Postgraduate Courses
- UGOD 5009Inferential Statistics and OLS Regression[3-0-0:3]DescriptionThis course introduces fundamental knowledge and practice of basic statistics in quantitative social science research, with a focus on how quantitative methods are used to assemble, describe, and draw inferences from bodies of numerical data. The course serves as an additional foundation for more advanced methodology courses (such as UGOD 5020). The course covers two modules. The first is about descriptive statistics and fundamentals of statistical inference. Topics include frequency distribution, probability theory, random variable and probability distributions, estimation, hypothesis testing, t-test, Analysis of Variance (ANOVA), and contingency table analysis. The second is about linear regression techniques, which are widely used in social science research. The course materials are explored through the analyses of real data sets using STATA.
- UGOD 5010Science of Cities[3-0-0:3]DescriptionThe course aims to provide a comprehensive understanding of the city and the system of cities, the challenges faced by cities, especially the rapidly-developing large cities, and the key tools for interventions in response to critical pressures linked to economic development, urbanization, globalization, migration, social inclusion, climate change, resource efficiency, technology etc.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Demonstrate an understanding of the intellectual history of urban planning and designs.
- 2.Analyze selected cities as the cases of planning and designs.
- 3.Develop a new notion of cities as systems of networks and flows instead of places in space.
- 4.Apply new tools to understand different aspects of city structure.
- 5.Compare design and decision-making models that predict interactions and flow in future cities.
- 6.Write Report on Case Study.
- UGOD 5011Applied Numerical Methods[3-0-0:3]Background1. College-level calculus and linear algebra is required. 2. Some knowledge on programming languages (such as Matlab, Julia, Python, C, C++, Fortran etc.) is preferred, but not required. The course will introduce some basics on Matlab or Julia.DescriptionThis course introduces computational methods that are commonly used in social science (e.g. economics, finance etc.) and other disciplines (e.g. engineering). They are to solve/handle linear and non-linear equations, optimizations, numerical integration and differentiation, function approximation, dynamic models (discrete and continuous), etc. Classes will be interactive so that students can understand both theory and practice. Homework is designed for students to be familiar with those techniques.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Be familiar with one scientific programming language proficiently, e.g. Matlab, Julia, etc.
- 2.Understand various numerical methods.
- 3.Identify proper numerical methods for solving specific problems.
- 4.Apply numerical methods to solve problems on computer.
- 5.Combine methods learned or design new methods to solve problems in own research using a programming language.
- UGOD 5020Quantitative Social Science[3-0-0:3]BackgroundFundamental knowledge in probability and statistics, and software packagesDescriptionThis course builds on the knowledge of the linear regression models to introduce students advanced statistical methods to analyze survey, administrative and other types of data of interest to quantitative social scientists. The introduction of statistical methods is integrated into research contexts and designs from a holistic framework and bridge quantitative social science and computational social science (data science). Topics include measurement, prediction, causal inference, natural experiment and program evaluation (difference-in-differences, panel data, instrumental variables, regression discontinuity), applied to both survey and big data.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Apply statistical methods when the assumptions of classical linear regression are violated.
- 2.Understand the concept of causality and research designs to establish causal relationship.
- 3.Utilize some standard methods in causal inferences with observational data.
- 4.Apply basic tools to analyze different types of data, including big data.
- 5.Perform essential techniques to analyze big social data.
- 6.Write a research report on findings.
- UGOD 5030GIS and Spatial Analysis[3-0-1:3]DescriptionThis course introduces students to the basic concepts and methods in Geographic Information System (GIS), and their applications in urban design and governance, environmental and infrastructure sustainability, and smart city management. This course integrates social science and informatics perspectives, and is suitable for students with various backgrounds. In addition to learning traditional GIS data, spatial analytical techniques, and GIS software, this course also develops skills of manipulating spatially detailed urban sensing Big Data (about urban activities, environmental qualities, and mobility patterns).Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Demonstrate an understanding of common GIS concepts and spatial data models.
- 2.Manipulate tabular and spatial data to produce intelligible graphics.
- 3.Apply major extensions and data analysis functions in ArcGIS for problem solving.
- 4.Perform basic (satellite) image processing tasks.
- 5.Perform basic hot spot and other spatial statistical analysis.
