RTG: Cross-Training in Statistics and Computer Science

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于数学、统计学、计算机科学、物理科学、工程以及其他学科的不同部分的思想的结合。新类型的(大型)数据已经出现，呈现出前所未有的复杂性和挑战，需要新的思维方式。这个研究培训小组(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内在的跨学科培训，发展超越个别学科的技能。通过将统计和计算建模与推理相结合的领域的研究参与培训学生，将为准备在这一令人兴奋的领域取得新突破的新一代科学家提供智力基础，并为私营和公共部门的研究和设计努力做出贡献。该项目将催化对大数据集的建模和推理的原创性研究。该项目在任何时候都将涉及三名本科生、六名研究生和两名博士后研究员。本科生的部分将是综合研究体验，包括研讨会课程，学生将在其中学习和介绍关键主题的材料，并积极参与研究项目，这些主题将在实践中得到实践。每名学员将与至少两名RTG教职员工合作，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，为学员提供跨越传统系界限的教育。在整个历年，研究培训小组将为研究生和博士后学员举办高级课程和研究讲座。该计划建立在一个充满活力的教职员工群体的优势和互动的基础上，拥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指导活动和参加有组织的研究小组。这些活动的跨学科性质将导致新一代研究人员接受培训，能够产生新的方法和想法。将开发用于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促进学员的专业发展。将加强统计学与计算机科学之间的前沿研究。

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.