Work experience

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1. United States Geological Survey

   Mar 2022 – Apr 2025

   Physical Scientist

   Developed models and workflows for predicting water quality in rivers and lakes across the U.S. and New York State.

   • Developed and cross-validated models to predict water quality at the national and state level.
   • Led or contributed to 6 publications and created 3 public datasets that involved harmonizing multi-source data.
2. United States Geological Survey (Contractor)

   Sep 2019 – Feb 2022

   Postdoctoral Associates

   Designed machine learning and process-based models of river water quality and served as a team member on a nationally scoped effort to improve prediction of harmful algal blooms.

   • Demonstrated tradeoffs between in situ and remotely sensed input features and the importance of using spatial-cross validation routines for assessing the ability of machine learning models to make predictions at new locations.
   • Created a new physics-based model that was able to attribute how terrestrial and in-stream processes limit stream lighting conditions. The model was applied to over 2 million rivers to better understand energetic inputs into river ecosystems.
   • Led or contributed to 4 journal publications and 2 public datasets.
3. Duke University

   Jun 2016 – Aug 2019

   Postdoctoral Associate

   Member of a multidisciplinary team of academic and federal scientists advancing understanding of stream ecosystem energetics.

   • Applied unsupervised machine learning with a novel application of assessing similarity between time-series to create the first clustering typology of river productivity regimes. The results provide context for comparing rivers and identifying common drivers of river ecosystem function.
   • Developed a new model which incorporated riparian vegetation phenology to predict stream lighting conditions and created two related R packages.
   • Represented our project at conferences and workshops by presenting original research.
   • Led or contributed to 4 peer-reviewed publications.
4. S.U.N.Y. University at Buffalo

   Sep 2012 – May 2016

   Research Assistant

   Developed new submodels to represent forest canopy phenology within the TREES plant ecohydrology model.

Education

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1. S.U.N.Y. University at Buffalo

   2016

   Doctor of philosophy (Ph.D.), Geography

   “Modeling the seasonal course of canopy dynamics: Incorporating physiology into phenological models”

   Download my dissertation
2. S.U.N.Y. College of Environmental Science and Forestry

   2006

   Bachelor of Science (B.S.), Environmental and Forest Biology