RTG: Cross-Training in Statistics and Computer Science

RTG：统计和计算机科学的交叉培训

• 批准号: 1547433
• 负责人: Marina Vannucci
• 金额: $ 140万
• 依托单位: William Marsh Rice University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-08-15 至 2020-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1547433&HistoricalAwards=false
• 关键词: RTG; Cross; Training; Statistics; Computer

Data science is rapidly evolving as an essential interdisciplinary field, where advances often result from combinations of ideas from various parts of mathematics, statistics, computer science, physical sciences, and engineering, as well as other disciplines. New types of (large) data have emerged, presenting unprecedented complexities and challenges that require a new way of thinking. The goal of this Research Training Group (RTG) project is to provide inherently interdisciplinary training to undergraduate and graduate students, as well as post-doctoral fellows, developing skills that transcend individual disciplines. Training students through research involvement in areas that combine statistical and computational modeling and inference will provide the intellectual foundation for a new generation of scientists poised to make novel breakthroughs in this exciting area, and contribute to the research and design efforts in the private and public sectors. This project will catalyze original research on modeling and inference for large datasets. The program will involve three undergraduate students, six graduate students, and two postdoctoral fellows at any given time. The undergraduate component will be an integrated research experience, consisting of a seminar course, where students will learn and present material on key topics, and active participation in research projects, where these topics are put into practice. Each trainee will work with at least two RTG faculty members to ensure a truly interdisciplinary training experience. A new course in "data science" will be developed, for education of trainees across traditional department boundaries. Throughout the calendar year, the Research Training Group will sponsor advanced courses and research lectures for the benefit of the graduate and postdoctoral participants. The program builds upon the strengths and interactions of a dynamic group of faculty, with expertise in the general area of probabilistic models and methods for computational inference. Trainees will benefit from individualized mentoring activities and participation in structured research groups. The interdisciplinary nature of these activities will lead to a newly trained generation of researchers capable of generating new approaches and ideas. Resources and tools for cross-training will be developed and disseminated to the community. Exposure to modern aspects of data science and computing will enhance the professional development of the trainees. Cutting-edge research at the interface between statistics and computer science will be enhanced.

数据科学正在迅速发展成为一个重要的跨学科领域，其中的进步往往来自数学，统计学，计算机科学，物理科学和工程以及其他学科的各个部分的想法的组合。新类型的（大型）数据已经出现，带来了前所未有的复杂性和挑战，需要新的思维方式。该研究培训小组（RTG）项目的目标是为本科生和研究生以及博士后研究员提供固有的跨学科培训，培养超越单个学科的技能。通过在联合收割机统计和计算建模与推理相结合的领域参与研究来培训学生，将为新一代科学家提供知识基础，他们将在这一令人兴奋的领域取得新的突破，并为私营和公共部门的研究和设计工作做出贡献。该项目将促进大型数据集建模和推理的原创研究。该计划将在任何特定时间涉及三名本科生、六名研究生和两名博士后研究员。本科部分将是一个综合的研究经验，包括一个研讨会课程，学生将学习和介绍有关关键主题的材料，并积极参与研究项目，这些主题付诸实践。每个学员将与至少两名RTG教师合作，以确保真正的跨学科培训体验。将开发一门新的“数据科学”课程，为跨越传统部门界限的受训人员提供教育。在整个日历年中，研究培训组将赞助高级课程和研究讲座，为研究生和博士后参与者的利益。该计划建立在一个充满活力的教师群体的优势和相互作用的基础上，具有概率模型和计算推理方法的一般领域的专业知识。 学员将受益于个性化的辅导活动和参与结构化的研究小组。这些活动的跨学科性质将导致新一代经过培训的研究人员能够提出新的方法和想法。将开发交叉培训的资源和工具，并向社区传播。接触数据科学和计算的现代方面将提高学员的专业发展。将加强统计与计算机科学之间的前沿研究。