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“Automated Geoscience with Robotics and Machine Learning: A New Hammer of Rock Mapping, Detection, and Dynamics Analysis”

Abstract: Despite the rapid adoption of robotics and machine learning in industry, their application to scientific studies remains under-explored. Combining industry-driven advances with scientific exploration provides new perspectives and a greater understanding of the planet and its environmental processes. Focusing on rock detection, mapping, and dynamics analysis, I present technical approaches and scientific results of developing robotics and machine learning technologies for geomorphology and seismic hazard analysis. I demonstrate an interdisciplinary research direction to push the frontiers of both robotics and geosciences, with potential translational contributions to commercial applications for hazard monitoring and prospecting. 

Biography: Dr. Zhiang Chen is a Postdoctoral Research Scholar at the School of Earth and Space Exploration at Arizona State University. He conducts research in automated geoscience. Aiming to push interdisciplinary research, he develops robotics and machine learning technologies for geosciences, focusing on seismic hazard analysis, geomorphology, disaster assessment, and environmental monitoring.

The UW Data Science Seminar is an annual lecture series at the University of Washington that hosts scholars working across applied areas of data science, such as the sciences, engineering, humanities and arts along with methodological areas in data science, such as computer science, applied math and statistics. Our presenters come from all domain fields and include occasional external speakers from regional partners, governmental agencies and industry.

The 2022-2023 seminars will be virtual, and are free and open to the public.