COMPUTER SCIENCE

600.105

M & Ms: FRESHMEN EXPERIENCE (1) Houlahan    Limit 20 Satisfactory/ Unsatisfactory only This course is required for all freshmen Computer Science majors. Transfers into the major and minors may enroll by permission only. Students will attend three 4-week blocks of meetings with different computer science professors, focused on a central theme. Active participation is required.

Sec. 01

Th 3-3:50

600.107 (E)

INTRODUCTION TO PROGRAMMING IN JAVA (3) Houlahan  Limit 120   Prereq: familiarity with computers  This course introduces the fundamental programming concepts and techniques in Java and is intended for all who plan to use computer programming in their studies and careers. Topics covered include control structures, arrays, functions, recursion, dynamic memory allocation, simple data structures, files, and structured program design. Elements of object-oriented design and programming are also introduced. Students without experience are strongly advised to also take 600.108.

Sec. 01

MW 3-4:15

600.108 (E)

INTRO PROGRAMMING LAB (1)
Houlahan  Limit 12/section
Co-req: 600.107
The purpose of this course is to give novice programmers extra hands-on practice with guided supervision. Students will work in pairs each week to develop working programs, with checkpoints for each development phase.   Satisfactory/Unsatisfactory only 

Sec. 01

02


03

W 6-9pm

Th 4:30-7:30pm

F 3-6pm

600.120 (E)

INTERMEDIATE PROGRAMMING (4) Froehlich  
Limit:
Sec. 01 – 10
Sec. 02 – 20
Prereq: 600.107 or AP CS  
This course covers intermediate to advanced programming in both C and C++. The focus of the course is on programming techniques, class design, and the use of class libraries. Topics to be covered include: polymorphism, overloading, inheritance, pointers, dynamic memory allocation, templates, collections, exceptions, and others as time permits. Students are expected to learn syntax and low-level language features independently. Coursework involves significant programming projects in both languages.

Lec.

Sec. 01

02

MWF 3-3:50

T 3-3:50

Th 3-3:50

600.226 (E,Q)

DATA STRUCTURES (3) Houlahan Limit 60  Prereq: 600.107 or AP CS This course covers the design and implementation of data structures including collections, sequences, trees, and graphs.  Other topics include sorting, searching, and hashing.  Course work involves both written homework and Java programming assignments.

Sec. 01

WF 12-1:15

600.271 (E,Q)

AUTOMATA & COMPUTATION THEORY (3) Kosaraju  Limit 60 Students may receive credit for either 600.271 or 600.471, but not both This course is an introduction to the theory of computing. Topics include design of finite state automata, pushdown automata, linear bounded automata, Turing machines and phrase structure grammars; correspondence between automata and grammars; computable functions, decidable and undecidable problems, P and NP problems, NP-completeness, and randomization.

Sec. 01

TTh 1:30-2:45

600.315 (E)

DATABASE SYSTEMS (3) Yarowsky  Limit 40  Prereq: 600.226    Students may receive credit for 600.315 or 600.415, but not both.   Introduction to database management systems and database design, focusing on the relational and object-oriented data models, query languages and query optimization, transaction processing, parallel and distributed databases, recovery and security issues, commercial systems and case studies, heterogeneous and multimedia databases, and data mining.

Sec. 01

TTh 3-4:15

600.320 (E)

PARALLEL PROGRAMMING (3) Burns   Limit 20   Prereq: 600.120 or equiv. Students may receive credit for 600.320 or 600.420, but not both. This course prepares the programmer to tackle the massive data sets and huge problem size of modern scientific and enterprise computing. Google and IBM have commented that undergraduate CS majors are unable to "break the single server mindset'' (http://www.google.com/intl/en/ press/pressrel/20071008_ibm_univ.html). Students taking this course will abandon the comfort of serial algorithmic thinking and learn to harness the power of cutting-edge software and hardware technologies. The issue of parallelism spans many architectural levels. Even ``single server'' systems must parallelize computation in order to exploit the inherent parallelism of recent multi-core processors. The course will examine different forms of parallelism in four sections. These are: (1) massive data-parallel computations with Hadoop!; (2) programming compute clusters with MPI; (3) thread-level parallelism in Java; and, (4) GPGPU parallel programming with NVIDIA's Cuda. Each section will be approximately 3 weeks and each section will involve a programming project. The course is also suitable for second-year undergraduate CS majors and undergraduate and graduate students from other science and engineering disciplines that have prior programming experience. [Systems]

Sec. 01

TTh 12-1:15

600.321 (E)

OBJECT ORIENTED SOFTWARE ENGINEERING (3) Smith   Limit 30   Prereq: 600.226 and 600.120  
Students receive credit for 600.321 or 600.421, but not both   This course covers object-oriented software construction methodologies and their application. The main component of the course is a large team project on a topic of your choosing. Course topics covered include object-oriented analysis and design, UML, design patterns, refactoring, program testing, code repositories, team programming, and code reviews.

