AI theory, machine learning, safety and alignment of large models, generative AIs, etc.

Developing learning systems that rapidly acquire knowledge and adapt to new environments

The Convergence and Empowerment of AI and Neuroscience, and Brain-Computer Interface Algorithms

Advancing scientific observation with AI to accelerate scientific discovery

The cross-empowerment between artificial intelligence and software engineering: AI for SE and SE for AI

Egocentric Vision & Multimodal Generative AI

Interactive Embodied Intelligence powered by World Model, Dexterous Control and Sensing, and Embodied Foundation Model.

Mainly engaged in research related to multimodal large models and natural language processing.

AI+Science

Structured Representation Learning for Scientific Intelligence: Bidirectional Synergy between AI and Science

AI Economics, Generative Model Economics, Multi-Agent, Reinforcement Learning