Computer Science Course Descriptions for Spring of 2005
CMPSCI 105: Computer Literacy (R2)Professor: VertsMicrocomputers are now used widely not only in academia but in all areas of modern life. For this reason it's important that all students understand how computers work and how computers can be used as a problemsolving tool. The focus of this course is on computer applications. The course stresses the ways in which computers can help you solve problems efficiently and effectively. The course provides a broad introduction to hardware and software aspects of microcomputers. Then four application areas are discussed: word processing, spreadsheets, databases and telecommunications (access to the Internet). Weekly lab assignments are an integral part of the course. Students in lectures A1, A2, D, E, F use the University's microcomputer labs, all other students are expected to use their own equipment. Students who are more interested in computer programming should take CMPSCI 121 or 187. Prerequisites: reasonable high school math skills. Typing ability is also an important asset for the course. Previous computer experience is not expected. Registration is not available to majors and premajors. 3 credits. CMPSCI 105D: Computer Literacy (R2)Professor: VertsSAME AS 105. CMPSCI 105E: Computer Literacy (R2)Professor: VertsSAME AS 105. CMPSCI 105F: Computer Literacy (R2)Professor: VertsSAME AS 105. CMPSCI 121: Introduction to Problem Solving with Computers (R2)Professor:An introductory course in problem solving and computer programming using the programming language Java. The course focuses on the fundamental concepts of problem solving and the techniques associated with the development of algorithms and their implementation as computer programs. This course or its equivalent is required for all additional courses in CMPSCI. Three hours of lecture/recitation per week. About 7 programming projects are assigned. In addition there are assigned homework problems, a midterm exam and a final. No computer science prerequisite, although basic math skills (e.g. R1) and basic computer literacy (as taught in CMPSCI 105) are assumed. Use of computer is required. Prerequisite: R1. 3 credits. CMPSCI 123: Intro to Java IIProfessor: LehnertCmpSci 191B (123) is a programming course in Java for students who have previous programming experience in Java, C or C++. Students will be introduced to a variety of advanced topics such as inheritance, polymorphism, interface design, threads, and design patterns. Objectoriented concepts will be covered in great detail, but 123 assumes general familiarity with basic programming concepts such as arithmetic operators, boolean operators, conditional control structures, iterative control structures, and arrays. Students will have an opportunity to strengthen objectoriented programming skills through a series of required programming projects. CMPSCI 145: Representing, Storing and Retrieving InformationProfessor: VertsAn introductory course in the use of data in computer systems, a core course for the Information Technology certificate. Formats for representing text, numbers, sound, images, etc., as strings of bits. Equations of lines and courves, modeling of synthetic scenes (i.e., ray tracing), exploring the frequency domain and holography. Basic information theory, use and limitations of file compression and encryption. Structured databases and how to use them. Information retrieval in heterogenous environments such as the Web. XML as a language for defining new formats for representing data. Review of historical, precomputer methods of information representation. Prerequisites: "Basic computer literacy", i.e., userlevel familiarity with a modern operating system and some experience with application programs. Tier I math skills. Recommended for First Year and Sophomore NonMajors. Prerequisite: R1. 3 credits. CMPSCI 187: Programming with Data Structures (R2)Professor: MossThe course introduces and develops methods for designing and implementing abstract data types, using the Java programming language. The main focus is on how to build and encapsulate data objects and their associated operations. Specific topics include linked structures, recursive structures and algorithms, binary trees, balanced trees, and hash tables. There will be weekly assignments, consisting of programming and written exercises, a midterm, and a final exam. Prerequisites: CMPSCI 121 (or equivalentnot necessarily in Java) and Basic Math Skills (R1). Basic Java language concepts are introduced quickly. Prior experience with an objectoriented language is very helpful; if unsure of background, contact instructor. 187 Lect B, Computer Science Tap only. 4 credits. CMPSCI 197C: STProgramming In C++Professor: HeydtBenjamin, CornerCMPSCI 201: Architecture and Assembly Language (E)Professor: PalmerLecture, discussion, lab. The architecture and machinelevel operations of modern computers at the logic, component, and system levels. Topics include integer, scaled, and floating point binary arithmetic; Boolean algebra and logic gates; control, arithmeticlogic, and pipeline units; addressing modes; cache, primary, and virtual memory; system buses; inputoutput and interrupts. Simple assembly language for a modern embedded processor is used to explore how common computational tasks are accomplished by a computer. Two lectures, one discussion, and one lab session per week. Laboratory exercises, homework exercises, inclass quizzes, two midterm exams, and a final exam. Prerequisite: CMPSCI 187 or ECE 242 or equivalent. 4 credits. CMPSCI 250: Introduction to Computation (E)Professor: BarringtonLecture, discussion. Basic concepts of discrete mathematics useful to computer science: set theory, strings and formal languages, propositional and predicate calculus, relations and functions, basic number theory. Induction and recursion: interplay of inductive definition, inductive proof, and recursive algorithms. Elementary combinatorics. Basic graph theory. Finitestate machines, regular languages, nondeterministic finite automata, Kleene's Theorem. Problem sets, 2 midterm exams, timed final. Corequisite: MATH 132/136 or equivalent. Prerequisite: MATH 131 and (CMPSCI 187 or ECE 242). CS ENG majors may take CMPSCI 250 with ECE 242. Contact your Department Advisor. 4 credits. CMPSCI 287: Programming Language ParadigmsProfessor: UtgoffLecture, discussion, programming projects, lab. Programming language paradigms provide a basic philosophy to support the construction of reliable largescale systems. This course discusses four such paradigms. In the functional paradigm, software is constructed in such a way as to minimize the use of sideeffects, thereby simplifying the conceptual structure of programs and making them easier to analyze and understand. The logic paradigm supports the development of software in which the concept of relation (e.g. a relation between people) is more important than the concept of function. In the imperative paradigm we are concerned with principled ways in which software that is statedependent can be constructed. Finally, in the objectoriented paradigm we are concerned with combining data with code to create "objects" that exhibit behavior. Prerequisite: CMPSCI 187 or ECE 242. Corequisites: CMPSCI 250 and MATH 132. 