(734) 936-0491

Applications:
Astronomy and Cosmology, Earth Science, Environmental Sciences, Physics
Methodologies:
Algorithms, Artificial Intelligence, Bayesian Methods, Classification, Data Mining, Data Visualization, Deep Learning, High-Dimensional Data Analysis, Machine Learning, Mathematics, Missing Data and Imputation, Optimization, Pattern Analysis and Classification, Statistical Modeling, Statistics, Time Series Analysis

Xianglei Huang

Professor

Department of Climate and Space Sciences and Engineering

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.