Sec. 01

WF 1:30-2:45

600.333 (E)

COMPUTER SYSTEM FUNDAMENTALS (4) Mason   Limit 80Prereq: 600.107 or AP CS   Students may receive credit for 600.333 or 600.433, but not both. CSF addresses the design and performance of the principal operational components of a reduced-instruction-set computing system (RISC) which supports the efficient execution of widely used instruction sets. Arithmetic and logic units, memory hierarchy designs, state-machine controllers, and other related hardware and firmware components are studied, and the qualities of their combined processing capabilities are assessed by means of execution times associated with a range of benchmark programs. Assembly language programming projects, homework problems, and exams are employed to assess a student's fundamental understanding of the tradeoffs resulting from an assortment of variations in digital system design decisions that ultimately characterize the performance of the computing system architecture that is developed.

Sec. 01

MWF 10-10:50

600.361 (E,Q)

COMPUTER VISION (3) Hager Limit 20   Prereq: 600.226 This course gives an overview of fundamental methods in computer vision from a computational perspective. Methods include computation of 3-D geometric constraints from binocular stereo, motion, texture, shape-from-shading, and photometric stereo. Edge detection and color perception are studied as well. Elements of machine vision and biological vision are also included. [Applications] Course added 5/07/08

Sec. 01

TTh 3-4:15

600.363 (E,Q)

INTRODUCTION TO ALGORITHMS (3) Awerbuch   Limit 30   Prereq: 600.226 Students may receive credit for 600.363 or 600.463, but not both.   This course concentrates on the design of algorithms and the rigorous analysis of their efficiency. Topics include the basic definitions of algorithmic complexity (worst case, average case); basic tools such as dynamic programming, sorting, searching, and selection; advanced data structures and their applications (such as union-find); graph algorithms and searching techniques such as minimum spanning trees, depth-first search, shortest paths, design of online algorithms and competitive analysis.

Sec. 01

MW 12-1:15

600.392 (E)

SENIOR DESIGN PROJECT (3) Froehlich   Limit 30 Prereq: 600.120, 600.226; 600.321 recommended. CS senior majors only.  This course will give senior CS majors an intensive capstone design project experience. Students will work in groups with real world customers to develop a working system. Project design, management and communication skills will be emphasized. Software development methodologies may also be presented. [General]

Sec. 01

MWF 11-11:50

600.415 (E)

DATABASE SYSTEMS (3) Yarowsky   Limit 30   Prereq: 600.226   Students may receive credit for 600.315 or 600.415, but not both. Graduate level version of 600.315 Cross-listed with Information Security Institute

Sec. 01

TTh 3-4:15

600.420 (E)

PARALLEL PROGRAMMING (3) Burns   Limit 20   Prereq: 600.120 or equiv. Graduate level version of 600.320.  Student may receive credit for 600.320 or 600.420, but not both. [Systems]

Sec. 01

TTh 12-1:15

600.421 (E)

OBJECT ORIENTED SOFTWARE ENGINEERING (3) Smith   Limit 30   Prereq: 600.226 and 600.120    Students may receive credit for 600.321 or 600.421, but not both. Graduate level version of 600.321. Cross-listed with Information Security Institute

Sec. 01

WF 1:30-2:45

600.433 (E)

COMPUTER SYSTEMS (4) Masson  Limit 50  Students may receive credit for 600.333 or 600.433, but not both.  Graduate version of 600.333.    
Cross-listed with Information Security Institute

Sec. 01

MWF 10-10:50

600.443 (E)

SECURITY AND PRIVACY (3) Rubin   Limit 50   Prereq: A basic course in operating systems and networking, or permission of instructor. Lecture topics will include computer security, network security, basic cryptography, system design methodology, and privacy. There will be a heavy work load, including written homework, programming assignments, exams and a comprehensive final. The class will also include a semester-long project that will be done in teams and will include a presentation by each group to the class. [Applications] Cross-listed with Information Security Institute

Sec. 01

MW 1:30-2:45

600.445 (E)

COMPUTER - INTEGRATED SURGERY I (4) Taylor   Limit 40   Prereq: 600.120, 600.226 and linear algebra. Recmd: 600.457, 600.461, image processing.  This course focuses on computer-based techniques, systems, and applications exploiting quantitative information from medical images and sensors to assist clinicians in all phases of treatment from diagnosis to preoperative planning, execution, and follow-up. It emphasizes the relationship between problem definition, computer-based technology, and clinical application and includes a number of guest lectures given by surgeons and other experts on requirements and opportunities in particular clinical areas.

