Connor graduated from QUT in 2019 with a Bachelor of Engineering (Mechatronics) with first class honours. His capstone project focused on the development of a deployable ground plane segmentation system for the ‘Carlie’ mini autonomous vehicle platform. This work transitioned into the commencement of his PhD research under the supervision of Prof. Michael Milford, Assoc. Prof. Thierry Peynot and Dr Sourav Garg in 2020.
Connor is particularly interested in research contributing to the scene understanding capabilities of autonomous vehicles and how to improve their performance in challenging conditions. He also has a growing interest in the application of probabilistic methods to robotics and neural networks.
Thesis: Spatially Informed Scene Understanding for Robots and Autonomous Vehicles
Current Work: Investigating how Visual Place Recognition can be used to improve semantic segmentation in challenging domains (e.g. night, fog, snow, rain) without additional training.