AI 101 and Applied AI in Research Infrastructure
This session will provide an overview of the use of Artificial Intelligence in research infrastructure, including a general introduction to AI and machine learning concepts, consideration of the responsible and ethical use of AI, and case studies illustrating practical applications in research support and infrastructure settings. It is intended to give attendees a broad understanding of current opportunities, considerations, and emerging uses of AI relevant to research infrastructure.
Dr Renuka Sharma will outline AI efforts in the WildObs project that utlises advanced image classification models in supporting national wildlife conservation.
Dr Gnana Bharathy looks to convey risks and opportunities of AI and what it means to be the human in the loop under emerging ethical considerations and concepts of responsible AI.
Renuka is a Data Scientist (Computer Vision and Ecology) at QCIF Digital Research, contributing to wildlife and ecological conservation projects. At the Wildlife Observatory of Australia (WildObs), she designs and implements computer vision (AI) pipelines to support wildlife conservation efforts. In collaboration with EcoCommons, Renuka develops learning materials to help students and researchers use computer vision tools for ecological research and data analysis. She is also involved in mentoring and supervising research projects.
Prior to joining QCIF, Renuka worked as a Postdoctoral Research Fellow at CSIRO's Data61. Her research focused on behaviour recognition using computer vision and multi-modal sensing across diverse domains, ranging from agriculture to aged care. She obtained her joint PhD in Computer Vision from Monash University and IIT Bombay (India).
Dr Gnana Bharathy is a practitioner, mentor and closet researcher, working in AI/ML and advanced analytics, with an emphasis on socio-technical systems approaches. Gnana brings well over twenty years of experience spanning both industry and research sectors, with demonstrated success in establishing and delivering AI and data science capabilities from inception and addressing complex social and technical challenges.
Based at UTS as Data Science and AI Manager, Gnana primarily serves as an AI/ML specialist at the ARDC, where he has been co-leading the Advanced Analytics stream of work for the People Research Data Commons. In this capacity, Gnana has also individually contributed to framework development, pathfinder projects, co-design, reference architecture design, and the development of programs of work, and continues to contribute as an AI specialist.
Gnana's particular expertise lies in model development, assessment and evaluation, with a strong emphasis on socio-technical systems, ethics and governance.
Gnana is also co-leading the Machine Learning for Australia (ML4AU) Community of Practice
