UGOD - HKUST Class Schedule & Quota

COURSE INFO

DESCRIPTION	This 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.

DESCRIPTION

This 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 5009 - Inferential Statistics and OLS Regression (3 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L01 (6452)	Mo 03:00PM - 05:50PM	Rm 201, W1	ZHANG, Zhuoni	15	14	1	0

COURSE INFO

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.

UGOD 5010 - Science of Cities (3 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L01 (6453)	Mo 09:00AM - 11:50AM	Rm 222, W1	KAN, Ge Lin XIONG, Wanru YANG, Lin ZHANG, Haoxiang	30	18	12	0

COURSE INFO

DESCRIPTION	This 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.

DESCRIPTION

This 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.

UGOD 5020 - Quantitative Social Science (3 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L01 (6454)	Th 01:30PM - 04:20PM	Rm 239, E1	YUEN, Cheuk Yi Kelvin	30	9	21	0

COURSE INFO

DESCRIPTION	The course introduces students to a comprehensive understanding of how to leverage various types of data to answer critical questions in the social sciences for urban analysis. We will explore fundamental concepts and methodologies in social and population data collection, including, sampling surveys designs and analysis. Since alternative data sources (e.g., passive measurement, social media and simulated data generated by large language models (LLMs) become increasingly available, the course will explore cutting edge methods for collecting and analyzing data, and how they can be used in combination with traditional survey data.

DESCRIPTION

The course introduces students to a comprehensive understanding of how to leverage various types of data to answer critical questions in the social sciences for urban analysis. We will explore fundamental concepts and methodologies in social and population data collection, including, sampling surveys designs and analysis. Since alternative data sources (e.g., passive measurement, social media and simulated data generated by large language models (LLMs) become increasingly available, the course will explore cutting edge methods for collecting and analyzing data, and how they can be used in combination with traditional survey data.

UGOD 5040 - Social Data Acquisition and Analysis (3 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L01 (6455)	TuTh 01:30PM - 02:50PM	Rm 201, W4	ZHOU, Muzhi	15	14	1	0

COURSE INFO

PRE-REQUISITE	UGOD 5030
CO-REQUISITE	UGOD 5040
DESCRIPTION	Over recent years, especially with the rise of Artificial Intelligence (AI), 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.

UGOD 5060 - Urban Data Analytics (3 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L01 (6461)	Th 09:00AM - 11:50AM	Rm 101, W2	JIANG, Na	15	0	15	0

COURSE INFO

PREVIOUS CODE	UGOD 6100A
DESCRIPTION	This course examines human travel behaviors and mobility patterns across spatial and temporal dimensions, with a strong emphasis on the complex interactions between individual behavior and the urban environment. The course offers an interdisciplinary introduction to building AI-driven agent frameworks to understand, model, and simulate human mobility, and explore how urban environment, socio-economic factors, and other constraints shape individual and collective mobility patterns. Through theoretical frameworks, advanced analytical methods, and empirical tools (e.g., GPS tracking, mobile data), the course decodes how humans adapt their spatio-temporal travel behavior to evolving urban landscapes. Case studies on commuting efficiency, activity scheduling, accessibility disparities, and disaster resilience, and emerging trends such as shared mobility systems and virtual spaces will be covered. Through hands-on modeling and industry-linked case studies, students will learn to build and evaluate AI-agent systems for human mobility and urban studies.

PREVIOUS CODE

UGOD 6100A

DESCRIPTION

This course examines human travel behaviors and mobility patterns across spatial and temporal dimensions, with a strong emphasis on the complex interactions between individual behavior and the urban environment. The course offers an interdisciplinary introduction to building AI-driven agent frameworks to understand, model, and simulate human mobility, and explore how urban environment, socio-economic factors, and other constraints shape individual and collective mobility patterns. Through theoretical frameworks, advanced analytical methods, and empirical tools (e.g., GPS tracking, mobile data), the course decodes how humans adapt their spatio-temporal travel behavior to evolving urban landscapes. Case studies on commuting efficiency, activity scheduling, accessibility disparities, and disaster resilience, and emerging trends such as shared mobility systems and virtual spaces will be covered. Through hands-on modeling and industry-linked case studies, students will learn to build and evaluate AI-agent systems for human mobility and urban studies.

