Assistant Research Professor, School of Earth & Sustainability, Northern Arizona University
Philosophy & Approach
I’m a geosciences researcher in an era of ever-growing datasets.
I apply innovation in computation, geostatistics, and machine learning to problems in sedimentology, coastal and hydraulic engineering, geophysics, hydrology and geomorphology, by developing and applying novel data analytics to novel datasets.
I have developed algorithms and written multiple articles on stochastic statistics, machine learning and artificial intelligence for quantifying land cover, sediment properties, and oceanographic processes in images and acoustic data.
I am a strong supporter of open source software and I develop and contribute to community tools for scientific discovery.
Sediment: what is it made of, what lives in or on it, how it gets picked up by flows of air and water, how it forms and solves engineering problems, and how it modifies landforms in deserts, rivers and seas.
I have a Ph.D in Coastal Geomorphology/Nearshore Oceanography from the University of Plymouth, UK (2008). My doctoral research was on gravel beach
My first postdoc (2008-2009) was at the University of California Santa Cruz, School of Earth & Planetary Sciences, in conjunction with the U.S. Geological Survey, studying inner shelf sediment transport processes.
My second postdoc (2009 - 2012) was at the University of Plymouth, UK, School of Marine Science & Engineering, studying surf zone hydrodynamics and sediment transport processes.
I worked as a Research Geologist (Nov 2012 - Nov 2016) at the U.S. Geological Survey, at the Grand Canyon Monitoring & Research Center in Flagstaff, Arizona, studying fluvial sediment transport and geomorphic processes in regulated rivers.
I am Assistant Research Professor within the School of Earth & Sustainability, and Affiliate of the School of Informatics, Computing, and Cybersystems, at Northern Arizona University.
acoustics: seafloor/riverbed classification
bio-acoustics: mussels, vegetation
application of machine learning / deep learning in oceanography, geomorphology, hydrology
computational geomorphology and sedimentology
stochastic modeling techniques
remote characterization of sedimentary environments
developing and applying novel acoustics and optics instrumentation and computational algorithms
supporting, developing, and maintaining various open source scientific packages in the Python world.