About Matthias Mueller Matthias Mueller Ph.D., Electrical and Computer Engineering machine learning Deep learning Computer Vision robotics Matthias Mueller was an Electrical and Computer Engineering Ph.D. candidate in Image and Video Understanding Lab (IVUL) Group at Visual Computing Center (VCC) under the supervision of Prof. Bernard Ghanem at King Abdullah University of Science and Technology (KAUST). Education and Early Career Matthias graduated with a B.Sc. in Electrical Engineering and Math Minor from Texas A&M University in 2011. After graduation, he joined P+Z Engineering in Munich, Germany as an Electrical Engineer and worked for 3 years on the development of mild-hybrid electric machines at BMW. In 2014, he started his M Events Presented Events May 12 - May 18, 2019 Sim-to-Real Transfer for Autonomous Navigation Matthias Mueller, Ph.D., Electrical and Computer Engineering May 14, 16:00 - 17:00 B2 L5 R5220 Computer Vision UAV robotics machine learning This work investigates the problem of transfer from simulation to the real world in the context of autonomous navigation. To this end, we first present a photo-realistic training and evaluation simulator Sim4CV which enables several applications across various fields of computer vision. Built on top of the Unreal Engine, the simulator features cars and unmanned aerial vehicles (UAVs) with a realistic physics simulation and diverse urban and suburban 3D environments. We demonstrate the versatility of the simulator with two case studies: autonomous UAV-based tracking of moving objects and autonomous driving using supervised learning.
Sim-to-Real Transfer for Autonomous Navigation Matthias Mueller, Ph.D., Electrical and Computer Engineering May 14, 16:00 - 17:00 B2 L5 R5220 Computer Vision UAV robotics machine learning This work investigates the problem of transfer from simulation to the real world in the context of autonomous navigation. To this end, we first present a photo-realistic training and evaluation simulator Sim4CV which enables several applications across various fields of computer vision. Built on top of the Unreal Engine, the simulator features cars and unmanned aerial vehicles (UAVs) with a realistic physics simulation and diverse urban and suburban 3D environments. We demonstrate the versatility of the simulator with two case studies: autonomous UAV-based tracking of moving objects and autonomous driving using supervised learning.
Related Sites Electrical and Computer Engineering (ECE) Image and Video Understanding Lab (IVUL) Related Content Articles 4 Events 1 Related Links Also view list of Publications on KAUST Repository Matthias Mueller's Personal Webpage
