Download a PDF version of the syllabus.


Ming Yin

Office: TBD
Email: mingyin [AT]
Office Hours: By Appointment

Course Description

Crowdsourcing and social computing sits at the intersection of computer science, economics and other social sciences. It concerns developing empirical understandings and designing computational systems and techniques to enable effective interactions between people and machines for solving complex problems. This course surveys the state of the art in this area. Topics of interests include incentive design, workflow design, quality control and intelligent management in crowdsourcing, computer supported collaborative work, and applications in various domains like artificial intelligence and citizen science.

Course Schedule

See the calendar page.


Paper Reading, Presentation and Discussion

Most classes in this course consist of paper reading, presentation and discussion. Specifically, in a typical class, we will cover 1-2 papers on one topic, and 1-2 students will be assigned to give a presentation on this topic. Responsibility of presenters of one class include:

Responsibility of non-presenters of one class include:

Final Project

Final project serves as an opportunity for students to get hands-on experience in crowdsourcing and social computing research. Projects are open-ended; sample projects include:

Students are also encouraged to connect the final project with their own research.

Students can complete the project either individually or in a group of two. Tasks related to the final project include:

More detailed instruction on the final project will be provided through project guidelines.


Basic programming skills required. Students should be comfortable with at least one programming language (e.g., C, Java, Python, etc.). Knowledge with artificial intelligence and machine learning is welcome.

Required Texts

No textbook is required for this course.