Research Interests
I am generally interested in Brain-inspired Artificial Intelligence, Brain-inspired Cognitive Robotics, Ethics and Governance 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, Ethics and Governance 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.
Selected Projects
  • Brain-inspired Cognitive Intelligence Engine (BrainCog) : (2013.6-) [Principle Investigator] is a brain-inspired neural network based platform for simulating the cognitive brains of different animal species at multiple scales and realizing brain-inspired Artificial Intelligence. The long term goal of BrainCog is to provide a comprehensive theory and system to decode the mechanisms and principles of human intelligence and its evolution, and develop artificial brains for brain-inspired conscious living machines in future human-machine society.
  • Linking Artificial Intelligence Principles (LAIP) : (2018.10-) [Principle Investigator] Various Artificial Intelligence Principles are designed with different considerations, and none of them can be perfect and complete for every scenario. Linking Artificial Intelligence Principles (LAIP) is an initiative and platform for synthesizing, linking, and analyzing various Artificial Intelligence Principles World Wide, from different research institutes, non-profit organizations, non-governmental organizations, companies, etc. The efforts aim at understanding in which degree do these different AI Principles proposals share common values, differ and complete each other.
  • BORN: 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.
  • Linked Brain Data (LBD) : A large-scale, multi-modal brain knowledge base (2013.7 -) [Principle Investigator] This project is an effort for extracting and linking Neuroscience data and knowledge from multiple scale and multiple data sources together. The LBD platform provides services for neuroscience knowledge extraction, structured neuron data representation, neuron data integration, visualization, analysis, semantic search (through SPARQL queries) and reasoning over the integrated Neuron data.
  • The Large Knowledge Collider (LarKC) : (2008.4-2011.9) This project is a European funded 7th Framework Project. My research in LarKC was related to: (1) Retrieval and Reasoning based on vague or incomplete queries. (2) Unifying Search and Reasoning using various strategies such as the human interests centric approach, and multi-scale knowledge processing approach, etc.
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