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United States Department of Agriculture

Agricultural Research Service

Evan Coopersmith

Research Physical Scientist




photo of Evan Coopersmith Evan Coopersmith
Research Physical Scientist
USDA-ARS Hydrology and Remote Sensing Laboratory
104 Bldg. 007, BARC-West
Beltsville, MD 20705-2350 USA
Voice: (301) 504-5517
Fax: (301) 504-8931
evan.coopersmith@ars.usda.gov


Research Interests:

  • Soil moisture modeling from remotely sensed or in situ data.
  • Hydro-climatic classification.
  • Machine learning algorithms for environmental prediction.

Education:

  • 2006 B.S.E. (Operations Research and Financial Engineering, certificates in Finance, Engineering & Management Systems) Department of Operations Research and Financial Engineering, Princeton University, Princeton, NJ. (Graduated with honors)
  • 2008 M.S. (Environmental Engineering, specializing in Environmental Systems) Department of Civil and Environmental Engineering, University of Illinois, Urbana-Champaign, Urbana, IL.
  • 2013 Ph.D. (Environmental Engineering, specializing in Environmental Systems, certificates in Graduate Teaching, Teaching with Technology) Department of Civil and Environmental Engineering, University of Illinois, Urbana-Champaign, Urbana, IL.


Professional Experience:

  • 2006 - 2008 and 2009 - 2013. Department of Civil and Environmental Engineering, University of Illinois, Urbana-Champaign, Urbana, IL; Graduate Research Assistant.
  • 2008 - 2009. BCW Group LLC, New York, NY; Quantitative Hedge Fund at the New York Mercantile Exchange, Principal and Co-Founder.
  • 2012 - 2013. John Deere Center for Technological Innovation, Champaign, IL; Researcher.
  • 2013 - Present. USDA-ARS-Hydrology and Remote Sensing Laboratory, Beltsville, MD; Physical Science Post-Doctoral Researcher.


Awards:

  • 2006: University Fellowship, Dept. of Civil & Environmental Engineering, University of Illinois.
  • 2007: University Fellowship, Dept. of Civil & Environmental Engineering, University of Illinois
  • 2012: CEE Alumni Graduate Fellowship for Teaching Excellence, University of Illinois.
  • 2013: Englebrecht Fellowship, Most Outstanding Graduate Student in Environmental Engineering, University of Illinois.


Professional Service:

  • American Geophysical Union Member
  • EWRI Environmental and Water Resources Systems Committee Member

Selected Publications:(please contact the author to determine reprint availability)

( view author's publications/interpretive summaries/technical abstracts since 1999)

Patterns of Regional Climate Change: An Analysis of Shifting Hydrologic Regime Publications Curves. Coopersmith, Minsker, and Sivapalan. (In revision in Water Resources Res.)

Exploring the Physical Controls of Regional Patterns of Flow Duration Curves: Part 3 – A Catchment Classification System Based on Seasonality and Runoff Regime. Coopersmith, Yaeger, Ye, Cheng, and Sivapalan. Hydrology & Earth System Sciences, 16, 4467-4482, 2012, doi:10.5194/hess-16-4467-2012.

Exploring the Physical Controls of Regional Patterns of Flow Duration Curves: Part 4 - A Synthesis of Empirical Analysis, Process Modeling, and Catchment Classification. Yaeger, Coopersmith, Ye, Cheng, and Sivapalan. Hydrology & Earth System Sciences, 16, 4483-4498, 2012, doi:10.5194/hess-16-4483-2012.

Exploring the Physical Controls of Regional Patterns of Flow Duration Curves: Part 2 – Role of Seasonality and Associated Process Controls. Ye, Yaeger, Coopersmith, Cheng, and Sivapalan. Hydrology & Earth System Sciences, 16, 4447-4465, 2012, doi:10.5194/hess-16-4447-2012.

Exploring the Physical Controls of Regional Patterns of Flow Duration Curves: Part 1– Insights from Statistical Analyses. Cheng, Yaeger, Viglione, Coopersmith, Ye, and Sivapalan. Hydrology & Earth System Sciences, 16, 4435-4446, 2012, doi:10.5194/hess-16-4435-2012.

Machine Learning Assessments of Soil Drying – Coopersmith, Minsker, Wenzel, and Gilmore. (In revision in Computers and Electronics in Agriculture)

Understanding and Forecasting Hypoxia Using Machine Learning Algorithms – Coopersmith, Minsker, and Montagna, Journal of Hydroinformatics. Vol. 13, No.1 pp. 64-80, 2010.



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Last Modified: 11/29/2013
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