I am a Research Assistant Professor at the Department of Geology and Environmental Science of the University of Pittsburgh (was a Postdoc from Feb 2023 to Jul 2024). At Prof. John Gardner’s lab we work with remote sensing of hydrological and hydrosedimentological fluvial processes and freshwater science. My main project is a National Aeronautics and Space Administration (NASA) project that has the goal to produce sediment flux estimations for every major river on Earth using Machine Learning techniques.

As a researcher, I apply Remote Sensing, Spatial Data Science, and Machine Learning, to study river geomorphology, freshwater monitoring, extreme events, and the effects of climate change in hydrological processes.

I am a bachelor in civil engineering (2015), a Master of Science (2018), and a PhD (2022) in Water Resources and Environmental Sanitation from Universidade Federal do Rio Grande do Sul (UFRGS). I also did a PhD Sandwich (mobility period) on the GIScience group of the Geography Department of Friedrich-Schiller-Universität Jena, in Jena, Germany. For my PhD, I worked in the Hydroenvironmental Applications of Artificial Neural Networks (AHRNA) research group. I modeled landslide susceptibility using Machine Learning methods, especially Artificial Neural Networks. During my time in Jena, I had the chance to dive into spatial cross-validation and geomorphic plausibility of AI models.

I find Machine Learning methods fascinating and still underrepresented in environmental science and engineering research. Most of my research is based on Remote Sensing products and GIS techniques. I am a coding enthusiast and have coded scientifically for over a decade, having used many different languages over these years. I also like to use and support the use of open-source software. Every example you see in my Remote Sensing and GIS blog is based on open-source technologies.