I started in Civil Engineering with a broad interest in how infrastructure and the environment interact, but over time I found myself increasingly drawn toward environmental and water-related problems. Coursework and laboratory work first gave me a foundation in water and wastewater analysis, and my undergraduate thesis pushed that interest further by allowing me to work with field investigation, laboratory analysis, groundwater modeling, and spatial data in the same project.
What I enjoy most is moving between observation and analysis. I like the hands-on side of environmental research, collecting samples, understanding measurements, and seeing how a real system behaves, but I am equally interested in using models, programming, and data to understand what cannot be observed directly. That balance is what led me from groundwater contaminant transport to river-water-quality research, environmental simulation, Python-based analysis, and more recently, machine learning.
I am still exploring where this combination will take me, but I know that I want my future work to stay close to water quality, contaminants, environmental processes, and water systems, while continuing to strengthen both my experimental and computational skills. I am particularly interested in research where laboratory or field observations raise questions that modeling and data analysis can help answer, and where those results can guide the next experiment, measurement, or engineering decision.
Outside of research, I'm usually watching a football match or at the gym, trying to apply at least some discipline to my own systems, if not the planet's.
