Summary
Chris Hodapp is a machine learning engineer with 13 years of multidisciplinary experience building embedded systems, computer vision, and ML solutions across startups and research teams. Based in Cincinnati, he currently applies ML to inspection and blueprint image-processing problems at Etegent Technologies, drawing on a background that spans firmware and PCB design to high-performance C++ vision systems. His work blends practical production engineering—delivering sensors, low-power IoT firmware, and cloud-integrated analytics—with research in camera calibration, SLAM, and dense 3D reconstruction from his earlier projects. Chris pairs formal training (MS in Computer Science from Georgia Tech) with hands-on hardware expertise from roles designing BLE firmware, time-of-flight sensing, and CUDA prototypes for real-time processing. He’s comfortable moving between low-level embedded constraints and higher-level ML model development, and has a track record of turning experimental sensing technologies into deployable inspection tools. An often-overlooked strength is his experience writing Haskell libraries to provide stronger timing guarantees in mixed C environments, reflecting a taste for robust, provable engineering.
13 years of coding experience
12 years of employment as a software developer
Bachelor’s Degree, Electrical Engineering, Bachelor’s Degree, Electrical Engineering at University of Cincinnati
Master’s Degree, Computer Science, Master’s Degree, Computer Science at Georgia Institute of Technology
English, German