Fall 2011 Courses

600.104 (H)

COMPUTER ETHICS (1) Sheela Kosaraju

Students will examine a variety of topics regarding policy, legal, and moral issues related to the computer science profession itself and to the proliferation of computers in all aspects of society, especially in the era of the Internet. The course will cover various general issues related to ethical frameworks and apply those frameworks more specifically to the use of computers and the Internet. The topics will include privacy issues, computer crime, intellectual property law -- specifically copyright and patent issues, globalization, and ethical responsibilities for computer science professionals. Work in the course will consist of weekly assignments on one or more of the readings and a final paper on a topic chosen by the student and approved by the instructor.

Wed 6-8p, alternate weeks
limit 20, CS majors only

600.105

M&Ms: FRESHMAN EXPERIENCE (1) Selinski

This course is required for all freshmen Computer Science majors. Transfers into the major and minors may enroll by permission only. Students will attend four 3-week blocks of meetings with different computer science professors, focused on a central theme. Active participation is required. Satisfactory/Unsatisfactory only.

T 12
limit 30, CS majors only!

600.107 (E)

INTRO TO PROGRAMMING IN JAVA (3) Selinski

This course introduces fundamental structured and object-oriented programming concepts and techniques, using Java, and is intended for all who plan to use computer programming in their studies and careers. Topics covered include variables, arithmetic operations, control structures, arrays, functions, recursion, dynamic memory allocation, text files, class usage and class writing. Program design and testing are also covered, in addition to more advanced object-oriented concepts including inheritance and exceptions as time permits. First-time programmers are strongly advised to take 600.108 concurrently.

Prereq: familiarity with computers.

MW 1:30-2:45
limit 150

600.108 (E)

INTRO PROGRAMMING LAB (1) Selinski

Satisfactory/Unsatisfactory only. Must be taken in conjunction with 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.

Co-req: 600.107.

Sec 1: Wed 4:30-7:30p
Sec 2: Thu 6:00-9:00p
Sec 3: Fri 1:30-4:30p
limit 16/section

600.111 (E)

PYTHON SCRIPTING (3) Froehlich

For non-majors, this is an introductory "learning by doing" course focused on the quick prototyping of computational solutions to problems from a variety of disciplines. After an introduction to the UNIX and IDLE environments we briefly cover the basics of programming in Python. We then spend the rest of the semester surveying a variety of powerful Python libraries, frameworks, and tools. We use these building blocks to create, for example, systems for image and sound processing, data analysis and visualization, event-based simulation, or database-driven web applications. There will be several sizeable team-based programming projects. [Note: This course may not be used for the CS major or minor requirements, except perhaps as a substitute for 600.107.]

Prereq: none.

MWF 1:30
limit 40

600.120 (E)

INTERMEDIATE PROGRAMMING (4) Amir

This course teaches intermediate to advanced programming, using C and C++. (Prior knowledge of these languages is not expected.) We will cover low-level programming techniques, as well as object-oriented class design, and the use of class libraries. Specific topics include pointers, dynamic memory allocation, polymorphism, overloading, inheritance, templates, collections, exceptions, and others as time permits. Students are expected to learn syntax and some language specific features independently. Course work involves significant programming projects in both languages.

Prereq: AP CS, 600.107 or equivalent.

limit 15/section
Sec 1: MW 3-4:15, Tu 4:30-5:20
Sec 2: MW 3-4:15, Th 3-3:50
Sec 3: MW 4:30-5:45, Tu 4:30-5:20
Sec 4: MW 4:30-5:45, Th 3-3:50

600.211 (E)

UNIX SYSTEMS PROGRAMMING (3) Froehlich

This course covers a variety of topics in UNIX programming, including process control, signal handling, daemon processes, and interprocess communication. Participants must be familiar with using the UNIX environment and be fluent in the C programming language.

Prereq: 600.120.

MWF 3
limit 20

600.226 (E,Q)

DATA STRUCTURES (3) Selinski

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.

Prereq: AP CS or 600.107 or 600.120 or equivalent.

TuTh 3-4:15
limit 60

600.255 (E)

INTRODUCTION TO VIDEO GAME DESIGN (3) Froehlich

A broad survey course in video game design (as opposed to mathematical game theory), covering artistic, technical, as well as sociological aspects of video games. Students will learn about the history of video games, archetypal game styles, computer graphics and programming, user interface and interaction design, graphical design, spatial and object design, character animation, basic game physics, plot and character development, as well as psychological and sociological impact of games. Students will design and implement an experimental video game in interdisciplinary teams of 3-4 students as part of a semester-long project.

Prereq: sophomores and above, permission of instructor; Co-req: 600.256. Section 1 requires technical skills, including at least one programming course (preferably 2 or more). Section 2 requires artistic skills, including at least one multimedia course (preferably 2 or more).