4 credits. CMPSCI 305: Social Issues in ComputingProfessor: ConstantineDesigned to satisfy the Junior Year writing requirement, CMPSCI 305 introduces the student to technical writing and editing, scientific journalism and the social essay. The course combines practical, scientific writing as found in industry and business with explorative essays that focus attention upon the technological and humanistic concerns inherent in society. Ten written assignmentstwo longer papers, eight shorter ones and one oral presentation. Prerequisite: ENGLWP 112 or CW. 3 credits. CMPSCI 311: Introduction to AlgorithmsProfessor: SitaramanThis course will introduce you to algorithms in a variety of areas of interest, such as sorting, searching, stringprocessing, and graph algorithms. You will learn to study the performance of various algorithms within a formal, mathematical framework. There will be a few programming assignments as well to help you relate the empirical performance of an algorithm to theoretical predictions. Mathematical experience (as provided by CMPSCI 250) is required. You should also be able to program in Pascal or C (or some other closely related language). Prerequisite: CMPSCI 250 or MATH 455. 4 credits. CMPSCI 320: Introduction to Software EngineeringProfessor: FisherIn this course, students learn and gain practical experience with software engineering principles and techniques. The practical experience centers on a semesterlong team project in which a software development project is carried through all the stagesof the software life cycle. Topics in this course include requirements analysis, specification, design, abstraction, programming style, testing, maintenance, and software project management. Particular emphasis is placed on designing and developing maintainable software and on the use of objectoriented techniques throughout the software lifecycle. Use of computer required. Several quizzes, major term project. Prerequisite: CMPSCI 287. 4 credits. CMPSCI 377: Operating SystemsProfessor: CornerIn this course we examine the important problems in operating system design and implementation. The operating system provides a wellknown, convenient, and efficient interface between user programs and the bare hardware of the computer on which they run. The operating system is responsible for allowing resources (e.g., disks, networks, and processors) to be shared, providing common services needed by many different programs (e.g., file service, the ability to start or stop processes, and access to the printer), and protecting individual programs from one another. The course will start with a brief historical perspective of the evolution of operating systems over the last fifty years, and then cover the major components of most operating systems. This discussion will cover the tradeoffs that can be made between performance and functionality during the design and implementation of an operating system. Particular emphasis will be given to three major OS subsystems: process management (processes, threads, CPU scheduling, synchronization, and deadlock), memory management (segmentation, paging, swapping), file systems, and operating system support for distributed systems. Assignments: 3 labs in C/C++, 3 exams, 6 or more written homeworks. Prior experience with C/C++ is helpful, but not required. Prerequisites: CMPSCI 187 and (CMPSCI 201 or ECE 232). 4 credits. CMPSCI 383: Artificial IntelligenceProfessor: ZilbersteinIntroduction to techniques for building intelligent systems. Problem solving, statespace representation, heuristic search techniques, game playing, knowledge representation, logical reasoning, planning, reasoning under uncertainty, and machine learning. The course can be taken as part of the core CS program, as a grounding for further study in AI, or to gain familiarity with AI methods for application in other fields. Prerequisites: CMPSCI 250 and CMPSCI 287 and CMPSCI 311. 3 credits. CMPSCI 391S: Seminar  Fundamentals of Graphic CommunicationProfessor: WoolfThis course provides an understanding of computerbased design and multimedia production. Basic concepts in the areas of graphic design, animation, video editing and objectoriented programming will be covered preparing students for more advanced studies in 2D and 3D animation and in multimedia programming. Course work consists mainly of several student projects, built incrementally as several smaller subprojects. Each student s project will be presented via the World Wide Web and discussed in class. Students interaction is encouraged through peer reviews and inclass exercises. Topics include HTML, Cascading Style Sheets (CSS), file transfer, designing and drawing characters, image formats/image compression for the web, modeling and animation. CMPSCI 397B: ThreeDimensional Animation and Digital EditingProfessor: WoolfThis seminar is dedicated to the production of high quality 3dimensional computer animation using graphics technology. For example, color 3D objects are defined and manipulated, digitized images created and altered, and photorealistic effects and animated sequences produced. Techniques are used to bend and twist shapes around objects or lines, to provide a variety of light and texture, and to trace over images including digitized pictures. The course is directed at production of an informative and approachable ten minute 3dimensional animated piece. Using computergenerated graphical analogies as well as cartoon caricature, the video is designed to educate and entertain. The class does not have lab facilities for all students interested in this material and thus we limit the class to students who do well on the first assignment. This assignment will be graded and returned to students before the end of the Add/Drop period. Students are cordially invited to attend the first class, the first Tuesday/Thursday of the semester. At that time we will explain the course, what is expected of students and the entry condition. 3 credits. CMPSCI 397C: Interactive Multimedia ProductionProfessor: ** Section DeletedThis course explores the potential of high quality interactive authoring tools to develop presentation and training systems. Programming languages within professional presentation and editing packages will be used to create systems capable of presenting graphics, animation, text, sound and music, based on the users requests. Students will learn how to define and manipulate classical techniques such as storyboarding, staging, and interactivity. The course will concentrate on stateoftheart multimedia composition and presentation techniques and developing small individual projects. The class does not have lab facilities for all students interested in this material and thus we limit the class to students who do well on the first assignment. This assignment will be graded and returned to students before the end of the Add/Drop period. Students are cordially invited to attend the first class, the first Tuesday/Thursday of the semester. At that time we will explain the course, what is expected of students and the entry condition. Prerequisite: CMPSCI 551 (591x)  3D Computer Animation and Digital Editing. Permission of the instructor required; contact: Beverly Woolf 5454265. 