AI Skill Training Pathway: Bridging Gaps and Fostering Inclusivity
Frederick Fung1, Slava Kitaeff2, Anastasios Papaioannou3, Partric Tung 4, Jingbo Wang1, Maxime Rio, Mike Laverick, Mitchell Hargreaves, Mark Crowe, Abdullah Shaik
1National Computational Infrastructure, Canberra, ACT, Australia, 2 Monash eResearch Centre, Melbourne, Victoria, Australia, 3Intersect, Sydney, NSW, Australia, 4ResTech UNSW, Sydney, NSW, Australia
Abstract
This BoF session aims to aid in the development of a strategy which ensures the research support community can meet the needs of researchers reliant on computationally intensive Artificial Intelligence (AI) models. As the use of AI models, particularly within computationally intense disciplines, increases exponentially, we’ve observed a surge in researchers utilising the National Computing Infrastructure (NCI) as their computational resource for AI research. Disciplines such as Astronomy, Bioinformatics, and Earth Sciences are increasingly employing AI techniques to address domain-specific inquiries, as exemplified by the recent development of domain-specific GPT models during a Hackathon hosted at the NCI.
Our session aims to assemble a diverse group, including academics, industry professionals, and HDR students, to foster a 90-minute dialogue focused on bridging the technical gap between researchers and AI modelling techniques. In our pursuit to upskill AI talents and the new generation of researchers, we will explore innovative teaching methodologies, collaborative industry-academia initiatives, evolving curriculum development strategies, and effective corporate training programs.
Further, the session will highlight pathwaysto make AI training more accessible and inclusive for all researchers and HDR students, addressing barriers and pain-points to ensure diverse perspectives within the AI field.
Biography
Frederick Fung https://orcid.org/0000-0003-1417-4995 currently serves as the Training and Research Engagement Manager at the National Computational Infrastructure (NCI).
Patrick Tung ORCID ID: https://orcid.org/0000-0002-2741-3177
Patrick Tung Bio: Patrick Tung completed his PhD in 2018 in Materials Science followed by postdocs in X-ray and neutron imaging. He is currently an AI Imaging Officer at Research Technology Services at UNSW.
Slava Kitaeff https://orcid.org/0000-0002-9690-9395 holds a PhD in Computational Physics. Presently, he is Associate Director eResearch at Monash University.