JIANG Chunbi specializes in new energy power forecasting and renewable energy integration. She received her undergraduate degree from the University of Science and Technology of China (USTC) and earned her Ph.D. from the University of Texas at Austin, USA. With four years of experience in the development and deployment of new energy power forecasting systems, her research focuses on advancing algorithms for wind and solar power forecasting to improve prediction accuracy and support the stable and efficient operation of modern power systems.

Selected Publications

1. Jiang, C., D. Zhang, 2024, Lithofacies identification from well-logging curves via integrating prior knowledge into deep learning: Geophysics, 89 (1): 1JF-WB87

2. Jiang, C., D. Zhang, and S. Chen, 2022, Handling missing data in well-log curves with a gated graph neural network: Geophysics, 88 (1): 1JF-Y3

3. Jiang, C., D. Zhang, and S. Chen, 2021,Lithology identification from well-log curves via neural networks with additional geologic constraint: Geophysics, 86 (5): IM85–IM100

▪ New Energy Power Forecasting and Uncertainty Analysis

▪ Virtual Power Plant Optimization and Distributed Energy Aggregation