Sec. 01

TTh 1:30-2:45

600.450 (E)

NETWORK EMBEDDED SYSTEMS AND SENSOR NETWORKS (3) Terzis Limit 40   Prereq: 600.226, 600.120, and 600.344/444   (This course replaces 600.349/449.) This course is an introduction to fundamental concepts of networked embedded systems and wireless sensor networks. It is intended for juniors, seniors and first year graduate students in Computer Science and other engineering majors with the prerequisite background. Covered topics include: embedded systems programming concepts, low power and power aware design, radio technologies, communication protocols for ubiquitous computing systems, and some of the mathematical foundation of sensor behavior. Laboratory work consists of a set of programming assignments that consider a set of the issues described in class.  Cross-listed with Information Security Institute

Sec. 01

TTh 1:30-2:45

600.451 (E)

PERFORMANCE OF COMPUTER-COMMUNICATION NETWORKS AND PROTOCOLS (3) Mishra  Limit 40 Prereq: 600.344/333 & 550.310 This is an advanced course in networks and protocols that examines the performance evaluation, design, and management of networks, including wireless networks. This course may have additional newer topics such as network calculas and randomized algorithms as well other algorithms for networking. The course uses analytical and simulation methods to evaluate, design and manage networks and protocols. Topics include introduction to and application of queuing theory, queueing networks, introduction to and application of graph theory, optimization techniques for routing and flow control; intoduction to and application of simulation methods; performance of multiple access, TCP/IP, Wireless Cellular, Ad hoc and Sensor Networks; design of backbone and access networks.  [Analysis]  Course added 5/07/08

Sec. 01

MW 1:30-2:45

600.461 (E,Q)

COMPUTER VISION (3) Hager Limit 20  Prereq: 600.226 Graduate version of 600.361. Students may receive credit for 600.361 or 600.461, but not both. [Applications] Course added 5/07/08

Sec. 01

TTh 3-4:15

600.463 (E,Q)

ALGORITHMS I (3) Awerbuch  Limit 30
Prereq: 600.226 or Perm. Req'd.  Students may receive credit for 600.463 or 600.363, but not both   Graduate version of 600.363.        
Cross-listed with Information Security Institute

Sec. 01

MW 12-1:15

600.465 (E)

NATURAL LANGUAGE PROCESSING (3) Eisner Limit 60   Prereq: 600.226 Previous exposure to probability or linguistics may be helpful.   This course is an in-depth overview of techniques for processing human language. How should linguistic structure and meaning be represented? What algorithms can recover them from text? And crucially, how can we build statistical models to choose among the many legal answers? The course covers methods for trees (parsing and semantic interpretation), sequences (finite-state transduction such as morphology), and words (sense and phrase induction), with applications to practical engineering tasks such as information retrieval and extraction, text classification, part-of-speech tagging, speech recognition and machine translation. There are a number of structured but challenging programming assignments.

Sec. 01

MWF 3-3:50

600.471 (E,Q)

THEORY OF COMPUTATION (3) Hohenberger   Limit 40   Prereq: 550.171 or equiv.  This is a graduate-level course studying the theoretical foundations of computer science. Topics covered will be models of computation from automata to Turing machines, computability, complexity theory, randomized algorithms, inapproximability, interactive proof systems and probabilistically checkable proofs. Students may not receive credit for 600.271 and 600.471. [Analysis]   Cross-listed with Information Security Institute

Sec. 01

TTh 1:30-2:45

600.475 (E)

MACHINE LEARNING (3) Sheppard   Limit 20    Prereq: 600.335/435 or permission of instructor.
This course covers current topics in machine learning research. After a brief historical review, the class focuses on a series of different learning models, including memory-based learning, genetic algorithms, and neural net learning algorithms. The class considers the design and methodology of experiments used to test and compare different machine learning systems. Although the main focus is on experimental work, the course also examines theoretical work on distribution-free learning models. Students in the course design their own machine learning system as a final project. [Applications]

Sec. 01

MWF 10-10:50

600.490 (E)

