Industrial AI Program

Sarah’s research interests are in space exploration, stemming from her honours research in machine learning using techniques that measure gravitational waves. At AIML, she is supervised by Professor Tat-Jun Chin and the AI for Space Group to analyse lunar craters using satellite position tracking and computer vision technologies.

Oliver’s research examines anthropomorphism— the attribution of human qualities in objects—and how humans perceive consciousness when interacting with AI that possesses human-like features. His project is a joint collaboration between AIML and Adelaide University’s School of Psychology, supervised by Professor Carolyn Semmler, Professor Anton van den Hengel, Dr Jon Opie, and Dr William Ngiam.

Ethan’s research focus is on monocular event-only Visual Odometry (VO)—a process that determines the position and orientation of an object, such as a camera or a robot —and Simultaneous Localisation and Mapping (SLAM), a computational method for developing digital maps, in order to create new applications for space operations. Ethan is supervised by Professor Tat-Jun Chin.

Will’s research focuses on advancing 3D compositional reasoning by developing transformer based models capable of interpreting and generating LEGO structures. At AIML, under the supervision of Professor Anton van den Hengel, Dr Ravi Garg, and Dr Qi Chen, he has explored tokenisation approaches tailored to LDraw text (the open-source CAD format for 3D LEGO assemblies), uncovering strategies which improve a models ability to learn structural patterns in 3D space.

Jialiang's research focuses on the intersection of algorithm design and analysis, combinatorial optimisation, and advanced machine learning techniques. His research will contribute on improving the operational efficiency in the public health sector through algorithmic solutions. His research is jointly supported by AIML and SA Pathology, under the supervision of Dr Mingyu Guo and Dr Weitong Chen.

Zerui's research interests are in Vision-and Language Navigation (VLN) and embodied AI. He is particularly interested in developing algorithms that enable robots to understand and navigate complex environments using multimodal inputs, such as visual and language cues. His research aims to improve the ability of AI systems to perform tasks that require reasoning and interaction within dynamic, real-world settings. He is supervised by Associate Professor Qi Wu.

Irhas' research interests lie in spatial reasoning and examining how to provide an understanding of 3D structure to deep learning models. His current project builds from previous 2D to 3D lifting work by unlocking unsupervised 3D lifting methods for transformers. Irhas is supervised by Professor Simon Lucey.