reviewer for NeurIPS 2018.
  • Double 100 Talents of Sichuan University.
  • 1000 Talents of Sichuan Province.

Professional Activity:

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