UGOD 5066 - AI Agents for Human Mobility (3 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L01 (6539)	Tu 06:00PM - 08:50PM	Rm 103, E1	LI, Qiumeng	15	15	0	0

COURSE INFO

DESCRIPTION	This 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.

UGOD 5070 - Urban Planning and Design (3 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L01 (6464)	We 06:00PM - 08:50PM	Rm 201, E4	LI, Chaosu	17	17	0	0

COURSE INFO

EXCLUSION	CNCC 5840
CO-LIST WITH	CNCC 5840
DESCRIPTION	This 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.

UGOD 5080 - Economic Analysis of Cities and the Environment (3 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L01 (6469)	We 01:30PM - 04:20PM	Rm 102, W1	YANG, Lin	15	7	8	0

COURSE INFO

PRE-REQUISITE	UGOD 5020 Quantitative Social Science
PREVIOUS CODE	UGOD 6100D
DESCRIPTION	This course examines the economic forces driving urban development, combining theoretical frameworks with real-world policy challenges. Key topics include agglomeration and systems of cities, urban growth and its spatial forms (sprawl vs. densification), land use patterns (zoning and growth control), transportation (road network, transit, and congestion), housing (affordability, informality, and renewal), and the role of local governments. The course will also highlight recent disruptive forces such as remote work, autonomous vehicles, platform economy, and digital governance in different urban contexts. Through case studies in policy analysis, students will become familiar with classical causal inference research design and learn to leverage emerging data sources, such as AIpowered textual repositories, satellite and street imagery, sensors, GPS, and social media.

UGOD 5140 - Urban Economics and Policy Analysis (3 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L01 (6501)	Fr 01:30PM - 04:20PM	Rm 201, W1	WANG, Binzhe	15	6	9	0

COURSE INFO

PREVIOUS CODE	UGOD 6100E
DESCRIPTION	This course explores how big data transforms our understanding and modeling of urban systems. Students will develop computational thinking, creative problem framing, and the ability to integrate heterogeneous datasets to address typical urban challenges. Emphasis is placed on data-driven modeling, data thinking, and innovative applications across mobility, health, social sensing, and urban planning.

PREVIOUS CODE

UGOD 6100E

DESCRIPTION

This course explores how big data transforms our understanding and modeling of urban systems. Students will develop computational thinking, creative problem framing, and the ability to integrate heterogeneous datasets to address typical urban challenges. Emphasis is placed on data-driven modeling, data thinking, and innovative applications across mobility, health, social sensing, and urban planning.

UGOD 5150 - Big Data for Urban Modeling (3 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L01 (6502)	Mo 01:30PM - 04:20PM	Rm 202, W2	YUE, Yang	15	15	0	0

COURSE INFO

DESCRIPTION	GeoAI 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.

DESCRIPTION

GeoAI 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 5300 - Introduction to GeoAI (3 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L01 (6503)	Mo 06:00PM - 08:50PM	Rm 103, E1	CAO, Rui	18	17	1	0

COURSE INFO

PREVIOUS CODE	UGOD 6100B
DESCRIPTION	This course familiarizes students with modeling urban systems using Network Science and Agent-Based Modeling (ABM). They will design and implement simulations to study urban phenomena such as human dynamics and urban development. Through ABM, students will create computational models of individual agents interacting within urban environments to explore emergent patterns and complex system behaviors. Through Network Science, students will learn to represent urban systems as graphs and apply machine-learning techniques to analyze networks like street layouts and mobility patterns.

