Find an expert

Shakes an imaging expert that leads a strong deep learning, artificial intelligence (AI) focused research team interested in medical image analysis and signal/image processing applied to many areas of science and medicine. He received his Ph.D in Theoretical Physics from Monash University, Melbourne and has been involved in applying machine learning in medical imaging for over a decade.

Shakes’ past work has involved developing shape model-based algorithms for knee, hip and shoulder joint segmentation that is being developed and deployed as a product on the Siemens syngo.via platform. More recent work involves deep learning based algorithms for semantic segmentation and manifold learning of imaging data. Broadly, he is interested in understanding and developing the mathematical basis of imaging, image analysis algorithms and physical systems. He has developed algorithms that utilise exotic mathematical structures such as fractals, turbulence, group theoretic concepts and number theory in the image processing approaches that he has developed.

He is currently a Senior Lecturer and leads a team of 20+ researchers working image analysis and AI research across healthcare and medicine. He currently teaches the computer science courses Theory of Computation and Pattern Recognition and Analysis.

Jen Jen Chung is an Associate Professor in Mechatronics within the School of Electrical Engineering and Computer Science at The University of Queensland. Her current research interests include perception, planning and learning for robotic mobile manipulation, algorithms for robot navigation through human crowds, informative path planning and adaptive sampling. Prior to working at UQ, Jen Jen was a Senior Researcher in the Autonomous Systems Lab (ASL) at ETH Zürich from 2018-2022 and was a Postdoctoral Scholar at Oregon State University researching multiagent learning methods from 2014-2017. She completed her Ph.D. on information-based exploration-exploitation strategies for autonomous soaring platforms at the Australian Centre for Field Robotics in the University of Sydney. She received her Ph.D. (2014) and B.E. (2010) from the University of Sydney.

Shane Culpepper is Professor of Artificial Intelligence at the University of Queensland in St. Lucia, Australia. Before joining the University of Queensland in 2023, Professor Culpeper held a continuing academic position at RMIT University in Melbourne, Australia. He received his PhD in Computer Science from the University of Melbourn in 2008. His research focuses primarily on building better Search and Recommendation Systems. Over his 16 year career, Professor Culpepper has supervised 19 PhD students and co-authored more than 120 peer reviewed papers with 127 different research collaborators on problems such as algorithm efficiency and scalability, new machine learning algorithms for search and recommendation systems, and evaluating search and recommendation engine quality. Professor Culpepper is also an active member in the international research community. In the last 5 years, he has been a program co-chair for international conferences such as SIGIR and CIKM, and co-organized conferences such as WSDM and SWIRL. Professor Culpepper previously held an ARC DECRA fellowship in 2013 as well as an RMIT Vice-Chancellor's Princpal Researcher fellowship in 2017. Before joining the University of Queensland. Professor Culpepper was the founding director of the Centre for Information Discovery and Data Analytics at RMIT University. In total, he has been a chief investigator on 11 reseach grants totalling ~$3.5 Million AUD. For more information, see his personal hoomepage.

Dr Kai Li Lim is the inaugural St Baker Fellow in E-Mobility at the UQ Dow Centre for Sustainable Engineering Innovation. Specialising in data science, engineering, and emerging technologies, Dr Lim focuses on real-time vehicle telematics, infrastructure management, and computer vision-based autonomous driving.

At UQ, Dr Lim's research centres on electric vehicle (EV) usage and charging patterns to inform adoption policies and strategies. His work includes examining trends for incentive design and assessing the environmental and economic impacts of EVs. Dr Lim's current focus is on charging reliability and addressing EV drivers' pain points. His research has been featured in academic, industry, and media publications, facilitating discussions with various stakeholders.

Dr Lim has published a range of articles, book chapters, and conference papers in reputable venues. He has delivered invited talks and appeared in media outlets such as ABC, Courier Mail, and The Conversation. Collaborating with various UQ schools, including Civil Engineering, Electrical Engineering and Computer Science (EECS), Economics, and Environment, Dr Lim has secured funding for projects on topics like carbon emissions offset after EV uptake and evaluating price incentives for EV charging using real-time data.

In addition to his work at UQ, Dr Lim collaborates closely with the UC Davis Electric Vehicle Research Center, where he recently completed a six-month visiting fellowship on EV charging. He engages in speaking events and networking opportunities centred on sustainability and transportation innovation, delivering keynote speeches at conferences and industry roundtables.

Dr Lim holds a BEng (Hons) degree in electronic and computer engineering from the University of Nottingham, an MSc degree in computer science from Lancaster University, and a PhD degree from The University of Western Australia, supported by the Australian Government under the Research Training Programme.

Dr. Morteza Namvar is a Senior Lecturer at the UQ Business School and a member of Future of health - Business School - University of Queensland. He specializes in Machine Learning (ML), Natural Language Processing (NLP), and Large Language Models (LLMs) in business contexts. With a foundation in computer science and IT engineering, he brings interdisciplinary expertise to his research, focusing on the application of ML-driven solutions in organizational and healthcare settings.

Morteza is deeply committed to advancing ML, NLP, and LLM research in business and healthcare, mentoring PhD and HDR students in leveraging these technologies to drive innovation, automation, and efficiency across various industries. He has successfully secured competitive funding for multiple ML and NLP projects and has published extensively in leading IS and computer science journals and conferences.

Beyond research, Morteza is passionate about educating the next generation of ML practitioners. His teaching focuses on hands-on ML development using Python, equipping students with the technical skills and confidence needed to excel in the rapidly evolving field of machine learning.

Research interest: Monitoring ecosystem health of coral reefs and seagrass habitats, integrating field and remote sensing image datasets, and the developing applied cost-effective mapping and monitoring approaches. Developed approaches have been adopted as standard practice globally, making a difference in conservation of these valuable habitats. The long term monitoring studies at Heron and Moreton Bay formed the basis for the development of mapping and monitoring over time and space at local to global scale. See here major research impact

Major projects:

• Long term monitoring of benthic composition at Heron Reef (2002-ongoing).
• Long term monitoring of seagrass composition and abundance in Moreton bay Marine Park (2000-ongoing).
• Smart Sat CRC Hyperspectral Remote Sensing of Seagrass and Coral Reefs 2023-2027.
• Developement of Underwater Field Spectrometry and Benthic Photo Collection and Analysis
• 3D GBR Habitat Mapping Project 2015 - ongoing:
• Global habitat mapping project 2019-2023 Allen Coral Atlas .

Current position: Associate Professior in Marine Remote Sensing leading the Marine Ecosystem Monitoring Lab. . Academic Director Heron Island Research Station and affiliated researchers with Centre for Marine Science and Centre for Biodiversity and Conservation Science

Capacity Building and Citizen Science: Capacity: under/post graduate courses; Msc/PhD supervision, workshops/courses; Remote Sensing Educational Toolkit, and online courses (e.g. TNC).Strong supporter of citizen science based projects, as trainer, organiser and advisor for Reef Check Australia, CoralWatch, Great Reef Census and UniDive.