- 6.Write report on findings.
- UGOD 5040Urban Data Acquisition and Analysis[3-0-0:3]DescriptionThe course introduces students to different methods of collecting data in the social sciences for urban analysis, focusing on sampling surveys designs and analysis in urban settings. Since alternative data sources (e.g., passive measurement, social media and administrative data) become increasingly available in recent years, the course will also cover other modes of data acquisitions such as using new technology on wearables, sensors, and apps in urban research settings, and exploration of cutting edge methods for collecting and analyzing web data, and how they can be used in combination with traditional survey data.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Demonstrate an understanding of the basic ideas, concepts and principles of probability sampling from an applied perspective.
- 2.Identify and appropriately apply sampling techniques to survey design problems.
- 3.Identify the pros and cons for each of data collection methods, the implication of survey design decisions on data quality.
- 4.Test new technology on wearables, sensors, and apps, and methods for collecting and analyzing web data.
- 5.Perform statistical analysis of complex sample survey data, census data, or other data, and integrated data.
- 6.Integrate data from different sources to design a research project.
- UGOD 5050Cities and Society[3-0-0:3]DescriptionThe course looks at some of the major drivers of urban inequality and poverty, and the key actions that cities are taking to reduce urban inequalities through urban design, infrastructure and policy. Students are introduced with tools to analyze the socio-demographic profile of households and neighborhoods/communities and their relation to spatial distribution and clustering in cities of both the developing and the developed world. A particular emphasis is placed on identifying spatial strategies that can alleviate the concentration of urban poverty and inequality to enhance urban social cohesion by optimizing access to jobs, housing, education, health, public space, transport and community infrastructure.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Describe the major issues related to cities and society.
- 2.Explain the major drives of urban inequality and poverty issues in different countries.
- 3.Apply quantitative approach to analyze the socio-demographic profile of households and neighborhoods in cities.
- 4.Identify an urban issue and conduct independent research and present findings.
- UGOD 5060Urban Data Analytics[3-0-0:3]Prerequisite(s)UGOD 5030Corequisite(s)UGOD 5040DescriptionOver recent years, the way data are used to understand urban system has changed dramatically. Cities are constantly adapting to incorporate new technology, and urban social life increasingly occurs in digital environments and continues to be mediated by digital systems, producing urban data not only in volume but also in form (i.e. text, image, audio, and video). This course delves into the challenges and opportunities of using new and emerging forms of data to study cities.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Describe the opportunities and challenges created by digital big data.
- 2.Extract and manage urban big data.
- 3.Utilize basic graphic tools to visualize and analyze exemplary big data.
- 4.Perform basic text and image processing tasks.
- 5.Demonstrate an understanding of the basic knowledge of Agent-based Modeling.
- 6.Critically evaluate research that use big data and computational methods.
- UGOD 5070Urban Planning and Design[3-0-0:3]DescriptionThis course cuts across all major fields within urban planning and design and introduces the major theories, models, and methodological approaches that urban planners and policy makers use for urban planning and design. This course also critically examines the current practice of urban planning and governance in China at various geographical scales.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Identify and assess the major theories and methodological approaches of urban planning and design.
- 2.Understand descriptive and prescriptive approaches for examining urban form and function.
- 3.Have a broad understanding of the major epochs in urban planning and the ways they attempted to shape the design and function of cities.
- 4.Evaluate current policy and planning challenges affecting Chinese cities.
- 5.Formulate questions in the field of urban planning and design for in-depth exploration.
- 6.Use a big data lens to examine planning and design issues and solutions.
- UGOD 5080Economic Analysis of Cities and the Environment[3-0-0:3]BackgroundKnowledge in basic statisticsDescriptionThis interdisciplinary course will provide students a systematic framework of the interplay between urban growth and the environment from economic perspectives.By walking them through the state-of-the-art research in urban and environmental economic studies from both developing and developed countries., it will familiarize students with popular empirical strategies in applied economics and relevant fields to solve the most pressing environmental challenges accompanied with fast-urbanized cities. By the end of the class, students will be equipped with toolkits to evaluate policy questions in transportation, pollution and health, climate change, energy transition, housing market, and environmental justice.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Improve critical, innovative, and independent economic thinking skills.
