Summary
Evan King is a graduate teaching assistant and incoming product engineer with a B.S. in Computer Engineering and an M.S. in Electrical Engineering candidate at the University of Kentucky, bringing eight years of practical and research experience in control, embedded systems, and stochastic signal processing. His work blends Kalman, extended Kalman, and particle filters for probabilistic tracking with machine learning techniques to extract actionable indicators from complex datasets, applied to smart manufacturing and animal welfare research. Internships at Cummins sharpened his embedded controls and testing skills—he built a GTM-based signal generator and helped tune engine fuel control algorithms—while his master's thesis uniquely leverages accelerometer and EEG data from dairy cows to improve on-farm welfare monitoring. Comfortable moving between hands-on embedded development and probabilistic ML research, he’s joining Dynetics’ Product Engineering team to tackle challenging systems problems.
8 years of coding experience
Master's degree, Electrical and Electronics Engineering, Master's degree, Electrical and Electronics Engineering at University of Kentucky