November 2022 SCS Awards
M.A.P. Chamikara is a highly skilled researcher with a strong track record of collaboration and successful project leadership. He has contributed to the development of a patent and the expansion of the ‘Personal Information Factor’ project to the ‘Australia’s Data Emerging Privacy Preserving Techniques’ project. In addition, he has created internship opportunities for international undergraduate students and is also involved in PhD supervision at multiple universities.
Yanfeng has demonstrated exceptional ability in both internal and external collaboration, contributing to successful partnerships with Boeing, multiple CSIRO business units, SMEs in the Digital Agriculture sector, and universities. She has brought her expertise in knowledge graphs and information management to a variety of projects and effectively led cross-functional teams. Her research collaborations have resulted in high-quality publications and strengthened relationships with key partners.
The Privacy team provided exceptional customer service and technical expertise while developing innovative privacy-preserving analytics solutions for Practera and the University of South Australia. The solutions were successfully integrated into Practera’s Learning Analytics Toolbox. The team also helped present these solutions to the Ed-Tech community, further demonstrating their commitment to providing excellent customer service.
Dilum provided exceptional service to the Digital Finance CRC by delivering a new course in Digital Finance technology for the initial cohort of PhD students. His systematic and pedagogical approach, as well as the interactive in-class activities, resulted in positive feedback from the students as well as the DFCRC. The course will be used in future DFCRC courses and a Digital Finance MBA program at multiple universities, demonstrating the success and value of Dilum’s efforts.
The team successfully completed the RDTI Meta-Analysis Project for DISER, developing guidance for assessing software and AI research and development. They conducted a qualitative meta-analysis of 60 case studies and provided independent technical advice and insights on software and AI R&D. The project outcomes were well received by DISER staff who found the report and material very engaging, informative, and valuable for their future work.
The PIF (Personal Information Factor) team developed an innovative solution that assesses risks to individual data in datasets and enables targeted protection. The tool has been well received by government agencies in Western Australia and New South Wales and received testimonials from government officials praising its impact on data-sharing activities. The PIF project also won a Merit award in the Technology Platform Solution category of the New South Wales iAwards 2022 and was a finalist in the national iAwards 2022.
The US Army Project team has published two papers in top-tier security venues: ACSAC 2022 and ACM CCS 2022. The ACSAC paper is the first to examine the use of transformer-based models on code gadgets, which are small pieces of source code that capture data and control dependencies. The ACM CCS paper presents a machine learning framework for running distributed machine learning algorithms such as federated learning and split learning. The team has also developed a machine learning and natural language processing-based Crypto Function Detector, which is being extended to detect crypto functions that may be vulnerable to attacks from quantum computers.
Frank has published two high quality papers in top software engineering conferences, ICSME and ASE, in the past six months. His first paper, published in ICSME, proposes an automatic method for recovering traceability of discrepant vulnerability entries among different databases using key aspects and text-matching methods. His second paper, published in ASE, uses prompt-based training and self-training techniques with a BERT-based model to improve performance in software requirement classification under low-training data situations. Frank’s work demonstrates science excellence in the field of software engineering.
Yilin’s technical expertise in smart contract and web3 development was instrumental in his role as a member of the Central Bank Digital Currency (CBDC) project team at the Digital Finance CRC (DFCRC). He served as the lead developer for a demo app that provides access to the full range of CBDC functionality through a web interface and completed numerous unit test cases that contributed to the project’s achievement of 100% line coverage.