Karsten Mueller
About Karsten Mueller
Karsten Mueller is a Guidance, Navigation, and Autonomy Engineer with extensive academic and professional experience in electrical engineering and autonomous systems. He has worked at Joby Aviation since 2021 and has been a research assistant at Karlsruhe Institute of Technology since 2015.
Work at Joby Aviation
Karsten Mueller has been employed at Joby Aviation as a Guidance, Navigation and Autonomy Engineer since 2021. In this role, he focuses on developing advanced systems for aerial mobility, contributing to the company's mission of creating sustainable air transportation solutions. His expertise in guidance and navigation plays a crucial role in the design and implementation of autonomous flight technologies.
Education and Expertise
Karsten Mueller holds multiple degrees in Electrical Engineering and Information Technology. He achieved his Bachelor's Degree from Karlsruhe Institute of Technology (KIT) from 2008 to 2011, followed by a Master's Degree from 2011 to 2015. He further pursued his education at KIT, obtaining a Doctor's Degree (Dr.-Ing.) in Navigation and Autonomous Aerial Vehicles from 2015 to 2021. Additionally, he studied Electrical and Computer Engineering at North Carolina State University for one year.
Background
Karsten Mueller began his professional career with an internship at Mercedes-Benz Research & Development North America, Inc. in 2014, where he worked on autonomous driving technologies for five months in Sunnyvale, California. Following this experience, he joined the Karlsruher Institut für Technologie (KIT) as a Research Assistant in 2015, where he has been involved in various research projects for nine years.
Research Contributions
As a Research Assistant at Karlsruher Institut für Technologie (KIT), Karsten Mueller has contributed to various projects related to guidance and navigation systems, particularly in the context of autonomous aerial vehicles. His research focuses on advancing the understanding and implementation of navigation technologies, which are essential for the development of autonomous systems.