DONGCHENG
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Dongcheng Zhao

I am now the Assistant Professor at BrainCog Lab. I currently focus on Brain inspired LLM, Brain inspired Super Safe Alignment, Spiking Neural Networks, Event Based Vision, etc. Before that, I did my PhD at Institute of Automation, Chinese Academy of Sciences, where I was advised by Prof. Yi Zeng. I did my bachelors at school of mathematics and statistics, Xidian University.

I currently serve as a reviewer for several leading conferences and journals, including IJCAI, NeurIPS, ICLR, Neural Networks, Neurocomputing, Pattern Recognition and IEEE TNNLS, TIP, TETCI.

Email  /  Google Scholar  /  Zhi Hu  /  DBLP

News

  • 12/2024, Two Papers have been accepted by AAAI 2025.
  • 11/2024, Two Papers have been accepted by DATE 2025
  • 11/2024, 2023 Cell Press China Paper of the Year Award (in interdisciplinary science category)
  • 11/2024, Our paper has been accepted by TCAS-I Regular Papers.
  • 10/2024, Our paper has been accepted by Pattern Recognition.
  • 09/2024, Our paper has been accepted by NeurlPS.
  • 07/2024, Our paper has been accepted by ACM MM.
  • 06/2024, Our paper has been accepted by Neural Networks.
  • 05/2024, Our paper has been accepted by FPL.
  • 05/2024, Our paper has been accepted by Neural Networks.
  • 04/2024, Our paper has been accepted by IJCAI.
  • 03/2024, Our paper has been accepted by TCAD 2024.
  • 02/2024, Our paper has been accepted by CVPR.
  • Recent Projects

    Recently, I mainly focus on the development of BrainCog and Born.

  • BrainCog
  • Project Page | Paper

    BrainCog is accepted by Patterns! Brain-inspired Cognitive Intelligence Engine (BrainCog) is a brain-inspired neural network based platform for realizing Brain-inspired Artificial Intelligence, and simulating the cognitive brains of different animal species at multiple scales. The ultimate goal and long term efforts of BrainCog is to provide a comprehensive theory and systems to decode the mechanisms and principles of human intelligence and its evolution, and develop artificial brains for brain-inspired conscious living becomings for the future human-AI symbiotic society.

  • BORN
  • Project Page

    BORN is an Artificial Intelligence Engine based on Brain-inspired Spiking Neural Networks. The ultimate vision of BORN is to achieve living Artificial General Intelligence, as a new type of evolutionary becoming, and as a moral member of the future symbiotic society. The near term goal of BORN is a self enabled learning AI powered by spiking neural networks that can coordinate various cognitive functions in a self organized way to solve complex problems. BORN is powered by BrainCog, the Brain-inspired Cognitive Intelligence Engine.

    Publications

    I'm interested in devleoping biologically plausible Spiking Neural Networks with high performance for image recognition, tracking and robot control, etc.

    Preprint
    Publications
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