Butros (Peter) Dahu
Peter's research is to integrate population health and geospatial data layers with artificial intelligence (AI)-generated information from remote sensing for advanced predictive and prescriptive analytics of population phenomena such as the COVID-19 outbreak. Use cutting edge and best practice analytical techniques, we will extract information from multi-dimensional heterogeneous complex data collections such as environmental time series; multiscale-images; epidemiological and spaceborne sensor data. Extracted information can include multiscale convolutional features from high-resolution images; time dependent characterizations; and complex multi-model behavior. Such features are critical to the etiology of any phenomena. I thrive on new approaches to complex problems involving complex data.
Open Access Paper:
PhD Candidate, Informatics
Dahu BM, Khan S, Li WS, Shu X, Popescu M, Scott GJ. Time Trend Analysis of COVID-19 Positive Individuals in Boone County, Missouri Based on Demographic Features. AMIA 2022 Annual Symposium, Washington, DC, United States (under review)