معرفی
Simon Bøgh is an Associate Professor at the Department of Electronic Systems within The Technical Faculty of IT and Design at Aalborg University. His research focuses on Deep Reinforcement Learning applied to space robotics, industrial robotics, and industrial processes, emphasizing autonomous decision-making through trial-and-error learning and integration of human expert demonstrations. Key areas include robotics control systems, predictive analytics, and AI-driven automation.
He leads or participates in high-impact projects such as RIACT: Radical Innovation of Adaptive Cobot Technology and CAPeX: Pionercenter for Accelerating P2X Materials Discovery. His work contributes to UN Sustainable Development Goals related to Industry and Production, leveraging Industry 4.0 technologies like IoT and predictive analytics.
- Education: Not explicitly stated in provided texts.
- Research Highlights: Development of reinforcement learning frameworks for planetary rovers (e.g., RLRoverLab), corrosion detection systems, and collaborative robot control.
Dr. Bøgh has received prestigious awards, including the Novo Nordisk Foundation's Prize for Excellence in Technical Science Teaching (2025) and the IEEE iSpaRo 2024 Best Paper Runner-up Award. He actively engages in academic and industrial collaborations, delivering talks on AI in robotics and space exploration.
His research group collaborates with industry partners and academic institutions globally, addressing challenges in autonomous systems, robotic manipulation, and smart manufacturing. Current lab activities include advancing reinforcement learning algorithms for space exploration and industrial process optimization.
