Dr Darya Vanichkina1, Dr Glen Charlton2, Dr Kyle Hemming3, Dr Benjamin Goudey4, Dr Anastasios Papaioannou5, Dr Julie Iskander6, Dr Patrick Tung7
1Sydney Informatics Hub (SIH), Core Research Facilities, University of Sydney, Camperdown, Australia, 2Advanced Analytics & AI (3AI) Platform, Intersect Australia, Sydney, Australia, 3University of Auckland, Auckland, New Zealand, 4Australian BioCommons, University of Melbourne, Parkville, Australia, 5eResearch Platforms and Services, University of Technology Sydney, Ultimo, Australia, 6Walter and Eliza Hall Institute (WEHI), Parkville, Australia, 7Research Technology Services, University of New South Wales, Randwick, Australia
Biography:
Darya Vanichkina PhD SFHEA is the Data Science & AI Group Lead at the Sydney Informatics Hub, a University of Sydney Core Research Facility dedicated to enabling excellence in data and compute-intensive research. Darya leads a team that delivers consultancy services and training to boost research outcomes and funding, accelerate projects, and foster partnerships with industry and government. In 2025, her team is championing AI adoption for research across the University’s faculties and affiliates.
https://orcid.org/0000-0002-0406-164X
Dr Glen Charlton is the Lead Data Scientist for the Advanced Analytics & AI Platform at Intersect Australia. The team empowers researchers with data science and AI through hands-on support and knowledge transfer to improve efficiency and increase capability of researchers to conduct novel, practically relevant research. Glen actively promotes novel and responsible adoption of AI for both research and operational purposes within members, partners and internally within Intersect.
https://orcid.org/0000-0002-1482-9720
Dr. Kyle Hemming is a Senior eResearch Engagement Specialist at the University of Auckland, supporting researchers in data science, data management, and responsible AI adoption. With a decade of quantitative research experience and eight years supporting researchers, he is passionate about improving research outcomes. His interests also include reproducible research, strategic planning, and stakeholder engagement.
https://orcid.org/0000-0001-5913-3981
Dr Benjamin Goudey is AI Technical Lead at Australian BioCommons, a national digital infrastructure capability that provides access to tools, methods, and training for life science researchers. His role focuses on improving national AI capabilities and reducing barriers to adoption across life science research. Ben brings extensive experience from industry and academia in AI application and predictive modelling to a range of biological domains, evidenced by a strong record of publications and patents.
https://orcid.org/0000-0002-2318-985X
Anastasios Papaioannou is a Senior Manager leading the eResearch Platforms and Services at UTS, where he oversees cloud and high-performance computing, research data storage, training, and the integration of AI in research. He actively works on the adoption of AI by collaborating with UTS colleagues to develop a comprehensive suite of AI guidelines, tools, and training programs for researchers. With a strong background in research, data science, and computational physics, he works closely with academics and HDR students to help them leverage large-scale infrastructure and digital technologies to accelerate research. https://orcid.org/0000-0002-8959-4559
Dr Julie Iskander leads the Research Computing Platform at WEHI, where she brings her background in software engineering, computational biology, and biomedical research to drive infrastructure development and support scalable, data-driven science. Her team helps researchers bridge the gap between scientific questions and computational solutions, with growing emphasis on making AI tools and cloud platforms accessible across disciplines.
https://orcid.org/0000-0002-3426-4376
Dr. Patrick Tung is the AI Imaging Scientist at UNSW’s Research Technology Services. He collaborates across disciplines to apply AI in computer vision, particularly for 3D imaging and materials and medical analysis. With a background in tomography and diffraction, he has held postdoctoral roles in Australia and Europe. His research focuses on deep learning for structural analysis in materials for energy systems and circular economies, contributing to innovations in imaging techniques and computational modeling.
https://orcid.org/0000-0002-2741-3177
Abstract:
Situation
Artificial Intelligence (AI) tools are widely available and are transforming how knowledge work is conducted globally, yet AI adoption in research across Australasia remains somewhat limited. Researchers face a landscape of challenges that limit the adoption of AI in the research lifecycle, including concerns around data privacy and sovereignty, ethical oversight, accuracy and reproducibility, bias, intellectual property management and copyright, infrastructure limitations, the environmental impact of large-scale AI models, and more.
Task
In this BoF session, we will discuss these barriers through the lens of real-world experiences from our institutions. We will share case studies that demonstrate how some of these challenges have been addressed through innovative solutions, guidelines, and awareness. We will also highlight how emerging tools and ready-to-use infrastructure can lower the barrier to entry for researchers and provide a safe environment to use and experiment with AI.
Action
Our goal is to coordinate a collaborative discussion on how cross-institutional initiatives may benefit wider AI adoption in research. Together, we will identify opportunities for cross-institutional initiatives to accelerate AI literacy, infrastructure readiness, and policy/guidelines alignment across the region.
Result
Whether you are an AI enthusiast or a cautious sceptic, this session offers a space to share experiences, exchange ideas, and learn from one another, so we can better support researchers and collectively advance the adoption of AI in research.