AI Horizons – Conversations with Australia’s leading and emerging researchers
Join us for AI Horizons, a dynamic event that brings together Australia’s most established artificial intelligence researchers and the next generation of innovators. This unique gathering is designed to spark meaningful conversations, foster collaboration, and showcase the depth and diversity of AI talent across the country.
From cutting-edge developments in machine learning and robotics to ethical frameworks and real-world applications, AI Horizons highlights the breadth of research shaping the future of AI.
This event is a celebration of Australia’s growing influence in the global AI landscape. It provides a platform for emerging voices to share their work alongside renowned experts, creating a vibrant space for knowledge exchange and inspiration. Whether you're a researcher, student, technologist, or simply curious about the future of AI, AI Horizons offers a front-row seat to the ideas and people driving innovation forward.
Come and witness the future of AI—made in Australia.
Speakers
FTSE
Joint Director, QUT Centre for Robotics, ARC Laureate Fellow and Professor
Joint Director, QUT Centre for Robotics, ARC Laureate Fellow and Professor
Professor Michael Milford is a leading researcher in neuroscience-based robotics navigation. He works closely with industry and government developing high-performance positioning systems for robotics and autonomous vehicles.
Michael is at the forefront of visual place recognition technology, pioneering new methods for use in mission-critical contexts, including collaborations with Ford and Caterpillar.
Michael’s world-first advancements translating abstract neuroscience into technology for real-world commercial applications were recognised by ATSE in 2019 in awarding him the Batterham Medal for engineering excellence.
For more than 20 years, Michael has been creating STEM educational resources for students.
Michael is at the forefront of visual place recognition technology, pioneering new methods for use in mission-critical contexts, including collaborations with Ford and Caterpillar.
Michael’s world-first advancements translating abstract neuroscience into technology for real-world commercial applications were recognised by ATSE in 2019 in awarding him the Batterham Medal for engineering excellence.
For more than 20 years, Michael has been creating STEM educational resources for students.
FTSE FAA
Co-Director, Applied Artificial Intelligence Initiative, Deakin University
Co-Director, Applied Artificial Intelligence Initiative, Deakin University
Svetha Venkatesh is an ARC Australian Laureate Fellow, Alfred Deakin Professor and a co- Director of Applied Artificial Intelligence Institute (A2I2) at Deakin University.
She was elected a Fellow of the International Association of Pattern Recognition in 2004 for contributions to formulation and extraction of semantics in multimedia data, a Fellow of the Australian Academy of Technological Sciences and Engineering in 2006, and a Fellow of the Australian Academy of Science in 2021 for ground-breaking research and contributions that have had clear impact. In 2017, Professor Venkatesh was appointed an Australian Laureate Fellow, the highest individual award the Australian Research Council can bestow.
Professor Venkatesh and her team have tackled a wide range of problems of societal significance, including the critical areas of autism, security and aged care. The outcomes have impacted the community and evolved into publications, patents, tools and spin-off companies. This includes 668 publications, three full patents, one start-up company (icetana) and two significant products (TOBY Playpad, Virtual Observer).
Professor Venkatesh has tackled complex pattern recognition tasks by drawing inspiration and models from widely diverse disciplines, integrating them into rigorous computational models and innovative algorithms. Her main contributions have been in the development of theoretical frameworks and novel applications for analysing large scale, multimedia data.
This includes development of several Bayesian parametric and non-parametric models, solving fundamental problems in processing multiple channel, multi-modal temporal and spatial data.
She was elected a Fellow of the International Association of Pattern Recognition in 2004 for contributions to formulation and extraction of semantics in multimedia data, a Fellow of the Australian Academy of Technological Sciences and Engineering in 2006, and a Fellow of the Australian Academy of Science in 2021 for ground-breaking research and contributions that have had clear impact. In 2017, Professor Venkatesh was appointed an Australian Laureate Fellow, the highest individual award the Australian Research Council can bestow.
Professor Venkatesh and her team have tackled a wide range of problems of societal significance, including the critical areas of autism, security and aged care. The outcomes have impacted the community and evolved into publications, patents, tools and spin-off companies. This includes 668 publications, three full patents, one start-up company (icetana) and two significant products (TOBY Playpad, Virtual Observer).
