- Statistics
- Machine Learning
- Data Science
- +۶ مورد دیگر
Wei-Min Huang is a Professor in the Department of Mathematics at Lehigh University. He joined Lehigh in 1982 as an Assistant Professor, was promoted to Full Professor in 1995, and served as Chair of the Mathematics Department from 2007 to 2016, with an interim role in 2018. His research focuses on statistical theory and applications, including semiparametric modeling, nonparametric methods, and interdisciplinary collaborations in bioinformatics, engineering, and environmental science. Huang has published extensively in top-tier journals, addressing topics like GARCH models, plasma processes, and epidemiological forecasting. Education: Ph.D. in Statistics, University of Rochester (1982). Research Interests: Huang’s work bridges foundational statistics and applied domains. Key areas include semiparametric efficiency, kernel density estimation, and statistical applications in wireless networks and bioinformatics. Recent research extends to sustainable chemistry processes and optimal sampling strategies in ecology. His methods emphasize robustness and adaptability, with tools like the Bickel-Rosenblatt test and approximate entropy. Articles Trends: Recent publications highlight interdisciplinary applications, such as cold plasma reforming for hydrogen production and ensemble algorithms for influenza prediction. Earlier contributions include foundational work on semiparametric models and bootstrap methods for financial time series. Advising & Grants: Huang has supervised numerous Ph.D. students, fostering collaboration across disciplines. His grants and partnerships span statistical theory, environmental engineering, and materials science. Labs/Teams: Engaged in collaborative projects with engineering and chemistry departments, particularly on plasma-catalyzed processes and material characterization through XPS spectroscopy.