Topic
- Computing and Processing
- Components, Circuits, Devices and Systems
- Communication, Networking and Broadcast Technologies
- Power, Energy and Industry Applications
- Signal Processing and Analysis
- Robotics and Control Systems
- General Topics for Engineers
- Fields, Waves and Electromagnetics
- Engineered Materials, Dielectrics and Plasmas
- Bioengineering
- Transportation
- Photonics and Electrooptics
- Engineering Profession
- Aerospace
- Geoscience
- Nuclear Engineering
- Career Development
- Emerging Technologies
- Telecommunications
- English for Technical Professionals
Chenjuan Guo
Affiliation
School of Data Science & Engineering, East China Normal University, Shanghai, China
Topic
Graph Convolutional Network,Spatial Dependence,Spatiotemporal Model,Catastrophic Forgetting,Cognitive Learning,Concept Drift,Data Augmentation,Data Augmentation Methods,Data Streams,Deep Learning,Holistic Representation,Incremental Learning,Mean Absolute Error,Replay Buffer,Root Mean Square Error,Siamese Network,Spatio-temporal Prediction,Spatiotemporal Data,Spatiotemporal Representation,Traffic Flow,Traffic Prediction,Training Data,Autoregressive,Autoregressive Integrated Moving Average,Category Information,Concentration Values,Convolutional Network,Convolutional Neural Network,Current Data,Data Privacy,Dijkstra’s Algorithm,Edge Weights,Embedding Vectors,Error Accumulation,Exchange Rate,Federated Learning,Forecast Error,Forecast Values,Forecasting Model,Gaussian Mixture Model,Global Model,Global Navigation Satellite System,Global Trends,Graph Database,Graph Topology,Greenhouse Gas,Historical Observations,Historical Sequence,Impact Of Fluctuations,Learning Module,
Biography
Chenjuan Guo received the PhD degree in computer science from the University of Manchester, U.K., in 2011. She is a professor with East China Normal University, China. She was previously with Aalborg University, Denmark. Her research interests include spatial-temporal data management and data analytics.