Responsible modelling respecting privacy, data quality, and green computing

尊重隐私、数据质量和绿色计算的负责任的建模

• 批准号: DP230101196
• 负责人: Prof Zi Huang
• 金额: $ 34.17万
• 依托单位: The University of Queensland
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2023
• 资助国家: 澳大利亚
• 起止时间: 2023-12-31 至 2026-12-30
• 项目状态: 未结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP230101196
• 关键词: Responsible; modelling; respecting; privacy; data

With the unprecedented growing impact of data on science, the economy and society, there comes the need for responsible data science practices which are accountable for the social good. This project aims to investigate the challenging problem of how to provide responsible data management, spanning across privacy-aware data exploration, resilient modelling to cope with imperfect data, and efficient model architectures for resource-constrained environments. This will be achieved by developing theories and techniques for complex real-world multi-modal data retrieval throughout the data life-cycle. The expected outcomes will significantly contribute to building capability in emerging technologies in the context of responsible data science.

随着数据对科学、经济和社会的影响空前增长，需要负责任的数据科学实践，对社会利益负责。该项目旨在研究如何提供负责任的数据管理，跨越隐私感知数据探索，弹性建模以应对不完美数据，以及资源受限环境的有效模型架构等具有挑战性的问题。这将通过在整个数据生命周期中为复杂的现实世界多模态数据检索开发理论和技术来实现。预期的结果将大大有助于在负责任的数据科学背景下建立新兴技术的能力。