Machine learning and in particular computer vision enable smarter algorithms than ever before. What's next? Mobile robotics with artificial intelligence.

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.Sc. in Electrical Engineering at KAUST and rolled over into the Ph.D. program in 2016. He earned his Ph.D. in 2019 in Computer Vision. 

Research Interest

Matthias research interests lay in the fields of computer vision, robotics and machine learning where he has contributed to more than 10 publications. His primary research interest is in object detection and tracking, especially from Unmanned Aerial Vehicles. Matthias has extensive experience in object tracking and autonomous navigation of embodied agents such as cars and UAVs.

Honors and Awards

Matthias Mueller was a distinguished student through his academic life. He had the Academic Scholarship at Texas A&M. In 2018, he won a scholarship to attend PAISS summer school. Also, he was awarded the Best Paper/Presentation Award in the European Conference on Computer Vision (ECCV’18) – UAVision. Mueller was among the Outstanding Reviewer in the premier annual computer vision event CVPR’18.

Education Profile

  • Ph.D., Electrical Engineering, King Abdullah University of Science and Technology, Saudi Arabia, 2019
  • M.Sc., Electrical Engineering, King Abdullah University of Science and Technology, Saudi Arabia, 2016
  • B.Sc., Electrical Engineering with Math Minor, Texas A&M University, USA, 2011

Awards and Distinctions

  • Best Paper/Presentation Award – ECCVW’18 UAVision, 2018
  • Outstanding Reviewer – CVPR’18, 2018
  • Scholarship to attend PAISS summer school, 2018
  • President Award, 2011
  • Student Employee of the Year, 2008
  • Academic Scholarship + one fully paid semester abroad, 2008-2011
  • Dean’s Honor Roll, 2007-2010

Professional Memberships

  • IEEE
  • Computer Vision Foundation

Selected Publications

Li, G., Mueller, M., Casser, V., Smith, N., Michels, D. L., Ghanem, B. (2018). Teaching UAVs to Race With Observational Imitation Learning, (Preprint).
Mueller, M., Smith, N., & Ghanem, B. (2017). Context-Aware Correlation Filter Tracking. 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). doi:10.1109/cvpr.2017.152
Mueller, M., Smith, N., Ghanem, B. (2017). Persistent Aerial Tracking from UAVs, Winter Enrichment Program 2017 - Poster Competition||KAUST Research Conference 2017: Visual Computing – Modeling and Reconstruction.
Mueller, M., Smith, N., & Ghanem, B. (2016). A Benchmark and Simulator for UAV Tracking. Lecture Notes in Computer Science, 445–461. doi:10.1007/978-3-319-46448-0_27
Bibi, A., Mueller, M., & Ghanem, B. (2016). Target Response Adaptation for Correlation Filter Tracking. Lecture Notes in Computer Science, 419–433. doi:10.1007/978-3-319-46466-4_25
Mueller, M. (2016). Persistent Aerial Tracking, (Thesis).