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Shujie Wang’s research is centered at the intersection of cryospheric science, remote sensing, numerical modeling, and machine learning. He is broadly interested in understanding and studying past, present, and future cryospheric changes and processes, and their interactions with the atmosphere, ocean, biosphere, and human systems. His current research focuses on ice sheet processes, which are understood to be parameterized, representing large uncertainties in modeling the coupled ice-ocean-atmosphere system for projecting future sea-level rise. Specifically, Dr. Wang is currently studying Antarctic ice shelf dynamics, fractures, and controls on ice shelf instability using satellite optical, microwave, altimetry data, ice flow models, and climate model reanalysis data. He is also investigating the spatiotemporal dynamics of glacier algae on the Greenland Ice Sheet to quantify the role of ice surface changes. He is particularly intrigued by the possibility of developing novel approaches to solve research questions from interdisciplinary and multidisciplinary perspectives, such as using ocean color remote sensing to study algal blooms on ice surfaces and developing algorithms to extract ice sheet fractures and drumlin geomorphological features from altimetric measurements. In the context of big data, he is interested in ‘intelligently’ coupling observations and models using emerging advanced data-driven methods to address questions relating to land-water-climate-biological systems. His work is funded by grants from the National Aeronautics and Space Administration (NASA), National Science Foundation (NSF), United States Department of Agriculture, and Penn State seed programs. Before joining Penn State, he was a postdoctoral research scientist at the Lamont-Doherty Earth Observatory at Columbia University.
GRE scores are highly recommended but not strictly required for Applied Linguistics.