Megan L. Matthews

 Megan L. Matthews
Megan L. Matthews
  • Assistant Professor
3024 Civil and Environmental Engineering Building

Primary Research Area

  • Water Resources Engineering and Science

Research Areas

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Biography

Megan Matthews is an assistant professor in the Department of Civil and Environmental Engineering at the University of Illinois Urbana-Champaign. She earned her bachelor's, master's, and doctorate in electrical engineering from North Carolina State University. Megan’s work involves developing multiscale computational models to explore the impacts of a changing environment on plants and to identify engineering strategies for improving plant development and growth. She uses mechanistic and data-driven approaches to develop models describing plant processes at regulatory, metabolic, and physiological scales. Her body of work includes using crop growth and mechanistic metabolic models to explore how the effectiveness and resilience of photosynthetic improvement strategies on crop production is influenced when accounting for field-level crop growth dynamics. Her group also models crop-microbe symbiotic relationships and metabolism to identify and assess strategies to sustainably increase nutrient use efficiency for crops.

Education

  • Ph.D. Electrical Engineering, North Carolina State University, 2019, Advisor: Cranos Williams
  • M.S. Electrical Engineering, North Carolina State University, 2012, Advisor: Cranos Williams
  • B.S. Electrical Engineering, North Carolina State University, 2011

Academic Positions

  • Postdoctoral Research Associate, Institute for Sustainability, Energy, and Environment, University of Illinois Urbana-Champaign, 7/2019-12/2020
  • Assistant Professor, Dept of Civil and Environmental Engineering, University of Illinois Urbana-Champaign, 1/2021 - Present

Research Interests

  • Multiscale plant and crop modeling (gene regulation, protein regulation, metabolism, physiology, ecosystem, etc.)
  • Photosynthesis modeling and engineering
  • Crop and environmental sustainability
  • Control systems theory in biological modeling
  • Data-driven modeling

Primary Research Area

  • Water Resources Engineering and Science

Research Areas