Xiaolong Luo

Associate Professor Supervisor of Master's Candidates

E-Mail:
School/Department:地球科学学院
Education Level:With Certificate of Graduation for Doctorate Study
Gender:Male
Degree:博士
Professional Title:Associate Professor
Discipline:Cartography and Geographical Information System
Enrollment disciplines: Cartography and Geographic Information Engineering Cartography and Geographical Information System , Computer Application Technology , Computer Science and Technology , Software Engineering ,

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Luo Xiaolong, Han Chinese, graduated from East China University of Technology (formerly East China Institute of Geology) in 2000 with a Bachelor's degree in Surveying and Mapping Engineering. After briefly working in the industry, he returned to pursue a Master's degree at the same university and graduated in 2004. In July of that year, he joined Yangtze University, where he has been wo...

Educational Experience
Awards and Honours
Academic Honor

1996.9~2000.6
华东地质学院测绘工程 University graduated

Work Experience
Social Affiliations
Research Focus

2004.7~
长江大学地球科学学院

Pan-Spatial Intelligent Systems and Metaverse-Geospatial Collaborative Innovation Research ——Spatiotemporal-Coupled GeoAI Modeling and Phygital Symbiosis Technology Exploration

Paper Publications
Patents
Published Books

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Name of Research Group:: Geospatial-Metaverse Intelligent Synergy Laboratory

Description of Research Group:: Team Introduction
GeoVerse Synergy Lab is an interdisciplinary research team rooted in geospatial intelligence and advancing the frontiers of metaverse technologies. We are committed to driving full-chain innovation in the integration of "Geospatial Information (Geo) - Artificial Intelligence (AI) - Metaverse (Metaverse)". Leveraging cross-domain expertise in geomatics, computer science, industrial engineering, and cultural heritage conservation, we conduct systematic research in the following areas:

Research Areas and Core Competencies
Geospatial Intelligent System Development:

Develop high-precision spatial analysis algorithms (e.g., spatiotemporal data indexing, multi-source heterogeneous data fusion) to build pan-spatial dynamic decision platforms for smart cities and oil/gas exploration, supporting territorial spatial planning and disaster emergency response.
Phygital (Physical-Digital) Interaction Technologies:

Integrate multimodal machine learning (vision/tactile/acoustic perception) and immersive virtual reality engines to create industrial digital twins (e.g., smart production line simulation, 3D oilfield modeling), enabling real-time bidirectional mapping between physical and virtual spaces.
Metaverse Collaborative Space Construction:

Explore cutting-edge technologies such as distributed blockchain protocols and brain-computer interfaces to develop metaverse industrial operating systems for cross-regional collaboration, driving paradigm innovation in human-machine-environment synergy.
Technical Highlights
Spatiotemporal Coupled Modeling Framework:
Based on Academician Zhou Chenghu’s "Pan-Spatial Information Theory", we establish a dynamic association rulebase between geographic entities and metaverse spaces, resolving spatiotemporal modeling challenges in complex scenarios like urban flood simulation and logistics path optimization.

Multimodal Perception Middleware:
Integrate LiDAR point cloud processing, cross-modal transfer learning (e.g., fusion of remote sensing imagery and social media data), and physics engine simulations (Unity3D/Unreal Engine) to construct a 100,000-user concurrent phygital interaction testing ground.

Industry-Academia-Research Collaboration:
Partner with institutions such as the Hubei Provincial Museum to establish a Metaverse Joint Innovation Center, advancing applications in cultural heritage digitization and industrial production line digital twins.

Team Mission
"Reconstructing Spatial Cognition with Geography, Driving Phygital Symbiosis with Intelligence" — Building a spatial intelligence foundation for the digital twin era, empowering smart cities, Industry 4.0, and sustainable cultural heritage preservation.

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Xiaolong Luo