3 credits. CMPSCI 397D: Interactive Web AnimationProfessor: WoolfThis course teaches basic animation for the Web, interactivity, color theory, design, action scripting, and transitions. Students maintain their own web sites and submit projects every 2 weeks in Flash. Individual as well as, a final project are required. Knowledge of basic Web development, e.g., HTML, Java Script. Prerequisite: CMPSCI 391F; CMPSCI 551 and CMPSCI 552 preferred. Permission of instructor is required. 3 credits. CMPSCI 397E: Seminar  Character AnimationProfessor: WoolfThis class focuses exclusively on character animation techniques. The goal is to attain proficiency in modeling, texturing and animation. Modeling topics include character modeling and bones, designing joints and creating chains with constraints for easy animation, facial modelling and lip sync, designing faces with economical splinage to simplify facial animation, breaking down voice tracks into phonemes and animating facial and body language to match the track. Animation topics include action andpose, timing, overlap, pacing, and simulating and exaggerating physical laws. Student will create their own final project or work in a small team. Prerequisites: CMPSCI 551 (591x)3D Animation and Digital Editing or equivalent experience and a personal computer. 3 credits. CMPSCI 401: Formal Language TheoryProfessor: RosenbergThe course will introduce the abstract branch of Computer Science known as Computation Theory, via "big ideas" that underlie the field. The course will focus on: [1] The Theory of Finite Automata (What are the capabilities and limitations of finitestate transition systems?); [2] Computability Theory (What are the ultimate limitations of digital computing systems?); [3] Complexity Theory (Abstractly, this is Computability Theory with "within given resource bounds" [e.g., time, memory] replacing "ultimate.") The treatment of Finite Automata will culminate in the seminal KleeneMyhill and MyhillNerode characterization theorems. The treatment of Computability Theory will lead through proofs of noncomputability to the sweeping RiceMyhillShapiro Theorem. The treatment of Complexity Theory will develop the theory of problem reductions, leading to the CookLevin Theorem and NPCompleteness. PREREQUISITE: CMPSCI 250 and 311, or their equivalents. CMPSCI 445: Information SystemsProfessor: KulpIntroduction to database systems. Relational database topics including data modeling, query languages, database design, optimization and security. Alternative database approaches including objectoriented, objectrelational, XML and information retrieval technology. Prerequisite: CMPSCI 287. 3 credits. CMPSCI 445X: Information SystemsProfessor:PEEAS course. CMPSCI 453: Computer NetworksProfessor: KuroseThis course provides an introduction to fundamental concepts in the design and implementation of computer communication networks, their protocols, and applications. Topics to be covered include: layered network architectures, applications, network programming interfaces (e.g., sockets), transport, congestion, routing, and data link protocols, local area networks, emerging highspeed networks, network management, and network security. Examples will be drawn primarily from the Internet (e.g., TCP, UDP, and IP) protocol suite. There will be written assignments, programming assignments (in C), one midterm, and a final exam. Prerequisites: A rudimentary understanding of computer architecture and operating systems, while not required, would be helpful. 3 credits. CMPSCI 491J: Seminar: The Computer Science of Multiplayer GamesProfessor: Levine, BurnsThis undergraduatelevel seminar focus on the computer science that enable massivelymultiplayer online games. The class is based on studentled discussions and programming projects. Students in the class are evaluated based on their performance in those two tasks (and not exams, quizes, etc). Topics include artificial intelligence, networking, graphics, and game design. The project involve enhancing one or more components of an empty game given to the class at the beginning of the semester: e.g., automated bots, graphics, game consistency, network performance, and cheat proofing. Prerequisites: CMPSCI 377. CMPSCI undergraduates only, or with permission of instructor. CMPSCI 520X: Software Engineering: Synthesis and DevelopmentProfessor:PEEAS course. CMPSCI 521: Software Engineering: Analysis and EvaluationProfessor: ClarkeSoftware systems have become an integral part of our societal infrastructure. Software controls lifecritical applications, such as air traffic control and medical devices, and is of central importance in telecommunication and electronic commerce. In this course, we will examine state of the art practices for testing and analyzing software systems that require high assurance. We will initially look at techniques developed for sequential systems but then examine the complexity that arises from distributed systems. Laboratory requirements: students will be required to carry out an individual or group project that applies or extends some of the techniques described in class. Text: course material will be drawn from the software engineering literature.Prerequisites: CMPSCI 320, Introduction to Software Engineering (or equivalent course). 3 credits. CMPSCI 521X: Software Engineering: Analysis and EvaluationProfessor:CMPSCI 530: Programming LanguagesProfessor: WiledenThis course undertakes a detailed examination of the fundamental principles underlying the design and implementation of modern programming languages. We address a wide range of programming language concepts and issues from both a practical and a theoretical perspective. Special attention is given to type systems and typechecking, since these are central to all subsequent developments. We also examine other important contemporary language features such as object orientation, modularity, polymorphism and concurrency. While the predominant paradigm for contemporary programming languages  the imperative, objectoriented paradigm  is our primary focus, and the functional paradigm is our secondary focus, we will place special emphasis on webprogramming as a source of examples and a basis for assignments and projects. Homework problems, programming exercises and projects reinforce the material covered in lectures and readings. Prerequisites: CMPSCI 287. Honors module when requested. 