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.

   • Led or contributed to 6 peer-reviewed publications by working with academic, state, and federal collaborators to develop new models of river and lake water quality.
   • Designed models to predict algal concentrations and harmful algal blooms (HABs) across 110 New York State lakes and examined effectiveness of NYSDEC water quality monitoring data for making accurate predictions. Identified a simple, low-cost measure that was as effective as costlier laboratory measures for predicting HABs.
   • • Created public datasets with over 100,000 records with data on water quality, climate, and land use.
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.

   • Published 3 first authored and 2 coauthored peer-reviewed publications related to stream ecosystem dynamics.
   • Identified turbidity and total nitrogen as important predictors of chlorophyll concentrations in rivers nationally by developing and testing a machine learning model across 82 U.S. rivers.
   • Developed a new model to predict light available to river primary producers and used this model to estimate that water column processes limit river productivity for 50% of the nation’s river length and 80% of its surface area.
   • Created 2 public datasets with over 80 million records and associated metadata to support open science.
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.

   • Led or contributed to 3 peer-reviewed publications as part of a multidisciplinary team of academic and federal scientists.
   • Created the first clustering of common patterns of river autotrophy and linked the clusters to environmental drivers. The results provide context for drawing comparisons of observed patterns of primary productivity across many rivers.
   • • Communicated research findings by presenting at working groups or professional conferences, and authoring 2 open source R software packages.
4. S.U.N.Y. University at Buffalo

   Sep 2012 – May 2016

   Research Assistant

   Improved the realism of an existing plant physiology model by including better representation of how meteorological variables influence plant development and published a peer-reviewed article.

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