I am a Senior Staff Machine Learning Scientist in the Core AI team at Seeing Machines, specializing in human-centered 3D perception for Physical AI, robotics, and safety-critical systems.

I lead the development of real-time Human Mesh Recovery (HMR) and human-understanding technologies, combining 3D geometry, human body modelling, multimodal learning, and efficient on-device inference. I enjoy setting technical direction, developing novel ML architectures, and translating research into real-time embedded systems, integrated perception platforms, and high-profile product demonstrations — including the Interior Perception Map showcased at CES 2026. Our latest work, Seeing Machines HMR, recovers state-of-the-art 3D human meshes at up to 180 FPS on NVIDIA Jetson Thor, giving robots a real-time understanding of the people around them.

Previously, I was a Research Fellow at the Australian Institute for Machine Learning, The University of Adelaide, working on 6D object pose estimation, differentiable geometric optimization, adversarial machine learning, and efficient edge AI. Our team won two back-to-back first-place outcomes in the European Space Agency’s global satellite pose estimation competitions.

I also serve as a peer reviewer for IEEE TPAMI, CVPR, ICCV, AAAI, ACM Multimedia, IJCAI, ICRA, ICDM, WACV, and IEEE Access.