MW 4:30-5:45
Sec 1: for technical students
Sec 2: for non-technical students
limit 20/section

600.256 (E)

INTRODUCTION TO VIDEO GAME DESIGN LAB (1) Froehlich

A lab course in support of 600.255: Introduction to Video Game Design covering a variety of multi-media techniques and applications from image processing, through sound design, to 3D modeling and animation. See 600.255: Introduction to Video Game Design for details about enrolling. Unlike in 600.255, the sections for the lab are meant to have a cross-section of students from different backgrounds. Ideally students working on a team project will be enrolled in the same lab section.

Co-req: 600.255.

Sec 1: M 6-9
Sec 2: T 6-9
Sec 3: W 6-9
Sec 4: H 6-9
limit 12/section

600.306 (E)

INTRODUCTION TO SPEECH (1) Church

This course will introduce students to speech from an interdisciplinary perspective including Computer Science, Electrical Engineering, Linguistics and Psychology. Topics such as pitch will be discussed from a variety of perspectives including signal processing (estimating fundamental frequency), perception, linguistics and computational linguistics. Vowels will be described from multiple perspectives ranging from distinctive features in linguistics to formants in signal processing. Students will become familiar with a variety of topics ranging from spectrogram reading to using XML to program phones and Python (NLTK) to find interesting patterns in text corpora. To reach a diverse interdisciplinary audience, no background experience is required. Short course.

Prereq: none.

Tu 1:30
limit 40

600.315 (E)

DATABASES (3) Yarowsky

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. [Systems]

Prereq: 600.226. Students may receive credit for 600.315 or 600.415, but not both.

TuTh 3-4:15
limit 30

600.320 (E)

PARALLEL PROGRAMMING (3) Burns

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 undergraduate and graduate students from other science and engineering disciplines that have prior programming experience. [Systems]

Prereq: 600.120 and 600.226; 600.333 recommended. Students may receive credit for 600.320 or 600.420, but not both.

MW 4:30-5:45
limit 30

600.321 (E)

OBJECT ORIENTED SOFTWARE ENGINEERING (3) Smith

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. [Systems or Applications]

Prereq: 600.226 and 600.120. Students may receive credit for 600.321 or 600.421, but not both.

MW 1:30-2:45
limit 40

600.333 (E)

COMPUTER SYSTEM FUNDAMENTALS (3) Masson

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. (See 600.334 for corresponding lab course.) [Systems]

Prereq: intro programming. Students may receive credit for 600.333 or 600.433, but not both.

MWF 10
limit 50

600.336 (E)

ALGORITHMS FOR SENSOR-BASED ROBOTICS (3) Hager

This is an introductory course presenting a series of algorithms related to the representation and use of geometric models acquired from sensor data. Course topics include: basic sensing and estimation techniques, geometric model representations, and motion planning algorithms. The course will also discuss applications in diverse areas such as mobile systems, robot manipulation, and medicine. [Analysis]

Prereq: 600.226, calculus, prob/stat. Students may receive credit for 600.336 or 600.436, but not both.

MWF 9
limit 30

600.361 (E,Q)

COMPUTER VISION (3) Padoy

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]

Prereq: 600.226 & linear algebra

TuTh 9-10:15
limit 20

600.415 (E)

DATABASES (3) Yarowsky

Graduate level version of 600.315. Students may receive credit for 600.315 or 600.415, but not both. [Systems]

Prereq: 600.226.

TuTh 3-4:15
limit 40

600.420 (E)

PARALLEL PROGRAMMING (3) Burns

Graduate level version of 600.320. Students may receive credit for 600.320 or 600.420, but not both. [Systems]

Prereq: 600.120 or equiv.

MW 4:30-5:45
limit 40

600.421 (E)

OBJECT ORIENTED SOFTWARE ENGINEERING (3) Smith

Graduate level version of 600.321. Students may receive credit for 600.321 or 600.421, but not both. [Systems or Applications]

Prereq: 600.226 and 600.120/121.

MW 1:30-2:45
limit 30

600.433 (E)

COMPUTER SYSTEMS (3) Masson

Graduate version of 600.333. Students may receive credit for 600.333 or 600.433, but not both. [Systems]

MWF 10
limit 20

600.436 (E)

ALGORITHMS FOR SENSOR-BASED ROBOTICS (3) Hager

Graduate level version of 600.336 (see description above). [Analysis]

Prereq: 600.226, calculus, prob/stat. Students may receive credit for 600.336 or 600.436, but not both.

