Course Syllabus

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Fall 2017   Lecture Notes Lab Schedule Course Projects  Exam Info   Course Policies   Announcements 

 

Instructor

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

 

TA

Ming Yao (ymingaa@connect.ust.hk)

 

Time and Venues

Lectures:

L1  Friday  7:30 – 10:20pm   Room 4619

 

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.

 

References:

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

 

Links:

Resources:

visualcomplexity.com | 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