3 credits. CMPSCI 530X: Programming LanguagesProfessor:PEEAS course. CMPSCI 546: Web Search EnginesProfessor: AllanThe course will cover the information retrieval techniques needed to build a Webbased search engine. Topics covered will include basic models of retrieval systems, Web crawling, indexing and text representation, efficient storage of indexes, highthroughput query processing, and use of link information to change ranks. The course will include implementation of major parts of a Webbased search engine. 3 credits. CMPSCI 551: ThreeDimensional Animation and Digital EditingProfessor: WoolfThis seminar is dedicated to the production of high quality 3dimensional computer animation using graphics technology. For example, color 3D objects are defined and manipulated, digitized images created and altered, and photorealistic effects and animated sequences produced. Techniques are used to bend and twist shapes around objects or lines, to provide a variety of light and texture, and to trace over images including digitized pictures. The course is directed at production of an informative and approachable ten minute 3dimensional animated piece. Using computergenerated graphical analogies as well as cartoon caricature, the video is designed to educate and entertain. The class does not have lab facilities for all students interested in this material and thus we limit the class to students who do well on the first assignment. This assignment will be graded and returned to students before the end of the Add/Drop period. Students are cordially invited to attend the first class, the first Tuesday/Thursday of the semester. At that time we will explain the course, what is expected of students and the entry condition. 3 credits. CMPSCI 552: Interactive Multimedia ProductionProfessor: ** Section DeletedThis course explores the potential of high quality interactive authoring tools to develop presentation and training systems. Programming languages within professional presentation and editing packages will be used to create systems capable of presenting graphics, animation, text, sound and music, based on the users requests. Students will learn how to define and manipulate classical techniques such as storyboarding, staging, and interactivity. The course will concentrate on stateoftheart multimedia composition and presentation techniques and developing small individual projects. The class does not have lab facilities for all students interested in this material and thus we limit the class to students who do well on the first assignment. This assignment will be graded and returned to students before the end of the Add/Drop period. Students are cordially invited to attend the first class, the first Tuesday/Thursday of the semester. At that time we will explain the course, what is expected of students and the entry condition. Prerequisite: CMPSCI 551 (591x)  3D Computer Animation and Digital Editing. Permission of the instructor required; contact: Beverly Woolf 5454265. 3 credits. CMPSCI 553: Interactive Web AnimationProfessor: WoolfThis course teaches basic animation for the Web, interactivity, color theory, design, action scripting, and transitions. Students maintain their own web sites and submit projects every 2 weeks in Flash. Individual as well as a final project are required. Knowledge of basic Web development, e.g., HTML, Java Script. Prerequisite: CMPSCI 391F; CMPSCI 551 and CMPSCI 552 preferred. Permission of instructor is required. 3 credits. CMPSCI 554: Multimedia Production ManagementProfessor: WoolfThis course involves developing a large group 3D animation, beginning with a storyboard, developing models, lighting, background, sound and music. It involves team management, group dynamics, and production techniques. The final project will be demonstrated on the last day of class, to over 100 people. Prerequisite: CMPSCI 551. Permission of instructor is required. 3 credits. CMPSCI 570: Computer VisionProfessor: LearnedMiller, HansonPeople are able to infer the characteristics of a scene or object from an image of it. In this course, we will study what is involved in building artificial systems which try to infer such characteristics from an image. Topics include: Basics of image formation  the effect of geometry, viewpoint, lighting and albedo on image formation. Basic image operations such as filtering, convolution and correlation. Frequency representations of images. The importance of scale in images. Measurements of image properties such as color, texture, appearance and shape. Inference of motion and structure from moving objects and images. Detecting and recognizing objects in images. Statistical methods in computer vision.The graduate version CMPSCI 670(691A) requires more work than this version of the course. Prerequisite: Linear algebra, calculus, basic knowledge of probability, and an ability to program. 3 credits. CMPSCI 575: Combinatorics and Graph TheoryProfessor: MollThis course is a basic introduction to combinatorics and graph theory for advanced undergraduates in computer science, mathematics, engineering and science. Topics covered include: elements of graph theory; Euler and Hamiltonian circuits; graph coloring; matching; basic counting methods; generating functions; recurrences; inclusionexclusion; and Polya's theory of counting. Prerequisites: mathematical maturity; calculus; linear algebra; strong performance in some discrete mathematics class, such as CMPSCI250 or MATH 455. Modern Algebra  MATH 411  is helpful but not required. 3 credits. CMPSCI 591EX: Computer NetworkingProfessor:PEEAS course. CMPSCI 591F: Seminar  Software Engineering Management PracticumProfessor: FisherThe purpose of this course is to provide students with practical experience in the management of software development projects. Students in this course will gain this experience by serving as software development team technical managers for teams of software engineering students in CMPSCI 320. As software development team managers, the students in CMPSCI 591F will be responsible for: supervising and managing the work of teams of CMPSCI 320 students; interfacing with the other CMPSCI 591F students managing other teams in the course; interfacing with the course instructor, course TA, and course customer. CMPSCI 591F students will be assigned readings in software engineering project management to provide a theoretical basis for their work in this course. But the majority of work in the course will be related to the actual management of assigned development teams. As team managers, CMPSCI 591F students will set goals and schedules for their teams, track and report team progress, negotiate with leaders of other teams and the course customer, and evaluate the work of members of their teams. CMPSCI 591F course assignments may include: written team goals, plans and schedules; periodic reports on team progress; documentation of agreements reached with other team leaders and customers; evaluations of the applicability of theoretical papers to the work of this course. This course will meet at the same times and places