Graduate classes, Fall 2015, Computer Science

CS 524: Theory Of ComputingCredits: 3− 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.
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Prerequisites: CS 124 and 253.
000MSC: W306TuTh 10:00am - 11:15amMichelangelo Grignimax 25
CS 540: Software EngineeringCredits: 3− Description− Sections
Content: Software engineering principles and practice is taught by using materials from the classic textbook by Roger Pressman, guest lectures from industry practitioners from the Atlanta area, and a collection of essays from author-practitioners, like Joel Spolsky and Steve McConnell. Software engineering as a discipline has evolved in conjunction with computer hardware and programming tools. Despite its infancy, SW Engineering has some fundamental processes that are recognized as essential to the production of quality software that meets customer requirements. Both the ACM (as "SE2004") and the IEEE (as "Software Engineering Body of Knowledge" or "SWEBOK") have defined a set of skills that practitioners of software development should possess. These include Requirements, Design, Construction, Testing, Quality Control, and Configuration Management. This course seeks to teach principles of software engineering through hands-on experience in constructing a real-life project. See the course website at http://www.mathcs.emory.edu/~cs540000/index.html for information on textbooks, schedule, presentation materials, grading and assignments.
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000MSC: W303TuTh 4:00pm - 5:15pmAnca Doloc-Mihumax 10
CS 551: Systems ProgrammingCredits: 3− Description− Sections
Content: Systems programming topics will be illustrated by use of the Unix operating system. Topics include: file i/o, the tty driver, window systems, processes, shared memory, message passing, semaphores, signals, interrupt handlers, network programming and remote procedure calls. Programming examples and assignments will illustrate the system interface on actual computer hardware. All assignments will be in written in C. The department's computing lab will be used in the course to allow students to get hands-on experience with operating system and hardware topics that cannot effectively be pursued on a central timesharing computer.
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000MSC: W301TuTh 2:30pm - 3:45pmKen Mandelbergmax 25
CS 556: Compiler ConstuctionCredits: 3− Description− Sections
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000MSC: W301MW 2:30pm - 3:45pmJames Lumax 10
CS 570: Data MiningCredits: 3− Description− Sections
Content: This course offers an introduction to data mining concepts and techniques. The goal is for the students to have a solid foundation in data mining that allows them to apply data mining techniques to real-world problems and to conduct research and development in new data mining methods. Topics include data processing, design and implementation of data warehouse and OLAP systems, data mining algorithms and methods including association analysis, classification, cluster analysis, as well as emerging applications and trends in data mining.
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000MSC: W302MW 10:00am - 11:15amLi Xiongmax 25
CS 571: Natural Language ProcessingCredits: 3− Description− Sections
Content: This course introduces the fundamental concepts and ideas in natural language processing (NLP). It develops an understanding of algorithms for processing linguistic information and the underlying computational properties of text. The focus is on modern quantitative techniques in NLP. Advanced topics will include introduction to information retrieval, text mining and knowledge discovery from text data, as well as applications of NLP to bioinformatics and medical informatics.
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000MSC: W303MW 4:00pm - 5:15pmJinho Choimax 25
CS 584: Topics In Computer Science: Computer SecurityCredits: 3− Description− Sections
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001MSC: E408MW 11:30am - 12:45pmYmir Vigfussonmax 2
CS 584: Topics in Computer Science: Digital Image ProcessingCredits: 3− Description− Sections
Content: This course introduces the fundamental algorithms, concepts, and applications of image analysis with special focus on familiarizing students with contemporary techniques and applications in biomedical image analysis. Theoretical and practical knowledge concerning image analysis algorithms will be developed through short lectures, paper discussions, and a team project exercise. A variety of imaging modalities will be covered including microscopy and radiology. Following this course, students will understand the process of image formation, how information is extracted from images, and the role of this information in biomedical applications from diagnostics to molecular cell biology.
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000 MW 1:00pm - 2:15pmJun Kongmax 16
CS 590: Teaching SeminarCredits: 1− Description− Sections
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000MSC: W302F 2:00pm - 2:50pmShun Yan Cheungmax 30
CS 597R: Directed StudyCredits: 1 - 9− Description− Sections
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00P Mary Galinskimax 999
BENZ Michele Benzimax 999
CHOI Jinho Choimax 999
CS 598R: Rotation ProjectCredits: 1 - 3− 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.
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000 Shamim Nematimax 999
COOP Lee Coopermax 999
KONGJun Kong
CS 700R: Graduate SeminarCredits: 1− Description− Sections
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000MSC: W303F 3:00pm - 3:50pmVaidy Sunderammax 30
CS 797R: Directed StudyCredits: 1 - 9− Description− Sections
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QIN Zhaohui "Steve" Qinmax 99
CS 799R: Dissertation ResearchCredits: 1 - 9− Description− Sections
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AGIC Eugene Agichteinmax 999
COOP Lee Coopermax 999
QIN Zhaohui "Steve" Qinmax 99
SUND Vaidy Sunderammax 999
XION Li Xiongmax 99