PREVIOUS CODE

UGOD 6100B

DESCRIPTION

This course familiarizes students with modeling urban systems using Network Science and Agent-Based Modeling (ABM). They will design and implement simulations to study urban phenomena such as human dynamics and urban development. Through ABM, students will create computational models of individual agents interacting within urban environments to explore emergent patterns and complex system behaviors. Through Network Science, students will learn to represent urban systems as graphs and apply machine-learning techniques to analyze networks like street layouts and mobility patterns.

UGOD 5555 - Urban Simulation with Network Science and Agent-Based Modeling (3 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L01 (6513)	Th 06:30PM - 09:20PM	Rm 103, E1	WU, Cai ZHANG, Haoxiang	15	13	2	0

COURSE INFO

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.

UGOD 6000B - Independent Study (1 unit)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
R01 (6929)	TBA	No room required	TBA	20	1	19	0

COURSE INFO

DESCRIPTION	Digital twins are transforming how we represent, understand, and manage cities, enabling new forms of analysis, automation, and decision support across building and urban scales. With the rapid growth of large-scale 3D information assets, e.g., meshes, point clouds, and semantic models, digital twin cities introduce critical challenges in information organization, integration, management, and scalable intelligence. This course focuses on 3D information technologies for digital twin cities, emphasizing how heterogeneous information from Building Information Modeling (BIM), City Information Modeling (CIM), and Internet of Things (IOT) are structured, integrated, and orchestrated within scalable data infrastructures and platforms. Students will explore the fundamental methods for organizing, managing, and interacting with large-scale urban information, including semantic representation, information integration, indexing, visualization, and real-time information management to support dynamic urban systems. Building on this foundation, the course introduces AI-driven urban applications, including machine learning, computer vision, and large language model agents, as new paradigms for interpreting, querying, and interacting with digital twins. By integrating information modeling, visualization, analytics, and AI, the course demonstrates how digital twins can support scalable intelligence and informed decision-making in real-world applications such as infrastructure management, urban planning, housing, and urban health.

DESCRIPTION

Digital twins are transforming how we represent, understand, and manage cities, enabling new forms of analysis, automation, and decision support across building and urban scales. With the rapid growth of large-scale 3D information assets, e.g., meshes, point clouds, and semantic models, digital twin cities introduce critical challenges in information organization, integration, management, and scalable intelligence. This course focuses on 3D information technologies for digital twin cities, emphasizing how heterogeneous information from Building Information Modeling (BIM), City Information Modeling (CIM), and Internet of Things (IOT) are structured, integrated, and orchestrated within scalable data infrastructures and platforms. Students will explore the fundamental methods for organizing, managing, and interacting with large-scale urban information, including semantic representation, information integration, indexing, visualization, and real-time information management to support dynamic urban systems. Building on this foundation, the course introduces AI-driven urban applications, including machine learning, computer vision, and large language model agents, as new paradigms for interpreting, querying, and interacting with digital twins. By integrating information modeling, visualization, analytics, and AI, the course demonstrates how digital twins can support scalable intelligence and informed decision-making in real-world applications such as infrastructure management, urban planning, housing, and urban health.

UGOD 6100F - 3D Information Technologies for Digital Twin Cities (3 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L01 (6736)	Fr 03:00PM - 05:50PM	Rm 202, E1	LI, Maosu	15	15	0	0

COURSE INFO

DESCRIPTION	Cities today are continuously documented through diverse forms of user-generated content, ranging from geotagged social media and GPS signals to crowdsourced street-level imagery and platform-based services. These digital traces offer new ways of seeing urban environments beyond physical spaces, but as lived, perceived, and experienced places shaped by human activities and interactions. This course explores how cities can be “sensed”, moving beyond static representations to reconstruct dynamic spatial opportunities and human-environment interactions under uncertainty. Students will be introduced to core theories of Social Sensing and learn data paradigms and analytical methods that support urban analysis. A series of workshop will provide students with hands-on experience in analyzing real-world problems including mobility, accessibility, environmental exposure, and inequality, while developing independent research skills and critical awarene