as CMPSCI 320. Additional meetings with team members and other students in CMPSCI 591F are also expected to be arranged by mutual agreement. Enrollment in this course is only by permission of the instructor, and is restricted to students who have previously taken CMPSCI 320, and received a grade of A or AB. 3 credits. CMPSCI 591G: Seminar  Computer Networking LabProfessor: TowsleyIn this course, students will learn how to put "principles into practice," in a handsonnetworking lab course. The course will cover router and endsystem labs in the areas of Single Segment IP Networks, Multiple Segment IP Networks and Static Routing, Dynamic Routing Protocols (RIP and OSPF) LAN switching, Transport Layer Protocols: UDP and TCP, IP Multicast, NAT, DHCP, DNS, SNMP and Network Security. These labs will be done in a networked lab setting consisting of 4 routers, 4 hubs, and 4 end systems. See http://wwwnet.cs.umass.edu/cs591_fall03 for specific lab content. Prerequisites: Successful completion of CMPSCI 453 and permission of instructor. CMPSCI 591O: Seminar  Character AnimationProfessor: WoolfThis class focuses exclusively on character animation techniques. The goal is to attain proficiency in modeling, texturing and animation. Modeling topics include character modeling and bones, designing joints and creating chains with constraints for easy animation, facial modelling and lip sync, designing faces with economical splinage to simplify facial animation, breaking down voice tracks into phonemes and animating facial and body language to match the track. Animation topics include action andpose, timing, overlap, pacing, and simulating and exaggerating physical laws. Student will create their own final project or work in a small team. Prerequisites: CMPSCI 551 (591x)3D Animation and Digital Editing or equivalent experience and a personal computer. 3 credits. CMPSCI 591Y: Knowledge Discovery and Data MiningProfessor: JensenKnowledge discovery is the process of discovering useful regularities in large and complex data sets. The field encompasses techniques from artificial intelligence (representation and search), statistics (inference), and databases (data storage and access). When integrated into useful systems, these techniques can help human analysts make sense of vast stores of digital information. This course presents the fundamental principles of the field, familiarizes students with the technical details of representative algorithms, and connects these concepts to applications in industry, science, and government, including fraud detection, marketing, scientific discovery, and web mining. The course assumes that students are familiar with basic concepts and algorithms from probability and statistics. CMPSCI 596A: Independent Study  TA for CMPSCI 551 3D AnimationProfessor: WoolfTAs are responsible for developing student assignments weekly and for group grading assignments every two weeks. They typically give one lecture per semester and also spend 6 hours/week in the Animation Lab assisting students. TAs setup and maintain hardware and software needed for lectures  3 or 4 commercial graphics packages. TAs take a lead role in the final course production, a group effort of 68 weeks work. Each TA manages 45 students organized in groups for 1) character animation, 2) lighting, 3) special effects, 4) surfaces, and 5) editing. The TA creates weekly tasks for each student in his/her group and makes sure that the work is complete and passed along to the next group on time. Prerequisite: CMPSCI 551 with grade of B or better. 3 credits. CMPSCI 596B: Independent Study  TA for CMPSCI 552 Interactive Multimedia ProductionProfessor: WoolfTAs are responsible for developing student assignments weekly and for group grading of assignments every two weeks. They typically give one lecture per semester, plus spend 6 hours/week in the Animation Lab assisting students. Setup/maintain hardware and software needed for lectures  1 or 2 commercial graphics packages in addition to Director. Also setup and maintain an internet site into which students put their class assignments. Work with students on individual Director final projects; Maintain communiction between 1215 students, intstructors and TAs. Prerequisite: CMPSCI 552 with grade of B or better. 3 credits. CMPSCI 596C: Independent Study  TA for CMPSCI 591O SeminarCharacter AnimationProfessor: WoolfTAs are responsible for providing assistance to the instructor and students of CMPSCI 591O SeminarCharacter Animation. Activities will include critiquing students work and providing useful feedback. Grading the class projects and homework assignments, and spending at least 6 hours each week in the laboratory to help the students with their daily work for the class. Evaluation will be done by the instructor based upon the quality of assistance to the students, attendance at the lectures and hours spent in the animation laboratory. Grading will also be based on advanced projects by the student and presented at the end of the semester. Prerequisite: CMPSCI 591O with grade of B or better. 3 credits. CMPSCI 596D: Independent Study  Advanced Computer ModelingProfessor: WoolfThis course focuses on production of high quality models, beginning with simple vases, desks, lamps and moving to character and humanoids. Students will model organic shapes, such as fruit, using splines, lathes, and extrudes. Surfacing topics such as specularity, reflection, trasparency, glow, decals and image maps will be discussed and modeled. Texture and advanced lighting techniques will be developed. Students will develop humanoid characters, modeling torso, shoulders, pelvis, arms, legs and hands feet and eyeballs. Geometry bones will be added to the final characters along with kinematic constraints and Euler Limits. The character's face will "lip sync" to speak or sing. Students will also create low patch proxy models of their characters to be used for blocking and simple motion within a final animation. These characters will be rigged for animation and the models given to students in the Animation Class for creation of the final project. Students will complete five independent modeling assignments and a final project in which their characters are animated by the Animation Class. The class does not have lab facilities for all students interested in this material and thus we limit the class to students who do well on the first assignment. This assignment will be graded and returned to students before the end of the Add/Drop period. Students are cordially invited to attend the first class, the first Tuesday/Thursday of the semester. At that time we will explain the course, what is expected of students and the entry condition. 