MSBD5005 (L1) - Data Visualization

Spring 2021  Lecture Notes  Tutorials  Course Projects  Exam Info  Course Policies  Announcements 



L1:  Huamin Qu
Office hours (in Room 2529): by email appointment.



Leo Yu Ho Lo (


Time and Venues


L1  Sa 03:00PM - 05:50PM


Grading Scheme:

Final Exam (30%)
Essay (10%)
In-Class Exercise (10%)
Final project (50%)

Course Description:

This course will introduce visualization techniques for data from everyday life, social media, business, scientific computing, medical imaging, etc. The topics include human visual system and perception, visual design principles, open- source visualization tools and systems, visualization techniques for CT/MRI data, computational fluid dynamics, graphs and networks, time-series data, text and documents, Twitter data, and spatio-temporal data. The labs and the course project will give students hands-on experience to turn their favorite data into beautiful visualizations.



Visualization Analysis and Design by Tamara Munzner
Interactive Data Visualization: Foundations, Techniques, and Applications by Matthew Ward, Georges Grinstein, and Daniel Keim
The visualization handbook
Information visualization: perception for design
The visual display of quantitative information
Envisioning information
Visual explanations: images and qauntities, evidence and narrative



Resources: | A visual exploration on mapping complex networks
information aesthetics - Information Visualization & Visual Communication


Conferences and Journals:

IEEE VIS Conferences
IEEE Transactions on Visualization and Computer Graphics
IEEE Xplore (Proceedings of IEEE visualization, infovis; TVCG)



Exam Scheduling:  

Final   TBD  TBD  TBD



Intellectual Honesty & Plagiarism

  • Students are expected to follow the HKUST Academic Honor Code
  • All work submitted for grading, e.g., assignments, must be your own
  • You are permitted to discuss problems with other students but you must write-up all solutions by yourself, in your own words.
  • If you got the main idea for a solution from another student or a web-site you must acknowledge that source in your submission.
  • Submission of non-acknowledged material will be considered as plagiarism and dealt with under the university policy for cheating.


Course Summary:

Date Details Due