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Additional Course Descriptions 2007-2008

CS 525D Knowledge Discovery and Data Mining (Spring 08)

Instructor: C. Ruiz

Due to advances in technology and the availability of increasingly cheap storage devices, data in different domains have been accumulating at an impressively high rate in recent years, leading to very large databases. This course presents current research in Knowledge Discovery in Databases (KDD) dealing with the data integration, mining, and interpretation of patterns in such databases. Topics include data warehousing and mediation techniques aimed at integrating distributed, heterogeneous datasources; data mining techniques such as rule-based learning, decision trees, association rule mining, and statistical analysis for discovery of patterns in the integrated data; and evaluation and interpretation of the mined patterns using visualization techniques. The work discussed originates in the fields of databases, artificial intelligence, information retrieval, data visualization, and statistics. Industrial and scientific applications will be given. (Prerequisites: Background in databases and artificial intelligence at the undergraduate level, or permission of the instructor. Background in statistics would be helpful but is not assumed. Proficiency in a high level programming language, preferable Java, is required.)

CS 525M Techniques for Modular Software Composition (Fall 07)

Instructor: G. Heineman

This course will cover advanced topics in modularity. The essence of Software Engineering is to develop techniques that enable corporations and the individual programmer to effectively use their time while developing quality applications. The fundamental approach towards achieving such efficiency is dividing a problem into smaller sub-problems that are reassembled to achieve a larger goal. Over the past fifty years, various systems of design have been developed to enable software engineers to model and program software applications. In this course, we will investigate the issue of modularity in theory and practice. Students will be expected to design and implement solutions using advanced techniques in modularity, such as aspect oriented programming, feature-based software layers, mixins, meta programming, software compositional languages, and category theory. Students will prepare presentations, read seminal and relevant conference and journal publications, and participate in class discussions. (Prerequisites: A graduate course in Software Engineering or equivalent knowledge is required. If you have questions, contact the instructor).
Web: web.cs.wpi.edu/~heineman/html/teaching_/CS525_2007/

CS 525P Intelligent Pedagogical Agents (Fall 07)

Instructor: N. Heffernan

This course addresses the use of educational datamining techniques to build better intelligent tutoring systems. Students will learn empirical and theoretical methods for creating cognitive models of human problem solving. Such models have been used to create educational software that has been demonstrated to dramatically enhance student learning in domains such as mathematics and computer programming. This course will have three components: 1) a literature review of some of the fundamental papers in the field; 2) some lectures on the needed cognitive psychology and current techniques for desiging and building tutoring systems; 3) a significant project component in which students will be practicing the use of these methods. The culminating project will be to build a piece of an intelligent tutoring system. Ideally, the final project should lead to a publishable EDM 2008 paper. At the end of this course a student should be able to do research in intelligent tutoring systems. (Prerequisites: Good programming skills are required. Artificial intelligence would he helpful but not required. Knowledge of cognitive psychology and/or human-computer interaction would be a plus).

CS 525S Computer and Network Security (Fall 07)

Instructor: W. Lou

This course provides a comprehensive introduction to the field of computer and network security. Security architectures and protocols and their impact on computers and networks are examined. Critical computer and network security aspects are identified and examined from the standpoints of both the user and the attacker. Computer system and network vulnerabilities are examined, and mitigating approaches are identified and evaluated. Both the principles and practice of computer and network security are introduced. The basic issues to be addressed by a computer and network security capability are explored. The practice of computer and network security: practical applications that have been implemented and are in use to provide security are surveyed. (Prerequisites: Working knowledge of computers, basic computer networks.)

CS 525U Intelligent User Interfaces (Spring 08)

Instructor: C. Rich

We have exhausted the potential of current WIMP (windows, icons, menus and pointer) interfaces to make computational systems easier for people to use. This course will focus on the application of techniques from artificial intelligence, such as knowledge representation, machine learning, planning and natural language processing, to create intelligent user interfaces that learn, teach and adapt to the user. Topics studied will include programming by example, social recommender systems, collaborative interfaces, affective (emotion) computing and human-robot interaction. The course will include reading of current research papers and an implementation project. (Prequisites: CS 4341 and CS 3041, equivalent graduate courses, or familiarity with basic techniques in artificial intelligence and human-computer interaction.)

CS 525V Building Effective Virtual Worlds (Spring 08)

Instructor: R. Lindeman

In this course we will explore the techniques and technologies that need to be brought together to allow people to work efficiently in virtual worlds. Topics include systems for presenting information to all five senses (visual, auditory, haptic, olfactory, and gustatory), methods for users to interact with objects within virtual environments, and evaluation techniques for assessing effectiveness. Students will use various display and interfaces devices available for the course, develop prototype applications, and evaluate them. The format of the course will be a combination of traditional lecture, literature review, and hands-on work. Students will be expected to implement several techniques as part of this course. (Prerequisites: a graduate or undergraduate course in computer graphics or HCI).

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Last modified: August 08, 2007 14:11:53