Guodanhuai

Danhui Guo is a Professor and Ph.D. Supervisor. He received his M.S. degree from Wuhan University and his Ph.D. degree from the Graduate University of the Chinese Academy of Sciences. He is currently the Director of the Spatio-Temporal Data Intelligence Laboratory at Beijing University of Chemical Technology. He has been selected for a provincial-level high-level talent program. He is a Senior Member of the China Computer Federation (CCF), a Corresponding Executive Committee Member of the CCF Big Data Technical Committee, an Executive Committee Member of ACM SIGSPATIAL China, and a Committee Member of the Hybrid Intelligence Technical Committee of the Chinese Association for Artificial Intelligence. He serves as an Editorial Board Member of the Journal of Safety Science and Resilience, and as Associate Editor and Action Editor of Geoinformatica.

His main research interests include high-performance geospatial computing, spatio-temporal geographic intelligence (GeoAI), anomaly detection, and large-scale model methodologies. He has long been engaged in theoretical research and engineering applications of complex spatio-temporal data analysis, and has established systematic research achievements in the fields of geospatial computing and intelligent diagnosis of high-end equipment.

In the field of high-performance geospatial computing, his research focuses on spatial cognition, scene generation, and representation learning. Related成果 have been published in leading international journals such as ACM Transactions on Intelligent Systems and Technology (TIST), International Journal of Applied Earth Observation and Geoinformation, Journal of Safety Science and Resilience, Journal of Big Data, and ISPRS International Journal of Geo-Information.

In the field of aerospace high-end equipment, his research group has developed intelligent diagnosis and prognostic models, and proposed core technologies including streaming sensor data analysis, fault knowledge graphs, and dynamic threshold-based anomaly detection. These technologies have been successfully applied to anomaly detection and lifetime assessment of spacecraft propulsion systems, providing strong technical support for ground testing, operation, and maintenance of major national aerospace missions such as the BeiDou Navigation Satellite System, the Chang’e lunar exploration program, and the China Space Station.

He has served as the principal investigator of three National Natural Science Foundation of China (NSFC) General Programs, as well as an NSFC Major Research Plan (cultivation project), sub-projects of the Ministry of Science and Technology Torch Program, and sub-projects of the CAS “12th Five-Year Plan” Informatization Program, totaling more than ten national-level projects. He has published nearly 100 academic papers in international journals such as The Lancet, Nature Communications, WWW Journal, Geoinformatica, ACM Transactions on Intelligent Systems and Technology (TIST), Neurocomputing, and Journal of Computer Science and Technology, as well as in top-tier international conferences including DASFAA and ACM SIGSPATIAL. He has authored two academic monographs and holds more than ten granted invention patents. He has received the First Prize of the ACM GIS Cup 2014, the Third Prize of the China VIS & VAST Challenge 2015, the Second Prize of the China VIS & VAST Challenge 2018, and the First Prize of SpatialDI 2020. In addition, he has undertaken multiple collaborative research projects with aerospace and chemical industry enterprises.

1. Geographic big data and geographic spatiotemporal intelligence

2. Data driven deep learning

3. Geographic Large Model

4. Health Management of Aerospace and Chemical Equipment

Undergraduate Course：

    Nosql databases

    Nosql databases Experiment

    Introduction to Big Data Science and Technology

    Computer System Architecture

    Principles of Data Mining

Postgraduate courses：

    Data Analysis and Data Intelligence