From 16-20 October, members of the NeSI team attended the 2023 eResearch Australasia Conference to learn from peer experiences across the Australian sector as well as share insights from our collab... Read more

Please join us in welcoming the newest members to the NeSI team!  Attribution:  Lai Kei Peng, Senior Data and Insights AnalystI have been a University of Auckland librarian for more than 10 years a... Read more

On 2 November, Nisha Ghatak (NeSI) and Liz Stokes (ARDC) hosted the final Carpentries communities discussion this year for members in New Zealand and Australia.FocusThe primary aim of the call was ... Read more

A global consortium of scientists from federal laboratories, research institutes, academia, and industry has formed to address the challenges of building large-scale artificial intelligence (AI) sy... Read more

SupercomputingAsia 2024’s (SCA 2024) call for abstracts is now open. Typically held in Singapore, SCA 2024 is coming to Sydney, Australia from 19-22 February 2024. This is is the first time SCA is ... Read more

Picture of a baby sitting on a rug, facing away from the camera. Image by thedanw from Pixabay

AI app to identify cerebral palsy in infants

“Our eyes cannot focus on the arm, leg and eyes at the same time, but a machine can learn the connectivity in the limbs’ movements.”
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As more domains integrate computational and data-focused approaches to the way they work, we're seeing research communities' needs evolve beyond traditional models of queue-based High Performance C... Read more

This image depicts a Deep Learning model's prediction of adult Tarāpuka (Black-billed gulls) sitting on nests in a colony. The ground truth is pictured on the left, and the prediction is on the right. Image courtesy of Saif Khan.

Using Deep Learning to detect braided river bird populations

"To be honest, being an ecologist, I was a bit nervous to approach people from advanced data science space. But this fear diminished quickly as all involved in the project was more than ready to understand my needs and was ready to work with my strengths.
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Photo of a riparian strip. Credit Dave Allen, NIWA.

Tools to better understand and address water quality issues

"The team at NeSI worked with us to provide a solution to achieve significant speed-up in legacy R- and FORTRAN-based code for catchment model runs."
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Person wearing a virtual reality headset. Image by Wren Handman from Pixabay

AI software learns, tracks and predicts cybersickness in virtual reality users

“It would take me a day to train one machine learning model [on my desktop], but I'd train something like 56 models in a day on Mahuika.”
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