Graduate classes, Fall 2010, Computer Science
|CS 524: Theory Of Computing||Credits: 4||− Description||− Sections|
Content: This course gives mathematical methods to classify the complexity of computational problems. Topics include regular languages, grammars, decidability, NP-completeness, and corresponding models of computation.
Texts: Introduction to the Theory of Computation, by Spiser. Course Technology. ISBN 10: 0534950973.
Prerequisites: CS 124 and 253.
|000||MSC: E408||MWF 12:50pm - 1:40pm||Michelangelo Grigni||max 16|
|CS 551: Systems Programming||Credits: 4||− Description||− Sections|
Texts: Advanced Unix Programming, by Marc J. Rochkind. Addison Wesley Professional. ISBN# 10-0131411543.
|000||MSC: W301||TuTh 2:30pm - 3:45pm||Ken Mandelberg||max 20|
|CS 556: Compiler Construction||Credits: 4||− Description||− Sections|
Content: An introduction to the algorithms and data structures used to construct a high level language compiler. Topics include: formal language specification, lexical analysis, parsing, and code generation.
Texts: Principles, Techniques, and Tools, by Aha, Sethi, Ullman, & Lam. Pearson Education, Inc. ISBN 0-471-69466-5.
Prerequisites: CS 253, CS 255, and CS 424, or their equivalents. A substantial portion of this course will involve a student project to construct a compiler for a simplified programming language. Working knowledge of C or C++ is highly recommended.
|000||MSC: W301||MW 3:00pm - 4:15pm||James Lu||max 10|
|CS 558: Networking||Credits: 4||− Description||− Sections|
Content: This course studies performance issues in computer networks.
The course starts with a brief introduction to
The Markov chain analysis technique is then used to
study the performance of classic protocols such as Aloha, CSMA and
new wireless protocols, such as 802.11.
The second topic is congestion control in the Internet.
The performance of the TCP protocol will be studied
analytically as well as empirically using the NS2 network simulator.
A number of TCP performance issues will also be discussed,
including TCP synchronization, High speed TCP and RTT unfairness.
The last portion of the course will study advanced network
techniques to ensure quality of service (QoS).
Topics include fairness guarantee, delay guarantee, and
If time permits, we will also study
multicasting, video on demand and
other exotic network protocols.
Texts: no text book (online notes and research papers)
Assessments: homeworks, one midterm and one final
|000||MSC: W304||TuTh 1:00pm - 2:15pm||Shun Yan Cheung||max 25|
|CS 584: Topics in Computer Science: Software Engineering||Credits: 4||− Description||− Sections|
Content: This course seeks to teach principles of software engineering through hands-on experience in a series of projects, and through a survey of the skills and body of knowledge software engineers are expected to possess. These include Requirements, Design, Construction, Testing, Quality Control, and Configuration Management. In addition, the student will be introduced to applied concepts in software engineering through the blogs and writings of some of today's most noted practitioners.
Texts: Software Engineering: A Practitioner’s Approach (Roger S. Pressman, 7th edition)
will serve as the primary text. Other materials used in the course are available on the web.
Assessments: A combination of exams, homework and project work will provide the basis for assessments.
Prerequisites: Graduate student, or Senior standing, with permission from the instructor. The student must be competent in at least one language used in web software development.
|001||MSC: W304||TuTh 4:00pm - 5:15pm||Joan Smith||max 10|
|CS 584: Topics in Computer Science: Machine Learning||Credits: 4||− Description||− Sections|
Content: This course will cover the theory and practice of machine learning. We will discuss both supervised approaches (linear methods for classification, rule based methods, kernels, prototype based methods) and unsupervised approaches (clustering, linear and non-linear dimension reduction). Student presentations on topics from the primary text, research papers, and applied projects will make up a significant portion of the course
Texts: Hastie, Tibshirani, and Friedman. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. **Second Edition**
The text is available online at http://www-stat.stanford.edu/~tibs/ElemStatLearn/download.html, but a physical copy is **highly** recommended.
|000||MSC: E406||TuTh 11:30am - 12:45pm||James Taylor||max 16|
|CS 590: Teaching Seminar||Credits: 1||− Description||− Sections|
Content: This seminar will concentrate on effective teaching techniques in computer science. Topics included will include:
General advice for new TA's. General advice for International TA's. Students will present several practice lectures over different levels of material. They will receive practice on quiz and test preparation. Syllabus information on courses most likely to be taught by new TA's will be supplied. General professional development information will also be included.
|000||MSC: E408||F 2:00pm - 2:50pm||Shun Yan Cheung||max 999|
|CS 597R: Directed Study||Credits: 1 - 12||− Description||− Sections|
|00P||TBA||Faculty (TBA)||max 999|
|CS 598R: Rotation Project||Credits: 1 - 4||− Description||− Sections|
Content: Computer Science and Informatics PhD students are required to complete two rotation projects prior to their qualifying exams and dissertation research. Projects often involve interdisciplinary work, and can be co-supervised by a Math/CS faculty and an external faculty member or researcher (e.g., Schools of Medicine and Public Health, the CDC). Students are required to submit a project proposal and a final report.
|000||TBA||Faculty (TBA)||max 999|
|02P||Shun Yan Cheung|
|03P||Michelangelo Grigni||max 999|
|04P||James Lu||max 999|
|06P||James Nagy||max 999|
|07P||Vaidy Sunderam||max 999|
|CS 599R: Master's Thesis Research||Credits: 1 - 12||− Description||− Sections|
|000P||TBA||Faculty (TBA)||max 999|
|CS 700R: Graduate Seminar||Credits: 1||− Description||− Sections|
Content: This is a required course for all students in the PhD program. It comprises seminars given by faculty, invited guests, and students.
|000||MSC: W301||F 3:00pm - 4:15pm||James Lu||max 25|
|CS 730R: Topics in Data and Information Management||Credits: 4||− Description||− Sections|
Content: This is an advanced graduate course in the focus area of the Computer Science and Informatics PhD program. Coverage and syllabus will vary according to the instructor and emphasis will be on current developments in the field.
|000||Emerson E510||M 10:00am - 12:30pm||Eugene Agichtein||max 16|
|CS 797R: Directed Study||Credits: 1 - 12||− Description||− Sections|
|00P||TBA||Faculty (TBA)||max 999|
|CS 799R: Dissertation Research||Credits: 1 - 12||− Description||− Sections|
|00P||TBA||Faculty (TBA)||max 999|