Data Science

数据科学

• 批准号: CRC-2019-00426
• 负责人: Plan, Yaniv
• 金额: $ 7.29万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Canada Research Chairs
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=696025
• 关键词: Data; Science

New connections between mathematics and applied data analysis have facilitated new methods of data collection and interpretation. This has led to a fundamentally new method of magnetic resonance imaging (MRI), with remarkable improvements in image quality and speed of image acquisition. The key is to understand the structure of the signal lurking in the data -- in many cases this signal belongs to a complex, yet low-dimensional, set. I study these structures, how they behave under various forms of measurement acquisition, and how to take advantage of their low dimensionality to make inferences in a computationally efficient manner.

数学和应用数据分析之间的新联系促进了数据收集和解释的新方法。这导致了一种全新的磁共振成像（MRI）方法，在图像质量和图像采集速度方面有了显着的改进。关键是要理解隐藏在数据中的信号的结构——在许多情况下，这个信号属于一个复杂的低维集合。我研究这些结构，它们在各种形式的测量采集下的行为，以及如何利用它们的低维性以计算高效的方式进行推断。