About me

I serve as an Assistant Teaching Professor of Data Science and Analytics at the University of Missouri’s Institute for Data Science and Informatics and as an AI Faculty Fellow within the Graduate School. My research integrates geomatics, remote sensing, and large language models to address critical challenges in environmental transformation, including the resulting impacts on public health, natural hazards, and water resource management. By developing computational frameworks that combine machine learning and simulation modeling, I provide the evidence-based insights needed to navigate a changing environment.

I hold dual Ph.D. degrees in Geomatics Engineering and Mathematics and Statistics from the University of Calgary, where my research focused on computational modeling, geospatial analysis, and numerical methods for environmental applications. My doctoral work encompassed forest fire dynamics, drought and flood risk assessment, land surface temperature reconstruction, and hydrological modeling. My research has been supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) and Alberta Innovates, and has resulted in a number of peer-reviewed publications in high-impact journals.

Before joining the University of Missouri, I served as a postdoctoral researcher and research associate in the Department of Geomatics Engineering at the University of Calgary, where I led interdisciplinary research projects applying data science, machine learning, and deep learning to environmental transformation and forest fire studies. I also gained valuable industry experience as a Data Scientist at Earth & Space Inc. and as a Data Science Developer at StellarAlgo Corp., where I developed predictive models, designed data pipelines, and implemented large-scale analytics using Python, SQL, and cloud computing platforms. My extensive teaching background includes positions at the University of Calgary, University of Lethbridge, and Mount Royal University, where I designed and delivered courses in machine learning systems, life cycle assessment, digital engineering, statistics, and mathematical modeling.

At the University of Missouri, I develop and teach a suite of advanced graduate courses that bridge the gap between computational theory and practical application. My curriculum includes Geospatial AI & Image Analysis, Cloud Computing for Data Analytics, Geospatial Data Engineering, and specialized topics in Natural Language Processing, Large Language Models, and Time Series Analyses and Modeling.

Beyond the classroom, I am actively engaged in curriculum innovation, having led a comprehensive review of the Data Science and Analytics program to align our training with rapidly evolving industry standards. As an AI Faculty Fellow, I serve as a strategic liaison for AI-related initiatives, contributing to policy development and facilitating faculty training on the ethical integration of generative AI. My current research and teaching efforts increasingly focus on leveraging these technologies to address critical health outcomes resulting from environmental shifts, sustainability, and natural hazards. I also coordinate monthly research seminars that bring industry leaders to campus, fostering a collaborative ecosystem that enhances program visibility and student professional development.

My research focuses on the intersection of geospatial data science and artificial intelligence to model complex environmental systems. I develop computational frameworks that integrate machine learning and remote sensing to analyze environmental shifts, with a specific focus on addressing the resulting public health outcomes, sustainability, and natural hazard management. I am actively engaged in guiding research at the University of Missouri and collaborating on interdisciplinary initiatives that bridge the gap between geoinformatics and evidence-based decision-making.

Beyond research and teaching, I am deeply committed to academic service and professional leadership within the Mizzou community and the broader scientific field. As an AI Faculty Fellow, I serve as a strategic liaison for AI-related initiatives, contributing to campus-wide policy development and leading faculty training on the ethical integration of generative AI. I actively support the Data Science and Analytics (DSA) program by serving as a committee member and examiner for PhD and Master’s students, and I led a comprehensive curriculum review to ensure our graduate training remains aligned with evolving industry standards. Furthermore, I coordinate monthly research seminars for the Institute for Data Science and Informatics to foster industry-academic collaborations and contribute to the global research community through recent engagements with the IEEE International Geospatial Remote Sensing Symposium (IGARSS). My professional service also includes guest editing special issues and reviewing for high-impact journals such as Results in Engineering, Ecological Informatics, and Environmental Research.

Outside of my professional roles, I enjoy hiking and spending time with family and friends. These activities provide a grounded perspective that continually informs my work as an educator, researcher, and mentor.