Jake Searcy
Department of Data Science, University of Oregon
Education
Ph.D. | University of Oregon
Jake’s Group Publications
A semi-automated pipeline for morphological analysis of myonuclei along single muscle fibers
Grading Runners: A Pilot Study to Reverse Engineer Patterns to Understand the Sizing of a Population
A Footprint-Aware, High-Resolution Approach for Carbon Flux Prediction Across Diverse Ecosystems
Uncertainty-Aware Carbon Flux Estimation from Multispectral Landsat Imagery Using Mixture Density Networks
Attendance of Underserved Populations at Field-Based Health Services Events: Application of Quasi-Experimental Methods that Accommodate the COVID-19 Pandemic
Cascadia Daily GNSS Time Series Denoising: Graph Neural Network and Stack Filtering
Detection of hidden low-frequency earthquakes in southern vancouver island with deep learning
Real-time fault tracking and ground motion prediction for large earthquakes with HR-GNSS and deep learning
Deep learning for denoising high-rate global navigation satellite system data
How useful are tax disclosures in predicting effective tax rates? A machine learning approach
Frontline data science: Lessons learned from a pandemic
Reaching Latinx communities with algorithmic optimization for SARS-CoV-2 testing locations
Workflow Analysis To Understand Ease of Preparation and Importation of 3D Exemplar Head Scan Data to 3D Modeling Software Programs for N95 Mask Sizing and Fit
Effectiveness of a COVID-19 testing outreach intervention for Latinx communities: a cluster randomized trial
Learning source, path and site effects: CNN-based on-site intensity prediction for earthquake early warning
Identification of low-frequency earthquakes on the San Andreas Fault with deep learning
Towards automatic sizing for PPE with a point cloud based variational autoencoder
Early warning for great earthquakes from characterization of crustal deformation patterns with deep learning
Interested in my High Energy Physics Work: See My Google Scholar Page
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