Summary
Alex Tyshka is an ML Engineer and robotics generalist with a decade of experience building data-efficient learning systems and human-robot interaction (HRI) research. Currently at General Motors, he develops metrics frameworks to track autonomous vehicle performance and mine meaningful events, drawing on prior internships at Amazon Robotics, Magna, and Dataspeed where he worked on obstacle testing, low-latency perception, and embedded localization. As a graduate student and Research Assistant at Oakland University’s Intelligent Robotics Lab, he focuses on transparent, multi-modal teaching strategies and learning-from-demonstration to make social agents more interpretable and sample-efficient. Alex combines hands-on engineering—CUDA/TensorRT optimization, Kalman filters, and full-stack demos—with rigorous PhD-level research, bridging prototyping and production. Based in Rochester, MI, he brings a practical track record of shipping robotic systems alongside a research agenda aimed at making interactive agents both safer and easier to teach.
10 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy - PhD Electrical and Computer Engineering, Doctor of Philosophy - PhD Electrical and Computer Engineering at Oakland University