NRT-DESE: UrbComp: Data Science for Modeling, Understanding, and Advancing Urban Populations

NRT-DESE：UrbComp：数据科学建模，理解和推进城市人口到2030年，世界上每十个人中就有六个预计生活在城市中。为了支持市民的持续涌入，城市必须准备好处理与城市人口有关的大规模问题，如公共卫生、有限能源的可持续利用、应急准备和社会稳定。“大数据”方法在解决这些问题方面有很大的希望，因为随着我们的城市变得更加有线和网络化，正在收集大量的运营数据。弗吉尼亚理工大学的NSF研究培训（NRT）奖将强调数据支持的科学和工程教育以及在一系列领域的合作，以培养博士生成为跨学科的数据科学家，帮助实现前所未有的城市化承诺。该实习预计培训多达六十（60）名博士生，包括十八（18）资助的学生，这将有助于美国？学生将在八个家庭部门之一攻读博士学位：计算机科学，数学，统计学，电气和计算机工程，人口健康科学，城市事务和规划，土木和环境工程，社会学。具体的教育创新将包括：（一）？挂毯？课程，以支持跨学科问题的早期编织，ii）重视道德和社会问题的负责任的数据科学，iii）通过跨学科项目团队和数据分析比赛的社区建设，以及iv）有效的沟通技巧，以促进与广泛的城市专业人士的互动，即，数据科学的最终消费者。学员将学习如何建立城市模型，开发大规模统计模型，并使用数据挖掘和可视化技术提出和回答问题。学员将使用弗吉尼亚理工大学？的城市生活实验室，使合作与区域产业，地方市政府（阿灵顿，弗吉尼亚州），和地方卫生部门（弗吉尼亚州卫生部）通过实习，实习，数据挑战，和黑客马拉松。 该项目将积极招募不同的学生骨干，以应对城市计算建模的这一及时挑战。 培训模式将使用混合方法（定量和定性）方法进行评估，并针对五个重点领域（学生，社区，研究，计划，可扩展性和可持续性）NSF研究培训（NRT）计划旨在鼓励开发和实施大胆的，新的，潜在的变革性和可扩展的STEM研究生教育培训模式。 该培训轨道致力于在高优先级的跨学科研究领域的STEM研究生的有效培训，通过全面的培训模式，是创新的，以证据为基础，并与不断变化的劳动力和研究需求保持一致。

NRT-DESE: UrbComp: Data Science for Modeling, Understanding, and Advancing Urban PopulationsBy the year 2030, six out of every ten people in the world are projected to live in a city. To support the continuing influx of citizens, cities must be prepared to handle large-scale issues concerning urban populations, such as public health, sustainable use of limited energy resources, emergency preparedness, and societal stability. "Big data" methods hold great promise in addressing such issues because a great amount of operational data is being gathered as our cities become more wired and networked. This NSF Research Traineeship (NRT) award to Virginia Tech will emphasize data-enabled science and engineering education and collaboration across a range of fields to prepare doctoral students to become interdisciplinary data scientists who can help realize the promises of unprecedented urbanization. The traineeship anticipates training up to sixty (60) doctoral students, including eighteen (18) funded students, which will contribute to the United States? workforce and thus support our national competitiveness.Trainees will pursue a PhD in one of eight home departments: computer science, mathematics, statistics, electrical and computer engineering, population health sciences, urban affairs and planning, civil and environmental engineering, and sociology. Specific educational innovations will include: i) a ?tapestry? curriculum to support early weaving of interdisciplinary issues, ii) emphasis on ethical and societal issues for responsible data science, iii) community building through interdisciplinary project teams and data analytics competitions, and iv) effective communication skills to facilitate interactions with a broad range of urban city professionals, i.e., the end consumers of data science. Trainees will learn how to model cities, develop large-scale statistical models, and use data mining and visualization technologies to pose and answer questions. Trainees will use Virginia Tech?s Urban Living Laboratory to enable collaborations with regional industries, local city governments (Arlington, VA), and local health departments (Virginia Department of Health) via internships, practicums, data challenges, and hackathons. The project will actively recruit a diverse cadre of students to tackle this timely challenge of urban computational modeling. The training model will be evaluated using a mixed method (quantitative and qualitative) approach and target five focus areas (students, community, research, program, scalability and sustainability).The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new, potentially transformative, and scalable models for STEM graduate education training. The Traineeship Track is dedicated to effective training of STEM graduate students in high priority interdisciplinary research areas, through the comprehensive traineeship model that is innovative, evidence-based, and aligned with changing workforce and research needs.