Glen Merritt is a PhD-level engineer and researcher specializing in advanced control systems, robotics, and automation engineering. His work focuses on applying machine learning, neural networks, and model-based control techniques to complex physical systems, particularly in industrial automation and additive manufacturing processes.
He has contributed to peer-reviewed research in areas such as nonlinear system control, hybrid robotic systems, and real-time adaptive control methods, including applications in additive friction stir deposition and rehabilitation robotics. His background combines strong theoretical expertise in dynamical systems with practical engineering implementation in high-performance industrial environments.
