Jason O. Burkholder
Principal Research Scientist

Mr. Burkholder received an M.S. degree in Electrical Engineering with a concentration in Control Systems from the University of Virginia in 1997 and a B.S. degree in Systems Engineering from the United States Naval Academy in 1995. His graduate thesis involved adaptive compensation for unknown actuator nonlinearities in control systems.

From 1998 to 2003, Mr. Burkholder worked for Sperry Marine, a unit of Northrop Grumman Systems Corporation. At Sperry Marine, he was a control systems and software engineer in the Navigation and Controls department, where he designed, coded, and tested at sea new control algorithms and adaptive tuning algorithms that are now included in Sperry Marine's commercial autopilots. He also wrote and validated ship simulations for numerous commercial and military vessels, including DDG51 and LPD17 class ships. These models are used for the purposes of autopilot and track control algorithm development and testing as well as for LPD17 Steering and Integrated Bridge System Operator Training. Mr. Burkholder served as Project Lead for the CG47 Class Steering and Integrated Bridge System upgrade and the LHD7 modernized steering system development. In addition, he served as control systems engineer for Sperry Marine's active fin stabilizer product and wrote ship and control system simulations to predict and evaluate fin stabilizer performance and recommend appropriate fin sizes for new ship designs. His work on steering and track control systems provided opportunities to ride numerous commercial and military vessels around the world for the purposes of evaluating and improving Sperry Marine's heading and track control systems and roll stabilization systems. In December 2001, Mr. Burkholder received the Litton Marine Systems Engineering Excellence Award, an annual award recognizing the Company's outstanding young engineer.

Mr. Burkholder began working for BAI in 2002 and joined the firm full-time in January 2003. He has led several projects at BAI including the development of a comprehensive methodology for applying statistical change detection techniques to the analysis of residual signals generated in analytic redundancy schemes for fault detection and isolation in dynamical systems; the development and simulation of fault detection and isolation schemes for marine diesel engines; the development and simulation of advanced high-speed algorithms for detection and isolation of faults in zonal, grounded shipboard electrical power systems being considered for future U.S. Navy all-electric ship designs; the development and simulation of optimization algorithms for reconfigurable shipboard electrical power systems; and the design and simulation of a physical arrangement and an associated control system for permanent magnet motor steering gear for DDG 51 class ships.

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