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GitHub4 public repositories · AIMIA-PKU ↗ · RT-DETR ↗
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AIMIA 实验室
Our research focuses on embodied intelligence, multimodal intelligence and AI for Science (AI4S).

Associate professor
School of Electronic and Computer Engineering
Peking University Shenzhen Graduate School
4 public repositories · AIMIA-PKU ↗ · RT-DETR ↗
Updated
Jie Chen · h-index 64
Updated
An agent planner decomposes goals, while a native-action agent or VLA model executes actions. Environment feedback informs the next plan.
Select an action to explore planning and execution.
Studying the relationships between images, video and language through cross-modal representations and alignment.
Explore the alignment between scene regions and language concepts.
Combining data and learning methods to study biomolecular representations, property prediction and scientific modeling.
Illustration: build molecular representations from an amino-acid sequence.
Interactive research illustrations
Six latest publications · by publication year
Awards & academic recognition
First Prize, National Science and Technology Progress Award.
Zhiwei Nie received a Youth Outstanding Paper Award at the World Artificial Intelligence Conference for “A unified evolution-driven deep learning framework for virus variation driver prediction”.
Second Prize in the national final and First Prize in Guangdong, 2024 “Data Elements ×” Competition.
“Zu Chongzhi” Annual Major Achievement Award for Frontier Innovation in Artificial Intelligence.
Special Prize, Guangdong Science and Technology Progress Award.
The joint team involving our group was one of three finalists worldwide for the ACM Gordon Bell Special Prize for HPC-Based COVID-19 Research, and the only finalist team from China.
First place on a CAMEO monthly leaderboard for protein structure prediction.
How can an agent planner collaborate with native-action agents or VLA models to act in the physical world?
Exploring a hierarchical architecture with an agent planner and either a native-action agent or a VLA model, connecting task planning, action execution and environment feedback.
Research enquiriesHow can models understand and generate content across visual and language modalities?
Understanding and generating content across vision and language, including images, videos and human motion.
Related publication · TCSVT 2026DemoChain: Decoupled Motion-Chain for Multi-Action Video GenerationHow can AI support scientific prediction and discovery in biology and medicine?
Developing AI methods for biomolecular prediction and design, virus evolution, protein structure and medical image analysis.
Related publication · Nature Communications 2026SplitSeek-Pro: accurate prediction of splittable sites on protein structuresOur group brings together doctoral researchers and master's students working across our research areas.
Meet the group, explore members' research interests and find our alumni directory.
Students interested in embodied intelligence, multimodal intelligence or AI for Science (AI4S) can find contact details and admissions information here.
Prospective studentsA shared curiosity, across places and time zones.
Pageviews & geographic distribution