I am passionate about my overarching research goal: providing robots with perceptual abilities that allow safe, intelligent interactions with humans in real-world environments. To develop these perceptual abilities, I believe it is useful to study the principles of the human, animal and insect visual systems. I use these principles to develop new computer vision and machine learning algorithms and validate their effectiveness in intelligent robotic systems. I am enthusiastic about this forward/reverse engineering approach, which combines concepts from computer science and engineering with those from biology and social sciences, as it offers the dual benefit of uncovering principles inherent in the animal visual system, as well as applying these principles to its artificial counterpart. I am a recipient of two best thesis awards and two best poster awards and have acquired grants in excess of 400,000 AUD.
Here we go: @rosorg#ROS2 on a new shiny @Apple M1 Silicon (osx-arm64) thanks to @RoboStack and @condaforge. Still not quite ready for the public (some issues in the installation process), but we are nearly there! Stay tuned and follow @RoboStack to get updates.
Excited to share our new work on "Predicting Secondary Task Performance for Cognitive Overload Detection" - Early access: ieeexplore.ieee.org/document/95429… Led by @PVAmadori we explored task performance in a dual-task decision-making driving scenario, aiming for safer shared-control. 1/n
Very excited to be selected as a participant in this year's Fresh Science workshop. We'll learn about #science#communication in two full-day events with media training, meet&greet with businesses and a presentation at a local pub. Looking forward to meet the other participants! twitter.com/EconnectTeam/s…