CSE 591 - Visual Analytics


General Info:

Instructor: Prof. Klaus Mueller
    Office hours: CS 2428, We 2-3pm (or send email for other arrangements)
    Phone: 632-1524
    Email: muellerATcsDOTsunysbDOTedu

Grader: TBD
    Office hours:

Meeting time and venue:
    Soc Behav Sci, N436, Tu Th  6:50 - 8:10 pm

    Visual Analytics is the science of analytical reasoning facilitated by interactive visual interfaces. People use visual analytics tools and techniques to synthesize information and derive insight from massive, dynamic, ambiguous, and often conflicting data, provide timely, defensible, and understandable assesments; and communicate assesment effectively for action. The overall goal is to detect the expected and discover the unexpected.

Visual analytics is a multidisciplinary field that includes the following focus areas:
The course will discuss and combine principles from cognitive science, information visualization, machine-based reasoning and learning, and data mining. It is planned to have a variety of researchers proficient in these fields come and give guest lectures in the course. Visual analytics has a large and growing spectrum of application areas ranging from commercial (finance, business, medical/health care, insurance), law enforcement (money laundering, capital crimes), homeland security (combat terrorism, border security), national security (intelligence, information access) to information technology (internet security, network analysis, software management and debugging, etc).

    Graduate standing
    Working knowledge of C/C++

    Available on the internet for free download:
For additional reference and on reserve in the CS library:
    Presentations: 50%
    Final project: 50%


    The course will promote an interactive participation in the class. There will not be any midterms or finals. Rather, each particpant will be asked to give 1-2 presentations of relevant papers, book chapters, or similar.

Final Project:
    In the final project you may choose among several topics related to the course content. You will first write a proposal and then keep a log about your activites via a web page. At the end of the semester, you will present your project to the rest of the class and document your findings on the web page.