Luís M. A. Bettencourt
Classes at UChicago (2022-23)
This course is a grand tour of theory, general phenomena, emerging data, methods and policy applications that define a growing scientific, integrated understanding of cities and urbanization. Its objective is to provide students with an interdisciplinary knowledge base of urban phenomena and the capacity to conceive more systemic solutions to urban, local and global challenges.
The course follows the book "Introduction to Urban Science" (MIT Press, 2021). Roughly, every chapter of the book will be covered by 2 lectures. Themes include: worldwide urbanization and the challenge of sustainability, classical models from geography, economics and sociology, cities as complex networks and what they predict, variation and statistics of urban quantities, measuring and understanding diversity and productivity, neighborhoods and human development, cities in history and the origins of settlements, the structure and dynamics of systems of cities big and small (such as the US), the origins of (economic) growth and change, the emergence of institutions and their functional roles in connected, interdependent societies.
The main point of the course is for students to better grasp how these themes are interconnected and form a predictable, dynamical complex system that requires systemic interdisciplinary scientific approaches and solutions. We finish with an outlook of challenges ahead, including social justice, climate change, poverty and growth, and the role of cities in addressing them.
This course provides a graduate level introduction to concepts and research themes addressing our challenges of sustainable development across scales – with emphasis on cities but also nations and globally - and to pathways to solutions.
The course starts with a brief, empirically-based description of our present four interconnected crises of development – climate, biodiversity, equity and prosperity – and with a brief history of the fundamental concepts of sustainability, from early international reports in the 1980s to today’s Sustainable Development Goals and City-level comprehensive plans.
We will develop a fundamental understanding of sustainable development through the lens of the science of dynamical, coupled complex systems – physical, biological and social. This frame of reference will allow us to identify the roles of energy and information dynamics in defining sustainability across scales, in creating growth in both social and biological systems, and in elucidating present challenges and possible solutions.
Students will gain a working empirical understanding of urban science, energy systems, ecological systems, evolutionary dynamics and biodiversity, and the roots and consequences of inequality and economic growth in human societies.
The course is structured in 10 parts, each comprising of typically 2 lectures, including discussions. Students will be expected to gain a demonstrable understanding of fundamental concepts, exercise a systems-level scientific perspective across scales towards conceptualizing problems and solutions, and become proficient with mathematical models and data. The course will provide points of departure for student projects towards the Graduate Certificate on Urban Science and Sustainable Development at the University of Chicago.
co-taught with Matthias Steinrücken
In this course, students will learn fundamental concepts and models of population dynamics, selection and evolution. The course will emphasize the importance of population thinking, information, chance, competition and selection in finite populations in determining dynamical outcomes. We will show how genetic information can be modeled and transmitted under variation and selection across generations, providing a modern framework to understand mathematical theories of evolution by natural selection. This then leads to the central theme of the course, creating a general view of evolution as learning in populations, which establishes connections between ecology and evolution and computer science, economics and complex systems.