- 2.Compare and contrast the state-of-the-art research in urban and environmental studies.
- 3.Learn the econometric approaches commonly used in empirical studies.
- 4.Understand and critically assess the urban and environmental challenges especially in China.
- 5.Expand their toolkits on urban and environmental policy evaluation.
- 6.Effectively conduct oral, written, and visual communication.
- UGOD 5090Urban Sustainability[3-0-0:3]DescriptionThis course provides a road map for examining the sustainability of cities through perspectives and approaches in urban governance and design. Drawing from an interdisciplinary literature, we will explore the following major themes in the context of urban sustainability: theories and assessment tools of urban sustainability, land use and transportation, urban design, energy and climate change, food and health, governance, and social ecology.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Understand the debates over what constitutes “urban sustainability” and the complexities in measuring it.
- 2.Discuss the current literature on the three components of sustainability from an urban development perspective.
- 3.Explore what “actually-existing sustainability” may look like in urban governance and design practice.
- 4.Apply assessment tools for each of the components of sustainability for a project, plan, program or policy.
- 5.Write a research proposal on urban sustainability.
- UGOD 5100Public Finance and Taxation[3-0-0:3]BackgroundKnowledge in calculus, microeconomic theory, and basic statistical methods such as linear regressionsDescriptionPublic finance refers to that government uses (tax) policy tools to finance its spending on various areas. It is thus an important aspect of urban governance and public policy. This course introduces some classical results of the taxation theory as well as recent developments on the empirical side of tax policy. The topics include labor income tax, business taxes (such as corporate income tax and dividend tax), savings tax, inheritance tax etc. We also talk about urban (or local) tax policy and its effects on local economy.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Understand the efficiency cost of taxation.
- 2.Identify the benefits and costs of a change in certain tax policy.
- 3.Know various types of tax and their role in public finance.
- 4.Understand the concept of causality and research designs to establish causal relationship.
- 5.Apply statistical or theoretical methods to conduct independent tax policy analysis.
- 6.Write a research report on tax policy.
- UGOD 5101Empirical Methods for Urban Research[3-0-0:3]Prerequisite(s)UGOD 5020BackgroundKnowledge in econometrics (regression analysis and matrix algebra); basic programming skillsDescriptionThe course introduces students to basic practices and tools that will enhance their ability to conduct empirical research and analysis in applied economics and relevant disciplines in a data-rich world. By the end of the course, the students will be proficient in a variety of data management, visualization, and quantitative techniques necessary to efficiently conduct independent research. The course format is “hands-on”, and students will conduct most of their work on their personal computers using R and RStudio.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Apply reproducible R programming in the context of urban science and relevant disciplines.
- 2.Gather, manipulate, and visualize various types of data effectively for research purposes.
- 3.Analyze different types of data.
- 4.Employ simulation and resampling methods in applied research.
- 5.Conduct independent academic research.
- 6.Effectively conduct oral, and visual communication.
- UGOD 5102Life Course Research[3-0-0:3]Corequisite(s)UGOD 5020BackgroundGood knowledge in probability and statistics; be relatively familiar with software packages (such as R)DescriptionLife course analysis provides a framework to understand many topics across different disciplines, such as family and fertility, migration, child development and education, paid and unpaid work, and wellbeing, heath and ageing. Those decisions or outcomes of individuals are a result of how individuals interact with each other in the specific culture and historical context that is shaped by our city, policy, and environment. This course will introduce the field of life course research and basic concepts, cover a range of established research topics, with a focus on the theoretical and substantive research in addition to the translation of these research questions into empirical applications. Another central goal will be the introduction of event history techniques and sequence analysis. Students will learn how social survey data, administrative data, and geographic information are synthesized to answer those research questions.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Name, define, compare and give concrete form to the central theories, concepts and methodological approaches within life course research.
- 2.Name and critically assess the research design, theoretical approach, and methodology of several life course studies.
- 3.Identify different types of event history analysis applications and when to apply them.
- 4.Explain the application of sequence analysis and when to use them.
- 5.Develop a deep understanding in one of the life course research topics with a detailed literature review and critically identify the research gap with proper research design to tackle this gap.
- 6.Undertake an event history analysis or sequence analysis using the computer program R and interpret and present the results of this analysis in the form of a research paper.
