We’d like to welcome Zhuochen Wu to CIRES! Zhuochen joined the Centre as a Data Engineer in November 2022 and is based at Swinburne University of Technology. Her main work includes data curation, resilient data pipelines, graph databases and distributed ETL systems, with a focus on data extraction and analytics pipeline integration. Zhuochen has a degree of Master of Computing with Data Science specialisation from the Australian National University. She works closely with Chief Investigator Associate Professor Amir Aryani. She is excited by the diverse projects within the Centre and is looking forward to collaborating with other researchers to find meaningful insights from data.
We’d like to welcome Dr Shaoyang Fan to CIRES! Shaoyang joined CIRES as a Data Engineer in July 2023 at The University of Queensland. Shaoyang is a data scientist and specialises in microtask crowdsourcing, data quality, and bias. He works closely with Chief Investigator Associate Professor Gianluca Demartini, working in data curation and human computation research, including constructing crowd-sourced data curation processes. He has a PhD in Computer Science and Master of Science in Information Technology, both from UQ, and Master of Science in Econometrics from The University of Manchester.
Shaoyang is looking forward to applying his technical skills and passion for data science to make impactful contributions to the Centre.
Congratulations to School of EECS, Professor Helen Huang, and CIRES CI, Dr Sen Wang, for the successful $5M funding of the ARC Training Centre in Predictive Breeding for Agricultural Futures. The Centre will train the next generation of breeders and develop cutting-edge predictive breeding technologies in partnership with industry. The Centre will train 31 PhDs, seven Postdocs and perform research across 21 agriculturally important species. The Centre brings together significant contributions from five Australian universities and 30 national and international partner organisations, and now the ARC, to a total value of $136M.
Congratulations to CIRES Chief Investigator Associate Professor Gianluca Demartini and fellow authors who received the Best Paper Award for their work “Perspectives on Large Language Models for Relevance Judgment” https://lnkd.in/gmf3qU97
The work is the result of an international collaboration between researchers in Italy, USA, Canada, Australia, Germany, Netherlands, and Japan, who highlight the risks and opportunities of large language models and their impact on information retrieval research. The award was given by a committee of information retrieval experts at the ACM, Association for Computing Machinery‘s SIGIR International Conference on the Theory of Information Retrieval in Taipei last week.
We have a number of reading groups happening across the Centre and it’s a key part of our cross-collaboration between our university partners Swinburne University of Technology and The University of Queensland.
Great conversation in the Computational Social Science Reading group led by CIRES Postdoc Dr Hui Yin, PhD researchers Pa Pa Khin and Lufan Zhang, and Dr Javad Pool, around AI-enabled knowledge sharing and learning.
Swinburne University of Technology, hosted our second Computational Social Science Reading group with the collaboration of colleagues at the University of Queensland, part of the ARC Training Centre for Information Resilience (CIRES).
Dr. Hui Yin leads the conversation today with a focus on a paper about knowledge management titled ” AI-enabled knowledge sharing and learning: redesigning roles and processes” (https://lnkd.in/g8xSTg3c). Pa Pa Khin gave a detailed introduction to this paper. This research paper provides a comprehensive framework for analyzing AI’s impact on various practices in knowledge management, and it uncovers the vital necessity of tailored AI-enabled knowledge management systems to cater to modern knowledge worker demands. We had a productive conversation about the role of AI in facilitating organizational knowledge sharing and learning, and how it can support knowledge management activities.