Professor Venkatesh has tackled complex pattern recognition tasks by drawing inspiration and models from widely diverse disciplines, integrating them into rigorous computational models and innovative algorithms. Her main contributions have been in the development of theoretical frameworks and novel applications for analysing large scale, multimedia data.
This includes development of several Bayesian parametric and non-parametric models, solving fundamental problems in processing multiple channel, multi-modal temporal and spatial data.
Dr Hung Le
ARC DECRA Fellow and Lecturer, Deakin University
ARC DECRA Fellow and Lecturer, Deakin University
Dr. Hung Le is an ARC DECRA Fellow and Lecturer at Deakin University, specialising in deep learning and reinforcement learning. He completed his PhD at Deakin University in 2020, where he was awarded the Alfred Deakin Medal for Doctoral Theses in recognition of the best thesis award. He leads PhD research in machine learning, reinforcement learning, and large language models at the Applied Artificial Intelligence Initiative (A2I2). His research focuses on developing neural memory-augmented agents, with applications spanning health, robotics, dialogue systems, and natural language processing. Dr. Le has attracted research funding valued at over $1.1 million and regularly publishes papers and delivers talks in leading AI venues such as NeurIPS, ICLR, and ICML.
Dr Scarlett Raine
Lecturer, QUT School of Electrical Engineering and Robotics, and Chief Investigator, QUT Centre for Robotics
Lecturer, QUT School of Electrical Engineering and Robotics, and Chief Investigator, QUT Centre for Robotics
Dr Scarlett Raine is a Lecturer in the QUT School of Electrical Engineering and Robotics, and a Chief Investigator in the QUT Centre for Robotics. In her research, Scarlett is pioneering the use of computer vision and artificial intelligence to analyse underwater images and monitor marine ecosystems more efficiently. She brings her expertise to the Reef Restoration and Adaptation Program as a Chief Investigator on the $3.5m Transition to Deployment sub-program, where she is developing an AI-driven Reef Guidance System for automated re-seeding of temperature resilient coral babies to degraded reefs. She completed her PhD at QUT and CSIRO's Data61 in 2024 on the topic 'Weakly Supervised Segmentation of Underwater Imagery', and was recognised with the Executive Dean’s Commendation for Outstanding Doctoral Thesis Award. Her paper, 'Point Label Aware Superpixels for Multi-Species Segmentation of Underwater Imagery' was awarded the SAGE Publication Prize in 2022. Scarlett's innovative and impactful research, and her commitment to improving representation and diversity in engineering was recently Highly Commended at the Women in Technology Awards, where she was a finalist in both the Emerging Tech and Emerging Science Star categories. Scarlett is motivated by data-constrained and weakly-labelled problems, and automated analysis of challenging real-world field data, with a particular focus on conservation of marine ecosystems.
Director, UNSW AI Institute
Dr Sue Keay is an expert in robotics, AI and automation. She is the Director for UNSW AI Institute and Founder of Robotics Australia Group, the peak body for Australia’s robotics industry. An advocate for diversity in technology, Sue represents Oceania for Women in Robotics and brought the Grace Hopper celebration to Australia in 2019. Sue is a fellow of the Australian Academy of Technology and Engineering (ATSE), a member of the Kingston AI Group and Chief Executive Women, and is on numerous advisory boards, as well as being on the board of computer vision start-up, Visionary Machines. Sue has an MBA from The UQ Business School, a PhD in Earth Sciences from ANU and is a Graduate of the Australian Institute for Company Directors.
Moderator
Data Engineer and Director, The University of Queensland (UQ)
Shazia Sadiq’s research focusses on responsible data management to reduce the socio-technical barriers to data driven transformation, by assisting organisations to create, protect and sustain agile data pipelines for advanced analytical models and AI solutions. As an educator for over two decades, she is a passionate advocate of ethical educational technology for improving personalized learning and equitable graduate outcomes for diverse student cohorts. Shazia is Director for the ARC Industry Transformation Training Centre on Information Resilience 2020-2025, past chair of the National Committee on ICS at the Australian Academy of Science 2019-2022, and member of The Australian Research Council College of Experts 2018-2021.
