About
Between computer vision research, practical systems, and the occasional rabbit hole.
I study how visual models behave in the real world, build and test practical perception systems, and create thoughtful software for work that is complex, repetitive, or cognitively heavy.
I am a PhD Candidate at the School of Computing and Information Systems, The University of Melbourne. My research focuses on object detection with Detection Transformers, especially how Vision Transformer-based detectors can become more robust, efficient, and explainable.
Alongside my research, I build and test practical computer-vision systems for object detection and robotic perception. I also build tools that make tedious or cognitively heavy work feel lighter, leading me into learning systems, automation, AI workflows, and small software experiments. This site collects the pieces that sit between those worlds.