Jeffrey Mei

- Applied convolutional neural networks to sea ice imagery to infer ice thickness and snow depth from surface topography and interactively visualized the learned filters (OpenCV, PyTorch and AWS EC2) - Developed textural segmentation algorithm to distinguish different deformed sea ice surfaces (OpenCV) - Developed an algorithm with an interactive user interface to distinguish and delineate sea ice floes within open water (OpenCV)

- Developed a novel method for localizing glacial collapse using signal processing and hyperbolic geometry - Visualized seismic spectrograms and bandpass-filtered signals to automate detection of seismic shock wave onset - Collected oceanographic and seismic data during 2-week fieldwork in Greenland

Major in Applied Ocean Physics Minor in Data Science Thesis: "Morphological Approaches To Understanding Antarctic Sea Ice Thickness“

B.S. in Mathematics and Physics Honors thesis in geophysics, "Calving localization at Helheim Glacier using multiple local seismic stations“