Prof. Huang is specialized in satellite remote sensing, atmospheric radiation, and climate modeling. Optimization, pattern analysis, and dimensional reduction are extensively used in his research for explaining observed spectrally resolved infrared spectra, estimating geophysical parameters from such hyperspectral observations, and deducing human influence on the climate in the presence of natural variability of the climate system. His group has also developed a deep-learning model to make a data-driven solar forecast model for use in the renewable energy sector.
My research focuses on the application of data science in educational research, so called learning analytics. I have experience analyzing educational data on a large-scale to understand a) how course design influence students’ learning behavior and b) how students form peer networks. My work involves using multiple educational data sources such as log-data in online learning environment, course information, students’ academic records, and location data gathered from campus WiFi networks. I am interested in network analysis, time-series analysis, and machine learning.