MODERN SOFTWARE DEVELOPMENT FOR SCIENTISTS AND ENGINEERS (3) Hohenberger   Limit 20 Graduate students only; not CS, CE Prereqs: intro programming; recommended: data structures, basic familiarity with Unix. This course provides a broad survey of modern software development tools and methods for scientists and engineers working outside of computer science and computer engineering. Topics will include: programming style and documentation practices, software development processes, configuration management, object-oriented analysis and design, essential algorithms and data structures, software testing and quality assurance, performance analysis and tuning, automation of development activities, and a number of widely used libraries for scientific computation and visualization. Restrictions: graduate students only; not for CS or CE students. Course added 5/07/08

Sec. 01

02

MTW 12-12:50

MWThF 12-12:50

COMPUTER SCIENCE WORKSHOP I An applications-oriented, computer science project done under the supervision and with the sponsorship of a faculty member in the Department of Computer Science. Permission of faculty supervisor required
01 – Masson
02 – Kosaraju
03 – Awerbuch
04 – Taylor
05 – Smith
06 – Houlahan
07 – Lehmann
08 – Sheppard
09 – Hager
10 – Chirikjian
11 – Khudanpur
12 – Amir
13 – Yarowsky
14 – Cowan
15 – Burns
16 – Eisner
17 – Shapiro
18 – Hohenberger
19 – Karchin
20 – Ateniese
21 – Rubin
22 – Monrose
23 – Terzis
24 – Scheinerman
25 – Winslow
26 – Kazhdan
27 – Jelinek
28 – Froehlich
29 – Szalay
30 – Kazanzides

600.501

INDEPENDENT STUDY (FRESHMEN, SOPHOMORES)   Individual, guided study under the direction of a faculty member in the department. The program of study, including the credit to be assigned, must be worked out in advance between the student and the faculty member involved. Permission required. See 600.491 for faculty section numbers.

600.503

INDEPENDENT STUDY (JUNIORS, SENIORS)   Individual guided study under the direction of a faculty member in the department. The program of study, including the credit to be assigned, must be worked out in advance between the student and the faculty member involved. Permission required. See 600.491 for faculty section numbers.

600.507

INDEPENDENT RESEARCH
Individual research under the direction of a faculty member in the department. The program of research, including the credit to be assigned, must be worked out in advance between the student and the faculty member involved. Permission required. See 600.491 for faculty section numbers.

600.509

COMPUTER SCIENCE INTERNSHIP Individual work in the field with a learning component, supervised by a faculty member in the department. The program of study and credit assigned must be worked out in advance between the student and the faculty member involved. Students may not receive credit for work that they are paid to do. As a rule of thumb, 40 hours of work is equivalent to one credit. Perm. Req’d.  See 600.491 for faculty section numbers

600.519

SENIOR HONOR THESIS (3) Prereq: 3.5 GPA in C.S. courses at end of junior year and permission of faculty sponsor - C.S. majors only - See 600.491 for faculty section numbers The student will undertake a substantial independent research project under the supervision of a faculty member, potentially leading to the notation "Departmental Honors with Thesis" on the final transcript. Students are expected to enroll in both semesters of this course during their senior year. Project proposals must be submitted and accepted in the preceding spring semester (junior year) before registration. Students will present their work publicly before April 1st of senior year. They will also submit a first draft of their project report (thesis document) at that time. Faculty will meet to decide if the thesis will be accepted for honors.

600.546 (E)

SENIOR THESIS IN COMPUTER INTEGRATED SURGERY   Taylor
Prereq: 600.445 or Perm Req’d   

600.601

COMPUTER SCIENCE SEMINAR Eisner/Thornton Limit 150  Required for all full-time CS Graduate students 

Sec. 01

TTh 10:30-12

600.625

COMPUTER AND NETWORK FORENSICS Monrose  
Limit 10 (Undergrad)
Limit 15 (Grad)   
Prereq: Exposure to operating systems concepts and low-level system programming is assumed, or instructor permission.  The course exposes students to a myriad of fundamental concepts and techniques for recovering and inferring information in computer systems and networks. topics include (but are not limited too) file system forensics, kernel-level rootkits and associated challenges, reconstructing malware evolution and dynamics, analysis of anonymization and privacy preserving techniques, advanced network traceback, traffic classification, biometrics and digital evidence, data integrity and audit trails, secure remote logging, and system call introspection. A semester-long course project is required. Students will also be responsible for presenting and discussing selected research papers on topics pertinent to the course. Some familiarity with low-level system programming is assumed. [Applications] Course canceled 5/07/08

Sec. 01

MW 1:30-2:45

600.660

FFT IN GRAPHICS AND VISION Kazhdan  Limit 30  Prereq: Linear Algebra and comfort withmathematical derivations. In this course, we will study the Fourier Transform from the perspective of representation theory. We will begin by considering the standard transform defined by the commutative group of rotations in 2D and translations in two- and three-dimensions, and will proceed to the Fourier Transform of the non-commutative group of 3D rotations. Subjects covered will include correlation of images, shape matching, computation of invariances, and symmetry detection. [Applications or Analysis]

Sec. 01

MW 1:30-2:45

600.667

ADVANCED DISTRIBUTED SYSTEMS AND NETWORKS Amir   Limit 20  Prereq: 600.337/437 or permission of instructor.  This course is focused on the state of the art in distributed systems research, networks, and the Internet. The course is managed as a discussion group where the professor and students present recent research topics, as well as design and implement useful semester-long projects.

