Professor Richard Sinnott is the Professor of Applied Computing Systems and Director of eResearch in the School of Computing and Information Systems, Faculty of Engineering and Information Technology at the University of Melbourne. He leads the Melbourne eResearch Group (MeG), which supports the development and delivery of research-oriented IT systems to diverse research communities using agile processes, bleeding-edge technologies, open-source solutions, and rapid prototyping. With over 15 years of experience, MeG has delivered robust systems adopted globally by thousands of users and supporting millions of dollars in research funding. Sinnott's expertise spans security in demanding domains like rare genetic diseases, cloud computing across IaaS, PaaS, and SaaS models using technologies such as OpenStack and AWS, big data challenges of volume, velocity, variety, and veracity in areas like genomics, urban research, and social media analytics, as well as data management with noSQL databases and distributed systems including Hadoop and Elasticsearch.

Sinnott earned his PhD in Computing Science and MSc in Software Engineering from the University of Stirling, where he served as Research Associate from 1993 to 1997. He was Managing Director of the National e-Science Centre at the University of Glasgow from 2002 to 2010 before joining the University of Melbourne in 2010. Key projects under his leadership include the Australian Digital Observatory for social media data analysis with topic modeling and sentiment analysis, the Australian Urban Research Infrastructure Network (AURIN) for big data platforms, the EDGE platform for evaluating Victorian early childhood education, and clinical registries for conditions such as adrenal cancer, spinal trauma, type 1 diabetes via the ENDIA study, and rare diseases like Niemann-Pick. He has authored over 450 publications, including 'A survey of video-based human action recognition in team sports' (2024), 'Platypus Detection Through Deep Learning' (2024), 'Semantic Segmentation of Food Through Deep Learning: A Case Study' (2024), and contributions to SARS-CoV-2 infection studies in islet autoimmunity (2025). Sinnott has supervised over 1000 Master's dissertations and numerous PhD students, educated over 500 in cloud computing, and delivered keynotes such as at AusPDC2024. His team received a University of Melbourne Excellence Award in 2022.

Professional Email: rsinnott@unimelb.edu.au