3 credits. CMPSCI 601: Computation TheoryProfessor: ImmermanAn indepth introduction to the main models and concepts of the mathematical theory of computation, including: Computability: What problems can be solved in principle? How might you prove that a problem can't be solved? Complexity: What problems can be solved within given resource constraints? How do constraints on different resources (e.g., time, space, or parallel time) relate? Logic: What are the best ways to formally specify a problem, and how do these specifications relate to the difficulty of the problem? Prerequisites: Undergraduatelevel courses in discrete mathematics (e.g., CMPSCI 250) and analysis of algorithms (e.g., CMPSCI 311 or better yet 611), plus additional mathematical maturity (e.g., CMPSCI 611, A's in 250 or 311, or other mathematical background). Previous background in formal languages (e.g., CMPSCI 401) is quite desirable. Course requirements: about eight problem sets, timed midterm and final. Also open to qualified undergraduates. 3 credits. CMPSCI 601X: Computation TheoryProfessor:PEEAS. CMPSCI 603: RoboticsProfessor: GrupenIn addtion to traditions rooted in mechanics and dynamics, geometrical reasoning, and artificial intelligence, the study of robot systems is growing to include many issues traditionally part of the computing sciences; distributed and adaptive control, architecture, software engineering, realtime systems, information processing and learning. In robotics, processing and its relationship to mechanical function are dependent on the target platform and the world in which it is situated. Designing an embedded computational system for sensory and motor processes requires that designers appreciate and understand all of these disciplines. This course is concerned with the design and analysis of adaptive, closedloop physical systems. The focus will be sensory and motor systems that interpret and manipulate their environments. Toward this end, we will study mechanisms (kinematics and dynamics), actuators, sensors (with a focus on active vision), signal processing, associative memory, feedback control theory, supervised and unsupervised learning, and task planning. Interesting examples of integrated sensory, motor, and computational systems can be found in nature, so occassionally we will relate the subject matter to biological systems. Students willexperiment with system identification and control, image processing, path planning, and learning on simulated platforms to reinforce the material presented in class. 3 credits. CMPSCI 620X: Advanced Software Engineering: Synthesis and DevelopmentProfessor:PEEAS. CMPSCI 621: Advanced Software Engineering: Analysis and EvaluationProfessor: ClarkeSoftware systems have become an integral part of our societal infrastructure. Software controls lifecritical applications, such as air traffic control and medical devices, and is of central importance in telecommunication and electronic commerce. In this course, we will examine state of the art practices for testing and analyzing software systems that require high assurance. We will initially look at techniques developed for sequential systems but then examine the complexity that arises from distributed systems. Laboratory requirements: students will be required to carry out an individual or group project that applies or extends some of the techniques described in class. Text: course material will be drawn from the software engineering literature.Prerequisites: CMPSCI 320, Introduction to Software Engineering (or equivalent course). This course is taught concurrently with CMPSCI 521, but students taking CMPSCI 621 are expected to do additional and more challenging homework problems and projects. 3 credits. CMPSCI 621X: Advanced Software Engineering: Analysis and EvaluationProfessor:PEEAS. CMPSCI 630: Programming LanguagesProfessor: WiledenThis course undertakes a detailed examination of the fundamental principles underlying the design and implementation of modern programming languages. We address a wide range of programming language concepts and issues from both a practical and a theoretical perspective. Special attention is given to type systems and type checking, since these are central to all subsequent developments. We also examine other important contemporary language features such as object orientation, modularity, polymorphism and concurrency. While the predominant paradigm for contemporary programming languages  the imperative, objectoriented paradigm  is our primary focus, and the functional paradigm is our secondary focus, we will place special emphasis on webprogramming as a source of examples and a basis for assignments and projects. Homework problems, programming exercises and projects reinforce the material covered in lectures and readings. Prerequisites: Graduate standing or permission of instructor. 3 credits. CMPSCI 635: Modern Computer ArchitectureProfessor: WeemsThis course examines the structure of modern computer systems. We explore hardware and technology trends that have led to current machine organizations, then consider specific features and their impact on software and performance. These may include superscalar issue, caches, pipelines, branch prediction, and parallelism. Midterm and final exams, team project, homework, inclass exercises. Prerequisites: CMPSCI 535 or equivalent. 3 credits. CMPSCI 646X: Information RetrievalProfessor:PEEAS course. Students must register through PEEAS. Retrieval models, indexing and text representation, browsing and query formulation, routing, distributed information retrieval , evaluation, combining systems, and other advanced topics as time permits. CMPSCI 670: Computer VisionProfessor: LearnedMiller, HansonPeople are able to infer the characteristics of a scene or object from an image of it. In this course, we will study what is involved in building artificial systems which try to infer such characteristics from an image. Topics include: Basics of image formation  the effect of geometry, viewpoint, lighting and albedo on image formation. Basic image operations such as filtering, convolution and correlation. Frequency representations of images. The importance of scale in images. Measurements of image properties such as color, texture, appearance and shape. Inference of motion and structure from moving objects and images. Detecting and recognizing objects in images. Statistical methods in computer vision. This course is the graduate version of CMPSCI 570(591A) and it requires more work compared to the undergraduate version CMPSCI 570(591A). Prerequisite: Linear algebra, calculus, basic knowledge of probability, and an ability to program. 3 credits. CMPSCI 677: Operating SystemsProfessor: ShenoyThis course provides an indepth examination of principles of distributed operating systems. Covered topics include processes and threads, concurrent programming, distributed interprocess communication, distributed process scheduling, shared virtual memory, distributed file systems. Indepth examples will be taken from current operating systems such as UNIX and MACH. Some coverage of operating system principles for multiprocessors will also be included. Prerequisites: The student should be able to easily program in a highlevel language such as C, have had a course on data structures, be familiar with elements of computer architecture and have had previous exposure to the operating system concepts of processes, virtual memory, and scheduling. A previous course on uniprocessor operating systems (e.g., CMPSCI 377) will be helpful but not required. 