Sec. 01

MW 3-4:15

600.681

ADVANCED TOPICS IN COMPUTER VISION Vidal Limit 20   Prereq: 600.461 & linear algebra or permission. State-of-the-art methods in dynamic vision, with an emphasis on segmentation, reconstruction and recognition of static and dynamic scenes. topics include: reconstruction of static scenes (tracking and correspondence, multiple view geometry, self calibration), reconstruction of dynamic scenes (2-D and 3-D motion sementation, nonrigid motion analysis), recognition of visual dynamics (dynamic textures, face and hand gestures, human gaits, crowd motion analysis), as well as geometric and statistical methods for clustering and unsupervised learning, such as K-means, Expectation Maximization, and Generalized Principal Component Analysis. Applications in robotics and biomedical imaging are also included. [Applications]
Cross-listed as 580.681, formerly 600.642.

Sec. 01

TTh 10:30-11:45

600.726

SEMINAR IN PROGRAMMING LANGUAGES Smith  Limit 20  Perm.Req’d  This seminar course covers recent developments in the foundations of programming language design and implementation. Topics covered vary from year to year. Students will present papers orally.

Sec. 01

W 11-11:50

600.735

SEMINAR IN MACHINE LEARNING Sheppard   Limit 30   This seminar course will look at research in machine learning. topics will be selected from those of mutual interest between students and the instructor. Sample topics include reinforcement learning, kernel methods, experimental methods in machine learning, computational learning theory, lazy learning, evolutionary computation, and neural networks. Students are expected to select papers and lead discussion.

Sec. 01

Th 9-9:50

600.745

SEMINAR IN COMPUTER INTEGRATED SURGERY Etienne-Cummings/ Kazanzides Limit 20   This weekly seminar will focus on research issues in computer-integrated surgery, including subjects such as medical image analysis, statistical modeling, visualization, vision/sensing, surgical planning, medical robotics, and clinical applications. The purpose of the course is to widen the knowledge and awareness of the participants in current research in these areas, as well as to promote greater awareness and interaction between multiple research groups within the University and beyond. The format of the course is informal presentation by a pre-eminent invited speaker, followed by free discussion.  Co-listed as 520.744

Sec. 01

W 12-1:15

600.757

SEMINAR IN COMPUTER GRAPHICS Kazhdan   Limit 20  In this course we will review current research in computer graphics. We will meet for an hour once a week and one of the participants will lead the discussion for the week.

Sec. 01

TBA

600.765

SEMINAR IN NATURAL LANGUAGE PROCESSING Eisner   Limit 20 A reading group exploring important current research in the field and potentially relevant material from related fields. Enrolled students are expected to present papers and lead discussion.

Sec. 01

Th 12-12:50

600.766

SEMINAR IN MACHINE TRANSLATION Callison-Burch   Limit 20   The weekly machine translation reading group will review current research in statistical machine translation, and well as relevant historical papers. Enrolled students will present papers and lead discussions.

Sec. 01

F 11-11:50

600.801

DISSERTATION RESEARCH
See 600.809 for faculty section numbers

600.803

GRADUATE RESEARCH   Permission of faculty supervisor req’d.  Independent research for masters or pre-dissertation PhD students.  See 600.809 for faculty section numbers

600.809

INDEPENDENT STUDY (Graduate Students)   Permission required.  Individual study in an area of mutual interest to a graduate student and a faculty member in the department.
01 - Masson
02 - Kosaraju
03 - Awerbuch
04 - Taylor
05 - Smith
06 - Houlahan
07 - Lehmann
08 - Sheppard
09 - Hager
10 - Chirikjian
11 - Khudanpur
12 - Amir
13 - Yarowsky
14 - Cowan
15 - Burns
16 - Eisner
17 - Shapiro
18 - Hohenberger
19 - Karchin
20 - Ateniese
21 - Rubin
22 - Monrose
23 - Terzis
24 - Scheinerman
25 - Winslow
26 - Kazhdan
27 - Jelinek
28 - Froehlich
29 – Szalay
30 - Kazanzides