Research
Generate data-driven insights to better understand complex environmental and societal challenges, informing policy and practice for sustainable development.
Currently pursuing a PhD in Civil Engineering, I specialize in integrating geospatial artificial intelligence (GeoAI) and machine learning with environmental and urban datasets to better understand and manage risks such as flooding, land degradation, and climate-induced hazards. My research often intersects with global development goals, particularly those related to sustainable cities, climate action, and public health.
Over the years, I've cultivated advanced skills in data science, remote sensing, GIS, and statistical modeling using tools such as Python, R, Google Earth Engine, and ArcGIS. Whether it’s analyzing spatiotemporal land use changes, modeling future scenarios, or visualizing complex environmental data, I enjoy transforming raw information into clarity and impact.
Beyond academia, I’m passionate about mentoring, collaboration, and leveraging data for social good. Through research, innovation, and education, I aim to empower communities and decision-makers with the tools and knowledge needed to build a more resilient and equitable future.
Generate data-driven insights to better understand complex environmental and societal challenges, informing policy and practice for sustainable development.
Leveraging GeoAI, data science, and HPC to build practical tools for climate resilience, risk analysis, and environmental monitoring.
Sharing knowledge through mentoring, training, and public engagement, ensuring that research is accessible, timely, and capable of driving meaningful change.