Research Interests

I am generally interested in Brain-inspired Artificial Intelligence, Brain Simulation, Brain-inspired Cognitive Robotics, Risks and Ethics of Artificial Intelligence. My current research interests focus on the following directions:

  • Brain-inspired Cognitive Computation Models.
  • Brain-inspired Neural Networks.
  • Brain-inspired Cognitive and Neural Robotics.
  • Cognitive Brain Modeling and Simulation.
  • Philosophy, Risks and Ethics of Artificial Intelligence.

The goal for my research on Brain-inspired Intelligence is to propose and implement a Cognitive Computation Model for Brain-inspired Artificial General Intelligence, which is the "brain" for future intelligent living machines. Please visit my Publication page for more details.

 
 

Brain-inspired Cognitive 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 machines in human-machine society.

  BrainBo is a series of cognitive robotics with a CASIA brain (a multi-scale brain simulator developed at the Institute of Automation, Chinese Academy of Sciences). The CASIA brain is the core of BrainBo for coordinating its various cognitive behaviors, including but not limited to multi-modal sensation and perception (vision, audition, touch, etc.), language, prediction, reasoning, decision making, self-consciousness, etc. The goal for BrainBo is towards robots with Artificial General Intelligence.   Linked Brain Data (LBD) is an effort for extracting, integrating, linking and analyzing Brain data and knowledge from multiple scale and multiple data sources and support comprehensive understandings of the brain. LBD is proud to present the association graph among various cognitive functions, brain diseases and their relationships to brain building blocks at multiple scales. This association graph provide inspirations for future Neuroscience and Brain-inspired Intelligence research.
 
Recent Projects
  • Brain-inspired Cognitive Engine (2013.6-) [Principle Investigator]
  • Harmonious Artificial Intelligence Principles [2018.7-] [Principle Investigator]
  • Linked Brain Data : A large-scale, multi-modal brain knowledge base (2013.7 -) [Principle Investigator]
  • Brain-inspired Cognitive Computation Models (2015.6-2017.6) [Principle Investigator]
  • Visual Pathway Computational Modeling and Its Applications to Unmanned Aerial Vehicle (2015.1-2016.12) [Principle Investigator]
 
Teaching
  • Introduction to Brain-inspired Intelligence [2017, 2018], University of Chinese Academy of Sciences
  • System and Computational Neuroscience [2018], University of Chinese Academy of Sciences
  • Philosophy and Ethics of Artificial Intelligence [2018], University of Chinese Academy of Sciences
 

What's New!

  • BrainBo is realeased. It is a series of Cognitive robotics with a CASIA Brain. The first release is based on a NAO robot. The video shows the cognitive ability of BrainBo on inductive reasoning, object recognition and interpretation.
  • Linked Brain Data (LBD) Platform has been released. Linked Brain Data (LBD) is an effort for extracting and linking Brain and Neuroscience data and knowledge from multiple scale and multiple data sources together. The LBD platform provides services for Brain and Neuroscience knowledge extraction, structured data representation, integration, visualization, analysis, semantic search and reasoning over the integrated Brain and Neuroscience data.