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

NRT-DESE: UrbComp：建模、理解和推进城市人口的数据科学，预计到2030年，世界上每10个人中就有6个人生活在城市。为了支持不断涌入的公民，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具有很大的前景，因为随着我们的城市变得更加有线和网络化，大量的运营数据正在被收集。这项授予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跨领域的合作，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。该项目预计将培养60名博士生，其中包括18名受资助的学生，这些学生将为美国做出贡献。劳动力，从而支持我们的国家竞争力。受训者将在以下八个家庭部门之一攻读博士学位：计算机科学、数学、统计学、电气与计算机工程、人口健康科学、城市事务与规划、土木与环境工程以及社会学。具体的教育创新将包括：i)挂毯？课程以支持跨学科问题的早期编织，ii)强调负责任的数据科学的道德和社会问题，iii)通过跨学科项目团队和数据分析竞赛建立社区，以及iv)有效的沟通技巧，以促进与广泛的城市专业人士（即数据科学的最终消费者）的互动。学员将学习如何建立城市模型，开发大规模统计模型，以及使用数据挖掘和可视化技术来提出和回答问题。学员将使用弗吉尼亚理工大学？城市生活实验室（Urban Living Laboratory），通过实习、实习、数据挑战和黑客马拉松，与地区行业、当地市政府（弗吉尼亚州阿灵顿市）和当地卫生部门（弗吉尼亚州卫生部）开展合作。该项目将积极招募各种各样的学生来应对城市计算建模这一及时的挑战。培训模式将采用混合方法（定量和定性）进行评估，并针对五个重点领域（学生、社区、研究、项目、可扩展性和可持续性）进行评估。NSF研究培训（NRT）计划旨在鼓励开发和实施大胆的、新的、具有潜在变革性和可扩展的STEM研究生教育培训模式。通过创新、循证、适应不断变化的劳动力和研究需求的综合培训模式，培训项目致力于在高优先级跨学科研究领域对STEM研究生进行有效培训。

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.