Tom Bruls

Tom joined ORI in 2016 as a DPhil student and member of Keble College. His research at ORI focuses on deep learning techniques for semantic scene understanding for autonomous vehicles in urban environments.

He completed his BSc and MSc in Electrical Engineering at Eindhoven University of Technology in The Netherlands. His MSc focused on information engineering, more specifically on (robust and optimal) control.

During his BSc he was appointed Electronics & Finance manager of University Racing Eindhoven, a student team competing in the Formula Student Electric Competition. As part of his MSc curriculum he conducted an internship at AUDI AG (Ingolstadt, Germany) in the area of autonomous driving. The research focused on generating reference paths from a multi-hypothesis road representation, which are then used by the trajectory planner for automated driving in highway and urban environments.

Google Scholar

LinkedIn

• P. Amayo, T. Bruls, and P. Newman, “Semantic Classification of Road Markings from Geometric Primitives,” in IEEE International Conference on Intelligent Transportation Systems (ITSC), Maui, Hawaii, USA, 2018.
  [Bibtex]

• L. Kunze, T. Bruls, T. Suleymanov, and P. Newman, “Reading between the Lanes: Road Layout Reconstruction from Partially Segmented Scenes,” in IEEE International Conference on Intelligent Transportation Systems (ITSC), Maui, Hawaii, USA, 2018.
  [Bibtex]

• T. Bruls, W. Maddern, A. A. Morye, and P. Newman, “Mark Yourself: Road Marking Segmentation via Weakly-Supervised Annotations from Multimodal Data,” in 2018 IEEE International Conference on Robotics and Automation (ICRA), Brisbane, Australia, 2018.
  [Bibtex]