Responsible modelling respecting privacy, data quality, and green computing

随着数据对科学、经济和社会的影响前所未有地增长，人们需要负责任的数据科学实践，对社会公益负责。该项目旨在研究如何提供负责任的数据管理这一具有挑战性的问题，包括隐私感知数据探索、科普不完美数据的弹性建模以及资源受限环境的高效模型架构。这将通过发展理论和技术，在整个数据生命周期的复杂的现实世界的多模态数据检索。预期成果将大大有助于在负责任的数据科学背景下建设新兴技术的能力。

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.