Applications:
Complex Systems, Computer Science, Earth Science and Ecology, Environmental and Climate Research, Physical Science
Methodologies:
Artificial Intelligence, Bayesian Methods, Causal Inference, Computer Vision, Computing, Data Integration, Data Mining, Data Visualization, Databases and Data management, Geographic Information Systems, Graph-Based Methods, Image Data, Machine Learning, Mathematical and Statistical Modeling, Optimization, Statistics

Cheng Li

Assistant Professor

Climate and Space Sciences and Engineering

My research focuses on developing advanced numerical models and computational tools to enhance our understanding and prediction capabilities for both terrestrial and extraterrestrial climate systems. By leveraging the power of data science, I aim to unravel the complexities of atmospheric dynamics and climate processes on Earth, as well as on other planets such as Mars, Venus, and Jupiter.

My approach involves the integration of large-scale datasets, including satellite observations and ground-based measurements, with statistical methods and sophisticated machine learning algorithms including vision-based large models. This enables me to extract meaningful insights and improve the accuracy of climate models, which are crucial for weather forecasting, climate change projections, and planetary exploration.