3 trainers found

Expertise technical: Requirements Analysis  or Training development 

and

Interest: Data Management Systems  or Open Science  or Python 


Giorgia Mori

Giorgia is a Data Science Trainer at the Sydney Informatics Hub (SIH), University of Sydney. She has a background in microbiology and bioinformatics. She is a Software, Data and Library Carpentry instructor, and she has been supervising, teaching and training staff and students in the development...

Location: Sydney, Australia

Mori Giorgia giorgia.mori@sydney.edu.au Sydney, Australia Giorgia is a Data Science Trainer at the Sydney Informatics Hub (SIH), University of Sydney. She has a background in microbiology and bioinformatics. She is a Software, Data and Library Carpentry instructor, and she has been supervising, teaching and training staff and students in the development of computational skills for conducting efficient and reproducible research. She volunteers in diversity initiatives (RLadies, PyLadies) to support the representation of gender minorities in the programming community. ["English", "Italian"] https://orcid.org/0000-0003-3469-5632
Pauline Lawrey

I have worked in IT as a developer, software engineer, analyst and project manager for 20+ years. I'm currently working for James Cook University and QCIF as an eResearch Analyst. I primarily instruct the Python and Git training courses but plan on branching out. I'm very interested in ways to...

Location: Townsville, North Queensland

Lawrey Pauline pauline.lawrey@jcu.edu.au Townsville, North Queensland I have worked in IT as a developer, software engineer, analyst and project manager for 20+ years. I'm currently working for James Cook University and QCIF as an eResearch Analyst. I primarily instruct the Python and Git training courses but plan on branching out. I'm very interested in ways to help researchers after that introductory training session and training development. ["English"]
Tim Langlois

Stereo imagery is widely used by research institutions and management bodies around the world as a cost-effective and non-destructive method to research and monitor fish and habitats (Whitmarsh, Fairweather and Huveneers, 2017). Stereo-video can provide accurate and precise size and range...

Location: GitHub

Langlois Tim tim.langlois@uwa.edu.au GitHub Stereo imagery is widely used by research institutions and management bodies around the world as a cost-effective and non-destructive method to research and monitor fish and habitats (Whitmarsh, Fairweather and Huveneers, 2017). Stereo-video can provide accurate and precise size and range measurements and can be used to study spatial and temporal patterns in fish assemblages (McLean et al., 2016), habitat composition and complexity (Collins et al., 2017), behaviour (Goetze et al., 2017), responses to anthropogenic pressures (Bosch et al., 2022) and the recovery and growth of benthic fauna (Langlois et al. 2020). It is important that users of stereo-video collect, annotate, quality control and store their data in a consistent manner, to ensure data produced is of the highest quality possible and to enable large scale collaborations. Here we collate existing best practices and propose new tools to equip ecologists to ensure that all aspects of the stereo-video workflow are performed in a consistent way. ["English", "French"] https://orcid.org/0000-0001-6404-4000