Kyle Bradbury

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Lecturing Fellow in the Duke University Energy Initiative

Kyle Bradbury is the Managing Director of the Energy Data Analytics Lab at the Duke University Energy Initiative. He brings experience in machine learning and statistical modeling to energy problems. He completed his Ph.D. at Duke University, with research focused on modeling the reliability and cost trade-offs of energy storage systems for integrating wind and solar power into the grid. Kyle holds a M.S. in Electrical Engineering from Duke University where he specialized in statistical signal processing and machine learning, and a B.S. in Electrical Engineering from Tufts University. He has worked for ISO New England, MIT Lincoln Laboratories, and Dominion.

Appointments and Affiliations

  • Lecturing Fellow in the Duke University Energy Initiative
  • Lecturing Fellow in the Department of Electrical and Computer Engineering

Contact Information

Education

  • Ph.D. Duke University, 2013

Research Interests

Kyle Bradbury is the Managing Director of the Energy Data Analytics Lab at the Duke University Energy Initiative. He brings experience in machine learning and statistical modeling to energy problems.

Courses Taught

  • COMPSCI 391: Independent Study
  • COMPSCI 393: Research Independent Study
  • ECE 392: Undergraduate Research in Electrical and Computer Engineering
  • ENERGY 395: Connections in Energy: Interdisciplinary Team Projects
  • ENERGY 396-1: Connections in Energy: Interdisciplinary Team Projects
  • ENERGY 396: Connections in Energy: Interdisciplinary Team Projects
  • ENERGY 795: Connections in Energy: Interdisciplinary Team Projects
  • ENERGY 796-1: Connections in Energy: Interdisciplinary Team Projects
  • ENERGY 796: Connections in Energy: Interdisciplinary Team Projects

Representative Publications

  • Bradbury, K; Pratson, L; Patiño-Echeverri, D, Economic viability of energy storage systems based on price arbitrage potential in real-time U.S. electricity markets, Applied Energy, vol 114 (2014), pp. 512-519 [10.1016/j.apenergy.2013.10.010] [abs].
  • Bradbury, K; Torrione, PA; Collins, L, Realtime gaussian markov random field based ground tracking for ground penetrating radar data, Proceedings of SPIE - The International Society for Optical Engineering, vol 7303 (2009) [10.1117/12.818781] [abs].