Ryan works on data where the number of parameters exceed the number of data points by an order of magnitude to try and find a lower dimensional structure for predictive analysis. Some examples include DNA/RNA, seismic sensing data, FRMI imagery data.
Gravimetric anomaly detection with compressed sensing. Intelligence, surveillance, and reconaisance asset assignment.
University of Washington - PhD Statistics
Air Force Institute of Technology - MS Operations Research
United States Air Force Academy - BS Operations Research
Recent courses taught
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