DESCRIPTION

Cities today are continuously documented through diverse forms of user-generated content, ranging from geotagged social media and GPS signals to crowdsourced street-level imagery and platform-based services. These digital traces offer new ways of seeing urban environments beyond physical spaces, but as lived, perceived, and experienced places shaped by human activities and interactions. This course explores how cities can be “sensed”, moving beyond static representations to reconstruct dynamic spatial opportunities and human-environment interactions under uncertainty. Students will be introduced to core theories of Social Sensing and learn data paradigms and analytical methods that support urban analysis. A series of workshop will provide students with hands-on experience in analyzing real-world problems including mobility, accessibility, environmental exposure, and inequality, while developing independent research skills and critical awarene

UGOD 6100J - Social Sensing and Digital Traces: From Human Experience to Urban Intelligence (3 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L01 (6737)	Tu 06:30PM - 09:20PM	Rm 105, W3	JANG, KEEMOON WANG, Jianying	15	15	0	0

COURSE INFO

DESCRIPTION	This course focuses on how AI can be leveraged to address complex societal and urban challenges in domains such as smart cities, public health, and social development. The course bridges computational thinking with societal analysis such as risk analysis and stakeholder-centered design. Through case studies and collaborative projects, students will evaluate existing AI systems and/or propose innovative, socially beneficial solutions.

DESCRIPTION

This course focuses on how AI can be leveraged to address complex societal and urban challenges in domains such as smart cities, public health, and social development. The course bridges computational thinking with societal analysis such as risk analysis and stakeholder-centered design. Through case studies and collaborative projects, students will evaluate existing AI systems and/or propose innovative, socially beneficial solutions.

UGOD 6100K - AI for Social Good (3 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L01 (6899)	Tu 09:00AM - 10:50AM	Rm 202, E4	XUE, Hao	15	13	2	0
L01 (6899)	Tu 11:00AM - 11:50AM	Rm 202, E4	XUE, Hao	15	13	2	0

COURSE INFO

DESCRIPTION	This course examines how AI-enabled decision systems are governed in urban domains such as transport, housing, labor, and public services, and how governance choices shape access, accountability, and the distribution of risks and resources. Students gain working literacy in core AI concepts and common algorithmic system types used in digital society, and learn to apply risk-based governance and accountability instruments across the system lifecycle (Govern–Map–Measure–Manage), including algorithmic impact assessments, transparency registers, audit and continuous monitoring requirements, and data-sharing and privacy frameworks, to ensure legality, reliability, and public value in real policy contexts. This course also provides an initial, case-based lens for students to engage more deeply with sociological explanations in the subsequent course UGOD 5050 Cities and Society in spring term.

DESCRIPTION

This course examines how AI-enabled decision systems are governed in urban domains such as transport, housing, labor, and public services, and how governance choices shape access, accountability, and the distribution of risks and resources. Students gain working literacy in core AI concepts and common algorithmic system types used in digital society, and learn to apply risk-based governance and accountability instruments across the system lifecycle (Govern–Map–Measure–Manage), including algorithmic impact assessments, transparency registers, audit and continuous monitoring requirements, and data-sharing and privacy frameworks, to ensure legality, reliability, and public value in real policy contexts. This course also provides an initial, case-based lens for students to engage more deeply with sociological explanations in the subsequent course UGOD 5050 Cities and Society in spring term.

UGOD 6100L - AI Society and Urban Governance (3 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L01 (6940)	We 01:30PM - 04:20PM	Rm 105, E3	QIAO, Si	15	9	6	0

COURSE INFO

DESCRIPTION	Advanced 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.

UGOD 6101 - UGOD Program Seminar I (0 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
T01 (6515)	We 02:30PM - 03:20PM	Rm 102, E1	YANG, Xiuqi	30	30	0	0

COURSE INFO

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.

UGOD 6990 - MPhil Thesis Research (0 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
R01 (6922)	TBA	No room required	TBA	999	6	993	0

COURSE INFO

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.

UGOD 7990 - Doctoral Thesis Research (0 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
R01 (6923)	TBA	No room required	TBA	999	25	974	0