MWF 9
limit 30

600.442 (E,Q)

MODERN CRYPTOGRAPHY (3) Pappacena

This course focuses on cryptographic algorithms, formal definitions, hardness assumptions, and proofs of security. Topics include number-theoretic problems, pseudo-randomness, block and stream ciphers, public-key cryptography, message authentication codes, and digital signatures. [Analysis]

Prerequisite: 600.226 and a 300-level or above systems course; 600.271/471 and 550.171 or equiv.

Tu 4:30-7:15
limit 20

600.443 (E)

SECURITY AND PRIVACY IN COMPUTING (3) Rubin

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]

Prerequisite: A basic course in operating systems and networking, or permission of instructor.

MW 1:30-2:45
limit 30

600.445 (E)

COMPUTER INTEGRATED SURGERY I (4) Taylor

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. [Applications]

Prereq: 600.120, 600.226 and linear algebra. Recmd: 600.457, 600.461, image processing.

TuTh 1:30-2:45
limit 50

600.450 (E)

NETWORK EMBEDDED SYSTEMS AND SENSOR NETWORKS (3) Marcus Chang

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. [Systems]

Prerequisites: 600.226, 600.120 and 600.344/600.444.

TuTh 1:30-2:45
limit 20

600.461 (E,Q)

COMPUTER VISION (3) Padoy

Graduate version of 600.361. Students may receive credit for 600.361 or 600.461, but not both. [Applications]

Prereq: 600.226 & linear algebra

TuTh 9-10:15
limit 50

600.464 (E,Q)

RANDOMIZED ALGORITHMS (3) Kosaraju

Selected topics in algorithm design and analysis such as advanced data structures, amortization, graph algorithms, algebraic complexity, network flow, circulations, matching, randomization. [Analysis]

Prereq: 600.363 or 600.463. Students may receive credit for 600.464 or 600.664, but not both.

TuTh 1:30-2:45
limit 15

600.465 (E)

NATURAL LANGUAGE PROCESSING (3) Eisner

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. [Applications]

Prerequisite: 600.226. Previous exposure to probability or linguistics may be helpful.

MWF 3
limit 40

600.467 (E)

WIRELESS NETWORKS (3) Mishra

This course covers the basics of mobile communication and wireless networking for computer science majors by keeping a balance between communication and networking topics. In this course the students will be exposed to wireless transmission fundamentals (path loss, shadowing, modulation, coding and channel models), wireless cellular networks (cellular concept, channel reuse, capacity limits, and cellular systems such as GSM, GPRS and UMTS), and learn about mobile network and transport layers, medium access control protocols, wireless local area networks (IEEE 802.11) , wireless mesh networks (IEEE 802.16), and emerging dynamic spectrum access networks based on cognitive radios. [Systems]

Prerequisites: 600.344/444 or equivalent.

TuTh 12-1:30
limit 20

600.471 (EQ)

NEW!!

THEORY OF COMPUTATION (3) Variyam

This is a graduate-level course studying the theoretical foundations of computer science. Topics covered will be models of com-putation from automata to Turing machines, computability, complexity theory, randomized algorithms, inapproximability, interactive proof systems and probabilistically checkable proofs. Students may not take both 600.271 and 600.471, unless one is for an undergrad degree and the other for grad. [Analysis]

Prereq: discrete math or permission.

TuTh 12-1:15
limit 40

600.475 (E)

MACHINE LEARNING (3) Dredze

This course takes an application driven approach to current topics in machine learning. The course covers supervised learning (classification/structured prediction/regression/ranking), unsupervised learning (dimensionality reduction, bayesian modeling, clustering) and semi-supervised learning. Additional topics may include reinforcement learning and learning theory. The course will also consider challenges resulting from learning applications, such as transfer learning, multi-task learning and large datasets. We will cover popular algorithms (naive Bayes, SVM, perceptron, HMM, winnow, LDA, k-means, maximum entropy) and will focus on how statistical learning algorithms are applied to real world applications. Students in the course will implement several learning algorithms and develop a learning system for a final project. [Applications]

Prereq: multivariate calculus.

MW 12-1:15
limit 40

600.491 (E)

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.

Perm. of faculty supervisor req'd.

See below for faculty section numbers

600.503

INDEPENDENT STUDY

Individual, guided study for undergraduate students 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 below for faculty section numbers

600.507

INDEPENDENT RESEARCH

Independent research for undergraduates 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 below 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. S/U only. Permission required.

See below for faculty section numbers

600.519

SENIOR HONORS THESIS (3)

For computer science majors only. 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 publically 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.

Prereq: 3.5 GPA in Computer Science after spring of junior year and permission of faculty supervisor.

See below for faculty section numbers

600.546 (E)

SENIOR THESIS IN COMPUTER INTEGRATED SURGERY (3)

The student will undertake a substantial independent research project in the area of computer-integrated surgery, under joint supervision of a WSE faculty adviser and a clinician or clinical researcher at the Johns Hopkins Medical School.

