Closed-Loop Data Science for Complex, Computationally- and Data-Intensive Analytics

传感、计算能力、存储和分析工具的进步使我们能够访问大量复杂的数据，这些数据可以为我们提供更好的方法来管理我们的城市、运营我们的公司或开发新药。然而，“房间里的大象”是，当我们对这些数据采取行动时，我们改变了世界，潜在地使较旧的数据无效。同样，当监测活着的城市或公司时，我们无法对它们进行干净的实验-我们获得的数据受到它们今天运行方式的影响，这限制了我们对这些复杂系统进行建模的能力。我们需要在如此复杂的系统上进行持续实验的方法。我们还需要支持人类与大型复杂数据集的交互。在这个项目中，我们将考察一个人在处理与预订周末度假机票相关的所有选择时所面临的挑战与在实验室进行复杂实验的专家之间的重叠。该项目将在多个领域测试核心想法，包括助听器的个性化、癌症数据的分析，以及为一家大银行调整计算资源。

Progress in sensing, computational power, storage and analytic tools has given us access to enormous amounts of complex data, which can inform us of better ways to manage our cities, run our companies or develop new medicines. However, the 'elephant in the room' is that when we act on that data we change the world, potentially invalidating the older data. Similarly, when monitoring living cities or companies, we are not able to run clean experiments on them - we get data which is affected by the way they are run today, which limits our ability to model these complex systems. We need ways to run ongoing experiments on such complex systems. We also need to support human interactions with large and complex data sets. In this project we will look at the overlap between the challenge someone faces when coping with all the choices associated with booking a flight for a weekend away, and an expert running complex experiments in a laboratory.The project will test the core ideas in a number of areas, including personalisation of hearing aids, analysis of cancer data, and adapting the computing resources for a major bank.