3 credits. CMPSCI 677X: Operating SystemsProfessor:PEEAS. CMPSCI 691BB: Seminar  Intrinsically Motivated Reinforcement LearningProfessor: BartoCuriosity is a conspicuous feature of human behavior: we spontaneously explore and manipulate our surroundings to see what we can make them do; we obtain enjoyment from making discoveries and for making things happen. We often engage in these activities for their own sakes rather than as steps toward solving practical problems. Psychologists call these intrinsically motivated behaviors because rewards are intrinsic in these activities instead of being due to the satisfaction of more primary biological needs. This seminar will examine the subject of intrinsic motivation from the perspectives of machine learning, the neuroscience of brain reward systems, and classical and contemporary psychological theories of motivation. The objective is to increase our understanding of how to design intrinsically motivated artificial agents. Computer Science graduate students or permission of the instructor. CMPSCI 691CC: Seminar Advanced Information AssuranceProfessor: LevineThis course provides an indepth examination of the fundamental principles of information assurance. While the companion course for undergraduates is focused on practical issues, the syllabus of this course is influenced strictly by the latest research. We will cover a range of topics, including authentication, integrity, confidentiality of distributed systems, network security, malware, privacy, intrusion detection, intellectual property protection, and more. Prerequisites: undergraduate background in computer science or 415. CMPSCI 691FX: Programming LanguagesProfessor:PEEAS course. CMPSCI 701: Advanced Computer Science TopicsProfessor: ImmermanThis is a 6 credit reading course corresponding to the master s project. The official instructor is the GPD although the student does the work with and is evaluated by the readers of his or her master s project. CMPSCI 711: Parallel Algorithms and ArchitecturesProfessor: AdlerThis offering of CMPSCI 711 will focus on randomization in algorithms.Our emphasis will be on broadly applicable techniques for analyzing randomization, as well as the use of randomization in specific problem domains where it is helpful, or, in some cases, essential. Some of the topics to be covered include the following:  Tail inequalities: Chernoff, Hoeffding, Azuma, Second moment method. The probabilistic method: basic counting arguments, Lovasz Local Lemma, derandomizations. Universal hashing. Markov Chains, Random walks, and Coupling Arguments. Random graphs. Entropy, Information, and Coding. Randomization in approximation algorithms.Evaluation. There will be approximately four problem sets, as well as a take home final exam. In addition, each student will be responsible for taking detailed lecture notes on some topic, to be distributed to the class. Prerequisite: CMPSCI 611 or consent of the instructor. 3 credits. CMPSCI 741: Complexity TheoryProfessor:The study of the resources required to solve different problems in various abstract models of computation. Sequential computation: Turing machines, nondeterminism, alternation, algebraic automaton theory. Parallel computation: Boolean circuits, branching programs, uniformity. Lower bounds for circuit models. Descriptive Complexity. Possible optional topics depending on student interest: Approximation of NPcomplete prob lems, interactive proofs, nonuniform finite automata, dynamic complexity. Prerequisite: CMPSCI 601 or permission of instructor. Intended for interested general graduate students as well as those concentrating in theory. Course format: Probably 23 problem sets, class presentation (may be survey or actual research, might lead to a synthesis paper). Textbook: Xeroxed notes and research papers. 3 credits. CMPSCI 791AA: Seminar  Computational Methods in Structural Molecular BiologyProfessor: BrockStructural molecular biology is a subfield of bioinformatics concerned with the structure and function of organic molecules. Computational methods have proven to be very useful in this domain. In this class interdisciplinary teams of students from computational and biological sciences will explore ongoing research crossing the boundary between these two fields. Topics include: protein structure prediction, protein folding, protein motion, molecular docking, haptic rendering, molecular dynamics. After literature review, students will explore novel research ideas. CMPSCI 791BB: Seminar  Advanced Machine LearningProfessor: MahadevanGeometry has always been central to machine learning. Conceptual advances in machine learning often emerge from new ways of modeling the geometric structure of hypotheses spaces. For example, kernel methods use a sparse dual representation that exploits the geometry of Hilbert spaces. New work in many areas of ML, from reinforcement learning to data mining and unsupervised learning, has begun to exploit the curved (nonEuclidean) geometry of many commonly used hypothesis spaces, with amazing speedups and performance improvement. Computational models of early development of the brain point increasingly to the role of early cortical layers as extracting the underlying geometry of the world from noisy sensors. This course will read and discuss papers from many parts of machine learning and other related areas, emphasizing the geometrical perspective. EXAMPLE TOPICS: geometrical foundations of kernel methods and graphical models, manifolds and information geometry, natural gradients, the geometric em algorithm, Fisher kernels and feature discovery using tangent spaces, optimization and duality in Banach and Hilbert spaces, nonEuclidean reinforcement learning, the geometry of relational learning, geometry and models of development of the brain, applications to bioinformatics, robotics, sensor networks, signal processing, and relational/text data mining. Students will be expected to read and present recent papers from the literature, and actively participate in class discussions. PREREQUISITE: CMPSCI 689. CMPSCI 791CC: Seminar  Recent Results in Distributed SystemsProfessor: ** Section DeletedThis seminar class will discuss papers that cover a range of topics such as replication, content distribution and caching, peertopeer systems, Internet architecture, and fault tolerance. The papers will be selected from recent SOSP, SIGCOMM, PODC, and OSDI among others with some classical papers for background reading. Students will be expected to be familiar with basic networking and distributed systems concepts.The class may be either taken for one or three credits. The onecredit option will primarily involve reading and presenting papers and participating in class