- UGOD 5103Economics of the Urban Labor Market[3-0-0:3]BackgroundGraduate level training in EconomicsDescriptionThis course studies theoretical and empirical issues in economics of the urban labor market. Topics include theories and empirics of human capital in an urban area, labor search and matching, unemployment, and their applications. The modeling and empirical tools covered allow students to analyze various public policy issues facing contemporary urban governance and design, including minimum wage and unemployment benefits. Evidence from China’s urban labor market will be discussed along the course.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Explain the modern theories of employment and the urban labor market.
- 2.Analyze contemporary public policy issues concerning the labor market.
- 3.Describe and critically assess the literature on employment and the urban labor market.
- 4.Present and communicate recent research on employment and the urban labor market.
- 5.Write an original research paper on employment and the urban labor market.
- UGOD 5104Visualization for Urban Informatics[2-1-0:3]DescriptionAs urban areas continue to grow and become more complex, the amount of data generated by cities has increased exponentially. This presents significant challenges in terms of managing and interpreting urban data to address various urban issues or challenges. In response to this, our course is designed to equip students with the skills needed to visualize urban data, enabling them to gain a better understanding of city structure and dynamics. Moreover, this course will provide students with the knowledge and tools needed to conduct sustainable planning and design towards a sustainable society.
- UGOD 5105Urban Complexity Analysis and Modeling[2-1-0:3]DescriptionGoing beyond conventional GIS and geospatial analysis, this course delves into the realm of complexity-science methods, including fractal geometry, power law statistics, space syntax, complex networks, scaling hierarchy, and cellular automata. By embracing pivotal concepts like "natural streets" and "natural cities," alongside the tools such as Axwoman and head/tail breaks, students will explore city structure and dynamics from a complexity-science perspective. These concepts, methods and tools will be applied to open-access geospatial big data such as OpenStreetMap, nighttime imagery, and location-based social media data for revealing insights into cities for better transforming modern cities towards a sustainable planet.
- UGOD 5110Quantitative Macroeconomics[3-0-0:3]BackgroundCollege-level calculus is required.DescriptionThis course introduces the framework of modern macroeconomics and then conducts policy analysis based on it. We start from the classic economic growth model developed by Solow, then gradually add other features to the model to make it better explain the real world. These features include a life-cycle structure, income risks, incomplete credit markets, the role of government, etc. After building up the framework, we study its policy implications with a focus on fiscal policy.
- UGOD 5112Machine Learning in Remote Sensing[3-0-0:3]BackgroundPreferably have background in programming (python) and image analysis.DescriptionThis course focuses on applying machine and deep learning methods for remote sensing and covers a variety of practical applications of remote sensing image processing in complex urban environments. Through a mixture of theoretical and hands-on sessions, students will gain a deeper understanding of advanced image analysis methods and will be able to apply new concepts and approaches to enhance their problem-solving abilities in the interdisciplinary field using multi-source geo-information.
- UGOD 5120Entrepreneurship and Modern Economy[3-0-0:3]DescriptionThis course studies the role of entrepreneurship in the modern economy. Theories and empirics of startups as a driver of job creation, growth and development, and business cycles will be discussed. The course also examines the effects on venture growth, wealth accumulation, inequality, and innovation in a society. Finally, examples of entrepreneurial public policies will be demonstrated and assessed.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Understand the theories and empirics of entrepreneurship in relation to the modern economy.
- 2.Analyze contemporary public policy issues concerning entrepreneurship and the impact on the society.
- 3.Understand and critically assess the literature on entrepreneurship and the modern economy.
- 4.Present and communicate recent research on entrepreneurship and the modern economy.
- 5.Write an original research paper on entrepreneurship and the modern economy by going through the original research process covered in this course.
- UGOD 5200Applied Demography[3-0-0:3]DescriptionThis course provides an introduction to applied demography, the practical applications of demographic analysis. Students will learn about the basic principles of demographic analysis, including measures of population size, composition, and distribution, as well as methods for analyzing demographic changes and trends over time. Through hands-on instruction, students will also learn the applications of these techniques to real-world situations, such as policy-making, urban planning, and marketing.
