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Peter Gerstoft

NoiseLab
University of California, San Diego
Professor

Expertise: Seismology, Signal Processing and machine learning
 
 
About Me Publications
My research focus on data-driven computational geophysics and within these fields I further cover the subtopics: applied signal processing, inverse methods, mathematical models, extracting information from noise, and machine learning. I currently focus on developing new sensing techniques using large array sensor data. Data science methods (big data/machine learning) as well as compressive sensing is a main focus for sensing the physical environment. These techniques are applied to observing tsunamis, earthquakes, traffic, Antarctic signals, as well as extracting environmental information from noise.