About
Between computer vision models, software, AI, and rabbit holes.
I spend most of my time moving between computer vision research and practical software: studying how visual models behave, where they fail, and how thoughtful tools can make difficult work easier to move through.
I am a PhD Candidate at the School of Computing and Information Systems, The University of Melbourne. My research looks at object detection with Detection Transformers, especially how Vision Transformer based detectors can become more robust, efficient, and explainable.
Outside the research loop, I like building tools that make tedious or cognitively heavy work feel lighter. That usually leads me into learning systems, automation, AI workflows, and small software experiments. This site collects the pieces that sit between those worlds.