- UGOD 5201Spatial Econometrics for Urban Analysis[3-0-0:3]DescriptionThis course combines spatial analysis and econometrics to understand and analyze urban phenomena. It equips students with theoretical foundations and practical tools for understanding and analyzing urban data. The course covers spatial autocorrelation, heterogeneity, and various spatial econometric models. It also explores real-world applications in the fields of urban economics, regional science, and environmental economics.
- UGOD 5300Introduction to GeoAI[3-0-0:3]DescriptionGeoAI is an interdisciplinary field of Geography/GIScience and Artificial Intelligence (AI), aiming to harness AI techniques to address diverse environmental and societal challenges related to geospatial domain. The course will introduce fundamental concepts, methods, and tools of GeoAI, and show how emerging urban spatio-temporal data and GeoAI technologies can be applied to address urban challenges, improve urban governance and management, and enhance the overall livability and sustainability of cities.
- UGOD 5700Categorical Data Analysis[3-0-0:3]Prerequisite(s)UGOD 5020DescriptionThis course focuses on statistical analysis of data that are categorical or non-continuous in nature. The contents cover a family of statistical models that deal with binary data, discrete data, count data, and categorical data with special features such as truncation and overdispersion. The course gives emphasis to modeling techniques and hands-on applications to empirical research.
- UGOD 6000Independent Study[1-3 credit(s)]DescriptionIndependent study in a designated subject under direct guidance of a faculty member to provide students the advanced knowledge and research skill sets on urban governance and design related topics. Required readings, tutorial discussions, and submission of report(s) will be used for assessment. The course may be repeated for credit if different topics are studied.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Demonstrate mastery of the knowledge and skills in the selected topics related to Urban Governance and Design.
- 2.Apply an interdisciplinary approach in examining the selected topics.
- 3.Critically evaluate different aspects of the selected topics.
- 4.Communicate findings effectively in written reports.
- UGOD 6000AIndependent Study[1-3 credit(s)]DescriptionIndependent study in a designated subject under direct guidance of a faculty member to provide students the advanced knowledge and research skill sets on urban governance and design related topics. Required readings, tutorial discussions, and submission of report(s) will be used for assessment. The course may be repeated for credit if different topics are studied.
- UGOD 6100Special Topics in Urban Governance and Design[1-3 credits]DescriptionThis course covers emerging topics of Urban Governance and Design concerns not covered in the present curriculum. The course aims to provide students with the advanced knowledge and research skill sets on an Urban Governance and Design topic. Required readings, tutorial discussions, and submission of report(s) will be used for assessment. The course may be repeated for credit if different topics are studied. May be graded by letter or P/F for different offerings.
- UGOD 6101UGOD Program Seminar I[0 credit]DescriptionAdvanced seminar series presented by postgraduate students, faculty, and guest speakers on selected topics in urban governance and design. This course is offered once a year. Graded P or F.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Apply essential skills in communicating research results.
- 2.Use appropriate software or technologies to deliver an effective presentation.
- 3.Communicate effectively in professional settings.
- 4.Interact with guest lecturers.
- UGOD 6102UGOD Program Seminar II[1 credit]DescriptionSelected topics in hands-on data analyses, such as statistical software (R, STATA, or SAS), data management, and visualization, will be introduced to students in urban governance and design for their research. The course is offered once a year. Graded P or F.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Apply basic skills in statistical software.
- 2.Demonstrate hands-on skills in data management.
- 3.Apply fundamental knowledge of integrating data from different sources.
- 4.Utilize appropriate tools to visualize the data.
- 5.Apply the skills to a project on data analysis with application to UGOD topics in the real world.
- UGOD 6990MPhil Thesis ResearchDescriptionMaster's thesis research supervised by co-advisors from different disciplines. A successful defense of the thesis leads to the grade Pass. No course credit is assigned.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Design, develop and conduct cross-disciplinary research in Urban Governance & Design.
- 2.Communicate research findings effectively in written and oral presentations.
- UGOD 7990Doctoral Thesis ResearchDescriptionOriginal and independent doctoral thesis research supervised by co-advisors from different disciplines. A successful defense of the thesis leads to the grade Pass. No course credit is assigned.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Design, develop and conduct cross-disciplinary research in Urban Governance & Design.
- 2.Communicate research findings effectively in written and oral presentations.