Matt Aitken is a Fellow at Croatan Institute. A renewable energy physicist by training, Dr. Aitken leads data science initiatives at the Institute, including the development of RAISER: Research, Analytics, and Insights for Social and Environmental Returns. Prior to joining the Institute, he was the President and Executive Director of Greener Change, a nonprofit organization working to provide public access to open data on corporate sustainability. Previously, he served as an ORISE Research Fellow at the U.S. Environmental Protection Agency, where he used the MARKet ALlocation (MARKAL) model to carry out economic analysis of the U.S. energy system.
Aitken received a Ph.D. in physics from the University of Colorado, where his research on applications of lidar and computational fluid dynamics to wind energy garnered multiple awards from the American Meteorological Society and the Renewable and Sustainable Energy Institute. While in Boulder he also served as a Research Assistant at the National Renewable Energy Laboratory (NREL). He holds a B.S. in physics from the University of North Carolina at Chapel Hill and a M.S. in aerospace engineering from North Carolina State University, where he was a Dean’s Fellow. While at NCSU, he also served as a Research Assistant at the NASA Langley Research Center.
In addition to an unusual obsession with The New York Times, Aitken enjoys spending time with his wife, Dana; doing yoga; and running with his canine confidant, Amani. He also regularly volunteers with Code the Dream, teaching young people from minority and immigrant backgrounds how to program and develop software.
He lives in Durham, North Carolina.
Ph.D., Physics, University of Colorado
M.S., Aerospace Engineering, North Carolina State University
B.S., Physics, University of North Carolina
"Report on US Sustainable and Impact Investing Trends 2020." Washington, DC: US SIF Foundation, November 2020 (with Joshua Humphreys et al).
"Report on US Sustainable, Responsible, and Impact Investing Trends 2018." Washington, DC: US SIF Foundation, October 2018 (with Joshua Humphreys et al).
Aitken, M. L., D. H. Loughlin, R. S. Dodder, W. H. Yelverton, 2015: Economic and environmental evaluation of coal-and-biomass-to-liquids-
Aitken, M. L., 2014: Wind turbine wake characterization with remote sensing and computational fluid dynamics. Ph.D. dissertation, Dept. of Physics, University of Colorado, 231 pp.
Aitken, M. L., B. Kosović, J. D. Mirocha, and J. K. Lundquist, 2014: Large eddy simulation of wind turbine wake dynamics in the stable boundary layer using the Weather Research and Forecasting Model. Journal of Renewable and Sustainable Energy, vol. 6, p. 033137-1–033137-13.
Aitken, M. L., and J. K. Lundquist, 2014: Utility-scale wind turbine wake characterization using nacelle-based long-range scanning lidar. Journal of Atmospheric and Oceanic Technology, vol. 31, p. 1529–1539.
Aitken, M. L., R. M. Banta, Y. L. Pichugina, and J. K. Lundquist, 2014: Quantifying wind turbine wake characteristics from scanning remote sensor data. Journal of Atmospheric and Oceanic Technology, doi:10.1175/JTECH-D-13-00104.
Mirocha, J. D., B. Kosović, M. L. Aitken, and J. K. Lundquist, 2014: Implementation of a generalized actuator disk wind turbine model into WRF for large-eddy simulation applications. Journal of Renewable and Sustainable Energy, vol. 6, p. 013104-1–013104-19.
Aitken, M. L., M. E. Rhodes, and J. K. Lundquist, 2012: Performance of a wind-profiling lidar in the region of wind turbine rotor disks. Journal of Atmospheric and Oceanic Technology, vol. 29, p. 347–355.
Friedrich, K., J. K. Lundquist, M. Aitken, E. Kalina, and R. F. Marshall, 2012: Stability and turbulence in the atmospheric boundary layer: a comparison of remote sensing and tower observations. Geophysical Research Letters, vol. 39, L03801, doi:10.1029/2011GL050413.
Busnardo, D. M., M. L. Aitken, R. H. Tolson, D. Pierrottet, and F. Amzajerdian, 2011: Lidar-aided inertial navigation with extended Kalman filtering for pinpoint landing. Proc. 49th AIAA Aerospace Sciences Meeting, Orlando, FL, American Institute of Aeronautics and Astronautics, AIAA-2011-428.
Aitken, M. L., 2009: Lidar-aided inertial navigation with extended Kalman filtering for pinpoint landing. M.S. thesis, Dept. of Mechanical and Aerospace Engineering, North Carolina State University, 74 pp.