Associate Professor and Head
University of California Berkeley
By 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.