Dr. Omar Althuwaynee
About Me
I am a Research Associate at Durham University specializing in geomatics engineering, GIS, and spatial modeling using AI and machine learning. My research focuses on monitoring and predicting natural and anthropogenic hazards including landslides, rockfalls, dust storms, and air pollution through advanced geospatial analysis and early warning systems.
With a PhD in GIS & Geomatics Engineering and 15+ years of professional experience, I have worked across international research institutions including the National Research Council (CNR, Italy), Sejong University (South Korea), and the University of Johannesburg (South Africa). I am deeply committed to bridging academia and practice through open-source tools, online education, and collaborative global research networks.
Core Expertise
Featured Projects & Applications
Iraq Air Quality Platform & Dust Storm Early Warning System
A comprehensive real-time platform providing critical dust storm forecasting and air quality monitoring data for Iraq and the broader Middle East. This system integrates satellite data, meteorological information, and machine learning algorithms to predict dust storm severity and air pollution patterns. The platform has become a blueprint for regional hazard mitigation and environmental health monitoring.
LaGriSU: Landslide Grid & Slope Units QGIS Tool Pack
Advanced QGIS plugin suite for automated landslide susceptibility mapping and rainfall threshold analysis. Enables researchers to generate prediction maps using statistical and machine learning algorithms integrated with geospatial data.
Udemy Online Courses: Geospatial Analysis & Machine Learning
Developed 6 comprehensive courses with 3,870+ enrollments from 2,651 students across 127 countries. Step-by-step tutorials covering landslide prediction, GIS-based ML algorithms, ANN applications, and rainfall threshold analysis. Average instructor rating: 4.4/5.
YouTube Channel: 80+ Geospatial & ML Courses
Free educational content covering GIS tools, machine learning algorithms, programming tutorials, expert interviews, and research guidance for MSc/PhD students. Reaching thousands of learners globally across 30+ language backgrounds.
Scientists Adoption Academy (SCADAC)
Founded a global research collaboration platform with 3,000+ members, fostering international research partnerships and overcoming geographic and funding barriers. Acknowledged in 8+ peer-reviewed publications, including work in Environmental Modelling & Software and Remote Sensing journals.