ENGAGE : Interactive Machine Learning Accelerating Progress in Science, An Emerging Theme of ICT Research

我们的愿景是建立并引领基于交互式机器学习（IML）的信息通信技术研究的新主题。我们对IML的扩展将为科学家和非ict专家提供前所未有的尖端机器学习算法，通过提供人机界面，他们可以在直观的视觉环境中直接与大规模数据和计算资源进行交互。此外，这个特殊项目的成果将对科学产生直接的变革性影响，使非编程人员（科学家）能够创建半自动检测大量音频和视觉数据中的物体和事件的系统。通过在两个并行的、高度互联的信息通信技术研究流中共同努力，我们将为IML开发统计方法、算法和系统的基础。作为一个范例，该项目与世界领先的科学家合作，努力应对分析生物多样性科学中产生的大量异构数据的挑战。

Our vision is to establish and lead a new theme in ICT research based on Interactive Machine Learning (IML). Our expansion of IML will give scientists and non-ICT specialists unprecedented access to cutting-edge Machine Learning algorithms by providing a human-computer interface by which they can directly interact with large scale data and computing resources in an intuitive visual environment. In addition, the outcome of this particular project will have a direct transformative impact on the sciences by making it possible for non-programming individuals (scientists), to create systems that semi-automatically detect objects and events in vast quantities of A) audio and B) visual data. By working together across two parallel, highly interconnected streams of ICT research, we will develop the foundations of statistical methodology, algorithms and systems for IML. As an exemplar, this project partners with world leading scientists grappling with the challenge of analysing enormous quantities of heterogeneous data being generated in Biodiversity Science.