About me

I serve as an Assistant Teaching Professor of Data Science and Analytics at the University of Missouri. My work sits at the intersection of environmental science, geospatial engineering, and computational methods — with a growing focus on how environmental exposures such as wildfire smoke, climate variability, and air quality affect population health outcomes. I develop analytical frameworks that integrate Geospatial AI (GeoAI), remote sensing, and Large Language Models (LLMs) to study these environmental systems and their implications for human health and resilience.

Academic & Research Foundation
I hold dual PhDs from the University of Calgary — one in Geomatics Engineering and one in Mathematics and Statistics. My doctoral research, supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) and Alberta Innovates, focused on numerical methods and environmental modeling, including flood risk assessment and land surface temperature reconstruction. Prior to joining the University of Missouri, I served as a Postdoctoral Researcher at the Schulich School of Engineering, where I led interdisciplinary projects applying deep learning and big data analytics to climate change and hydrological modeling.

Leadership & Institutional Service
During the 2025–2026 academic year, I served as an AI Faculty Fellow within the Mizzou Graduate School, contributing to university-wide policy development and leading faculty training on the ethical integration of Generative AI in graduate education. My commitment to professional leadership extends to the international stage — I serve as a Community Contributed Theme Organizer for IGARSS 2026, overseeing the technical review process for themes spanning Risk and Disaster Management, Humanitarian AI, and Agriculture. I also serve as Guest Editor for specialized issues in peer-reviewed journals including Fire, Remote Sensing, and Applied Sciences.

Industry & Technical Expertise
My academic work is informed by professional experience as a Data Scientist and Developer at Earth & Space Inc. and StellarAlgo Corp. This background allows me to bridge theoretical computational models and scalable, production-level data pipelines — and to ensure that research outputs remain grounded in real-world applicability. I am committed to evidence-based approaches that leverage AI to advance environmental understanding and support improved public health outcomes.

Outside of my professional roles, I enjoy hiking and spending time with family and friends — activities that provide perspective and balance that continually inform my work as an educator, researcher, and mentor.