Prereq: 600.445 or perm req'd.

Section 1: Taylor

600.601

COMPUTER SCIENCE SEMINAR

Required for all full-time PhD students. Recommended for MSE students.

TuTh 10:30-12
limit 150

520.702

CURRENT TOPICS IN LANGUAGE AND SPEECH PROCESSING Khudanpur

CLSP seminar series, for any students interested in current topics in language and speech processing.

Tu 4:30-5:45 & Fr 12-1:15
limit 30

600.615

BIG DATA, SMALL LANGUAGES, SCALABLE SYSTEMS Yanif Ahmad

This class will study domain-specific data management tools, focusing on extremely scalable system design based on the domain's semantic and structural properties. We will study a variety of data models including stream, graph, array and probabilistic data, and their processing on modern architectures such as column- and key-value stores, stream and XQuery engines. Further topics include the use of novel hardware such as solid state disks, phase change memory, GPUs, and FPGAs. The class includes a semester long group project to develop a query processor for an application of the group's choice (e.g. on system log, finance, web, sensor, speech data). [Systems]

Pre-req: 600.315/415 or equivalent.

WF 12-1:15
limit 30

600.657

ADVANCED TOPICS FOR COMPUTER GRAPHICS (3) Kazhdan

This course presents advanced methodologies and their applications to computer graphics. Fall 2011 will focus on the physically-based rendering. The course will closely follow the book by Pharr and Humphreys, and will look at topics including efficient shape intersection, lighting and reflectance, Monte Carlo integration, etc. In addition to reading and lectures, students will also be expected to develop a high-quality renderer for visualizing 3D models. [Applications]

Prereq: any 600.4xx course in computer graphics & linear algebra; or permission of instructor.

TuTh 3-4:15
limit 15

600.664

RANDOMIZED ALGORITHMS (3) Kosaraju

Graduate level version of 600.464. [Analysis]

Prereq: 600.363 or 600.463. Students may receive credit for 600.464 or 600.664, but not both.

TuTh 1:30-2:45
limit 10

600.726

SELECTED TOPICS IN PROGRAMMING LANGUAGES Smith

This 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.

Prereq: permission of instructor

Wed 11
limit 20

600.728

NEW!!

SELECTED TOPICS IN CATEGORY THEORY Smith

Students in this course will read a sampling of standard texts in Category Theory (e.g. the books by Awodey, Mac Lane, Pierce, or others) and papers relevant to the research of participants.

Prereq: permission of instructor

Wed 10
limit 15

600.735

CANCELLED

SELECTED TOPICS IN MACHINE LEARNING (1) Sheppard

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.

CANCELLED
limit 20

600.745

SEMINAR IN COMPUTATIONAL SENSING AND ROBOTICS Kazanzides

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 with 500.745.]

Wed 12-1:30
limit 80

600.754

SELECTED TOPICS IN STATISTICAL ANATOMIC MODELS, REGISTRATION, AND RECONSTRUCTION Taylor

This weekly research seminar will focus generally on statistical modeling of anatomic structures, image and model registration, 3D image reconstruction methods, and their interrelationships. We will concen-trate primarily, though not exclusively, on x-ray based imaging modalities (x-ray fluoroscopy, CT, cone-beam tomography, "hybrid" reconstruction methods, etc.).

CANCELLED
limit 15

600.757

SELECTED TOPICS IN COMPUTER GRAPHICS Kazhdan

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.

tba
limit 20

600.763

NEW!

SELECTED TOPICS IN STREAMING ALGORITHMS Braverman

This course will focus on theoretical streaming algorithms and related methods. Examples of topics that we will address include sketching, sampling, frequency moments, heavy elements, k-wise independence, and the Johnson-Lindenstrauss lemma. Students will be required to select a paper and lead a discussion. This course is a good opportunity for motivated students to learn modern algorithmic methods. Prereq: 600.463 or equivalent.

Mon 11
limit 15

600.765

SELECTED TOPICS IN NATURAL LANGUAGE PROCESSING Eisner

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.

Th 12
limit 20

600.766

SELECTED TOPICS IN MEANING, TRANSLATION AND GENERATION OF TEXT Callison-Burch& VanDurme

This weekly reading group will review current research and survey articles on the topics of computational semantics, statistical machine translation, and natural language generation. Enrolled students will present papers and lead discussions.

Tu 12:30-1:30
limit 20

600.801

DISSERTATION RESEARCH

See below for faculty section numbers.

600.803

GRADUATE RESEARCH

Independent research for masters or pre-dissertation PhD students. Permission required.

See below for faculty section numbers.

600.809

INDEPENDENT STUDY (graduate students)

Permission required.

See below for faculty section numbers.