discussions. Students should expect to present at least one paper in class, and more depending on the size of the class. Students taking the class for three credits will additionally have to complete a final project on a topic of their choice. CMPSCI 791T: Seminar  Mathematical Topics for Distributed Sensor Data ProcessingProfessor: Towsley, GanesanThe focus of the course will be on reading and discussing recent work on (mainly) theoretical issues relating to many aspects of data processing in sensor networks. Some of the broad areas that we will be reading papers on as part of this course will be: Information Theory: SlepianWolf and other sensor data coding techniques, compression techniques for time and space, basestation assisted compression. Machine Learning: Techniques for learning models of data within the network. Dealing with missing data, outliers, building online models of data, modeldriven aggregation. Bayesian Inference: informationdriven routing. Estimation Theory: Distributed parameter estimation for various detection problems, estimating phenomena characteristics. Data summarization and aggregation: aggregation techniques including solving functions on data in a distributed manner. Statistical Signal Processing: Classifiers and their use in sensor data management. Predictionbased Techniques: Adaptive sampling, predictive synchronization. Computational Geometry: connectivity, coverage, routing. The course prerequisites includes a course on networking and reasonable statistics and/or probability sophistication. CMPSCI 891S: Theory of ComputationProfessor: ** Section DeletedLectures on various topics in the theory of computation by CMPSCI theory faculty, possible guest speakers, and seminar students. May be repeated for credit. Prerequisite: Graduate standing in CMPSCI or permission of the instructor. 1 credit. CMPSCI 899: PhD DissertationProfessor: StaffCMPSCI H01: Honors Colloquium for CMPSCI 201Professor: ** Section DeletedSeveral concepts are explored in more depth than is possible in the CMPSCI 201 lectures and discussions. Readings are assigned and explored in onceaweek discussion sessions. Students are assigned projects using an Intel I86 based computer, such as the IBM PC, that requires application of the material discussed in both the CMPSCI H01 weekly discussions and in CMPSCI 201. Grades are based on semester projects, written reports, participation in the weekly H01 discussions, and the application of discussed concepts in the assigned projects. Registration in CMPSCI 201 is required. CMPSCI H03: Honors Colloquium for CMPSCI 320Professor: FisherIn this course, students learn and gain practical experience with software engineering principles and techniques. The practical experience centers on a semesterlong team project in which a software development project is carried through all the stages of the software life cycle. Honors students will be expected to assume responsibility for some of the more complex aspects of the project as well as to study more advanced concepts. 1 credit. CMPSCI H06: Honors Colloquium for CMPSCI 521Professor: ClarkeThis course explores testing and analysis techniques for software systems, particularly large, complex systems used in safety applications such as medical devices and air traffic control. Honors students will work with the instructor on special projects, depending on their individual interests and opportunities that arise. For example, students might help implement or enhance a specific technique, conduct an experimental study using a small number of techniques, or design a quality assurance plan for a company or project. Recommended for Juniors and Seniors; Majors. 1 credit. CMPSCI H07: Honors Colloquium for CMPSCI 401Professor: RosenbergStudents will study additional topics in computability and complexity, through discussions (1 hour/week with professor), readings, and exercises. Specific topics will depend on student interest but may include algebraic automata theory, alternate models of computability, and interactive proofs. 1 credit. CMPSCI H08: Honors Colloquium for CMPSCI 383Professor: ZilbersteinHonors section will involve advanced study and implementation of one of the AI techniques covered in CMPSCI 383. The particular application will be determined based on student interest. Possible projects include game playing, automated information gathering over the internet, software agents, hierarchical planning systems, satisficing reasoning techniques. Recommended for Juniors and Seniors; Majors and Nonmajors. 1 credit. CMPSCI H09: Honors Colloquium for CMPSCI 530Professor: WiledenThe Honors section will meet with the instructor one hour per week to conduct additional exploration in the area of programming languages. Programming projects are also possible if student interest allows. 1 credit. CMPSCI H11: Honors Colloquium for CMPSCI 250Professor: BarringtonCMPSCI H14: Honors Colloquium for CMPSCI 453Professor: KuroseThis course provides an introduction to fundamental concepts in the design and implementation of computer communication networks, their protocols, and applications. Topics to be covered include: layered network architectures, applications, network programming interfaces (e.g., sockets), transport, congestion, routing, and data link protocols, local area networks, emerging highspeed networks, network management, and network security. Examples will be drawn primarily from the Internet (e.g., TCP, UDP, and IP) protocol suite. There will be written assignments, programming assignments (in C), one midterm, and a final exam. Prerequisites: A rudimentary understanding of computer architecture and operating systems, while not required, would be helpful. 1 credit. CMPSCI 691L: Seminar  Statistical Natural Language ProcessingProfessor: ** Section DeletedThis course surveys statistical approaches to the construction of tools for the automatic processing of human language. We begin with a presentation of the basic mathematical and linguistic principles necessary for the study of the statistical approaches that will be covered. We continue with the study of techniques for addressing issues encountered by applications containing natural language processing (NLP) components. These tasks include: determining the meaning of an ambiguous word (e.g. bank as a place to put money vs. bank as in river bank); identifying phrases and other ombinations of words that have a specialized meaning (e.g.: hit the hay); learning properties of words automatically from available bodies of text (e.g.: the recipient of contribute is expressed as a prepositional phrase with to); determining the parts of speech of the words in a sentence (e.g.: laugh is a verb in She makes me laugh, and a noun in She enjoys a good laugh); determining the higherlevel syntactic structure of a sentence; translating text from one language to another; classifying documents; and retrieving information from large text collections. 3 credits. Last automatic generation: 8/4/2005 at 12:40:51 PM 



