 |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | The 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. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6104) | Mo 09:00AM - 11:50AM | Rm 201, E4 | KAN, Ge Lin | 20 | 19 | 1 | 0 |
| VECTOR | [3-0-1:3] |
|---|---|
| DESCRIPTION | This 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). |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6101) | Tu 01:30PM - 04:20PM | Rm 228, E1 | LI, Chaosu | 15 | 8 | 7 | 0 | |
| LA01 (6102) | Tu 04:30PM - 05:20PM | Rm 228, E1 | LI, Chaosu | 15 | 8 | 7 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | The 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. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6105) | Fr 09:00AM - 11:50AM | Rm 223, W1 | ZHANG, Zhuoni | 15 | 7 | 8 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| PRE-REQUISITE | UGOD 5020 |
| DESCRIPTION | The 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. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6100) | Th 06:00PM - 08:50PM | Rm 201, W1 | YANG, Lin | 15 | 14 | 1 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | This 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. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6099) | Th 09:00AM - 11:50AM | Rm 233, W1 | YUEN, Cheuk Yi Kelvin | 15 | 7 | 8 | 0 |
| VECTOR | [2-1-0:3] |
|---|---|
| DESCRIPTION | Going 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. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6222) | We 09:00AM - 10:50AM | Rm 201, E4 | JIANG, BIN | 15 | 5 | 10 | 0 | |
| T01 (6223) | We 11:00AM - 11:50AM | Rm 201, E4 | JIANG, BIN | 15 | 5 | 10 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | This 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. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6221) | Fr 09:00AM - 11:50AM | Rm 202, E4 | GE, Zhigang | 15 | 4 | 11 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | This 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. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6220) | Mo 01:30PM - 04:20PM | Rm 202, E4 | YU, Hanchen | 15 | 5 | 10 | 0 |
| VECTOR | [1-3 credit(s)] |
|---|---|
| DESCRIPTION | Independent 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. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| R01 (6372) | TBA | TBA | TBA | 999 | 1 | 998 | 0 |
| VECTOR | [1 credit] |
|---|---|
| DESCRIPTION | Selected 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. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| T01 (6106) | We 01:30PM - 02:20PM | Rm 201, W4 | LI, Chaosu | 20 | 20 | 0 | 0 |
| DESCRIPTION | Master'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. |
|---|
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| R01 (6199) | TBA | TBA | TBA | 100 | 14 | 86 | 0 |
| DESCRIPTION | Original 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. |
|---|
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| R01 (6206) | TBA | TBA | TBA | 100 | 1 | 99 | 0 |