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Lucas Koepke (Fed)

Lucas Koepke graduated from the University of Colorado in 2006 with two Bachelor of Arts degrees, in Mathematics and Germanic Studies, and with a Master of Science degree in Statistics from the University of Washington in 2011. From 2011 to 2018 he worked as a Data Analyst/Statistician for the Technology & Social Change Group at the University of Washington.

Lucas has been with the Statistical Engineering Division at NIST since October 2018, first as a PREP associate and as a federal employee starting in 2020. 

Technical Areas of Research and Consulting

  • Linear and nonlinear models
  • Data visualization
  • Big data
  • Statistical computing (bootstrap, Monte Carlo, R, Python, Scala)
  • Machine learning (artificial neural networks, generative adversarial networks, deep learning)


Characterizing LTE User Equipment Emissions Under Closed-Loop Power Control

Jason Coder, Aric Sanders, Michael R. Frey, Adam Wunderlich, Azizollah Kord, Jolene Splett, Lucas N. Koepke, Daniel Kuester, Duncan McGillivray, John M. Ladbury
This report presents a laboratory-based characterization of Long Term Evolution (LTE) User Equipment (UE) emissions under closed-loop power control, building on

Characterizing LTE User Equipment Emissions: Factor Screening

Jason Coder, Adam Wunderlich, Michael R. Frey, Paul T. Blanchard, Dan Kuester, Azizollah Kord, Max Lees, Aric Sanders, Jolene Splett, Lucas N. Koepke, Rob Horansky, Duncan McGillivray, John M. Ladbury, Jeffrey T. Correia, Venkatesh Ramaswamy, Jerediah Fevold, Shawn Lefebre, Jacob K. Johnson, John Carpenter, Mark Lofquist, Keith Hartley, Melissa Midzor
Characterizations of long-term evolution (LTE) user equipment (UE) emissions are a key ingredient in models of interference between wireless cellular networks
Created September 11, 2019, Updated December 8, 2022