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.

We 6-8p, alternate weeks
limit 20, 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 operators, control structures, arrays, functions, recursion, dynamic memory allocation, files, class usage and class writing. Program design and testing are also covered, in addition to more advanced object-oriented concepts including inherit-ance 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 140

600.108 (E)

INTRO PROGRAMMING LAB (1) Selinski

Satisfactory/Unsatisfactory only. This course is intended for novice programmers, and must be taken in conjunction with 600.107. The purpose of this course is to give first-time 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. Prerequisite: familiarity with computers.

Co-Requisite: 600.107.

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

600.120 (E)

INTERMEDIATE PROGRAMMING (4) Froehlich

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 600.226.

MWF 12-1:15
limit 75

600.226 (E,Q)

DATA STRUCTURES (4) 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, 600.107 or 600.120.

MWF 3-4:15
limit 75

600.250 (E)

ADDED!

USER INTERFACES AND MOBILE APPLICATIONS (3) Froehlich

This course will provide students with a rich development experience, focused on the design and implementation of user interfaces and mobile applications. A brief overview of human computer interaction will provide context for designing, prototyping and evaluating user interfaces. Students will invent their own mobile applications and implement them using the Android SDK, which is JAVA based. An overview of the Android platform and available technologies will be provided, as well as XML for layouts, and general concepts for effective mobile development. Students will be expected to explore and experiment with outside resources in order to learn technical details independently. There will also be an emphasis on building teamwork skills, and on using modern development techniques and tools.

Prereq: 600.120 and 600.226.

MWF 3-3:50
limit 35

600.271 (E,Q)

AUTOMATA and COMPUTATION THEORY (3) Kosaraju

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. Students may not receive credit for 600.271 and 600.471 for the same degree.

TuTh 1:30-2:45
limit 75

600.316 (E)

DATABASE SYSTEMS (3) Ahmad

This course serves as an introduction to the architecture and design of modern database management systems. topics include query processing algorithms and data structures, data organization and storage, query optimization and cost modeling, transaction management and concurrency control, high-availability mechanisms, parallel and distributed databases, and a survey of modern architectures including NoSQL, column-oriented and streaming databases. Course work includes programming assignments and experimentation in a simple database framework written in Java. [Systems]

Prereq: 600.120 and 600.226. Students may receive credit for 600.316 or 600.416, but not both.

MW 12-1:15
limit 20

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

600.325 (E)

DECLARATIVE METHODS (3) Eisner

Suppose you could simply write down a description of your problem, and let the computer figure out how to solve it. What notation could you use? What strategy should the computer then use? In this survey class, you'll learn to recognize when your problem is an instance of satisfiability, constraint programming, logic programming, dynamic programming, or mathematical programming (e.g., integer linear programming). For each of these related paradigms, you'll learn to reformulate hard problems in the required notation and apply off-the-shelf software that can solve any problem in that notation -- including NP-complete problems and many of the problems you'll see in other courses and in the real world. You'll also gain some understanding of the general-purpose algorithms that power the software. [Analysis]

Prereq: 600.226, Calc II. Students can only receive credit for 600.325 or 600.425, not both.

MWF 3
limit 20

600.328 (E)

COMPILERS & INTERPRETERS (3) Froehlich

Introduction to compiler design, including lexical analysis, parsing, syntax-directed translation, symbol tables, run-time environments, and code generation and optimization. Students are required to write a compiler as a course project. [Systems]

Prereq: 600.120 & 600.226

MWF 10
limit 30

600.335 (E)

ARTIFICIAL INTELLIGENCE (3) Mitchell

Artificial intelligence (AI) is introduced by studying automated reasoning, automatic problem solvers and planners, knowledge representation mechanisms, game playing, machine learning, and statistical pattern recognition. The class is a recommended for all scientists and engineers with a genuine curiosity about the fundamental obstacles to getting machines to perform tasks such as deduction, learning, and planning and navigation. Strong programming skills and a good grasp of the English language are expected; students will be asked to complete both programming assignments and writing assignments. The course will include a brief introduction to scientific writing and experimental design, including assignments to apply these concepts. [Applications]

Prereq: 600.226, 550.171; Recommended: linear algebra, prob/stat. Students can only receive credit for 600.335 or 600.435, not both.

WF 12-1:15
limit 20

600.344 (E)

COMPUTER NETWORK FUNDAMENTALS (3) Haberman

This course considers intersystem communications issues. topics covered include layered network architectures; the OSI model; bandwidth, data rates, modems, multiplexing, error detection/correction; switching; queuing models, circuit switching, packet switching; performance analysis of protocols, local area networks; and congestion control. [Systems]

Prereq: 600.333 or 600.433 or permission. Students can only receive credit for 600.344 or 600.444, not both.

TuTh 9-10:15
limit 30

600.363 (E,Q)

INTRODUCTION TO ALGORITHMS (3) Braverman

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. [Analysis]

Prereq: 600.226 and 550.171 or Perm. Req'd. Students may receive credit for 600.363 or 600.463, but not both.

TuTh 1:30-2:45
Sec 01: F 2
limit 30

600.392 (E)

CANCELLED

CS DESIGN PROJECT (3) Froehlich

This course will give junior and senior CS majors an intensive 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]

Prereq: 600.120, 600.226; 600.321 recommended.

cancelled
limit 30, junior & senior CS majors only

600.402 (E)

MEDICAL INFORMATICS (1) Ochs

Advances in technology are driving a change in medicine. "Personalized Medicine" promises treatments tuned to the genetics of each individual. Computers and information technology will be critical to this transition. We shall discuss some of the coming changes in terms of computer technology, including genomic data management, computer-based patient records, and clinical practice guidelines, focusing on cancer as a paradigm. We will discuss the underlying technologies driving these developments - databases and warehouses, controlled vocabularies, and decision analysis. Prerequisite: none.

Short course meets 4 weeks 4/8-5/1

MW 4:30-5:45
4 weeks: 4/8-5/1
limit 30

600.416 (E)

DATABASE SYSTEMS (3) Ahmad

Similar material as 600.316, covered in more depth. Intended for upper-level undergraduates and graduate students. [Systems]

Prereq: 600.120 and 600.226. Students may receive credit for 600.316 or 600.416, but not both.

MW 12-1:15
limit 30

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

600.424 (E)

NETWORK SECURITY (3) Mishra

This course focuses on communication security in computer systems and networks. The course is intended to provide students with an introduction to the field of network security. The course covers network security services such as authentication and access control, integrity and confidentiality of data, firewalls and related technologies, Web security and privacy. Course work involves implementing various security techniques. A course project is required. [Systems]

Prereq: 600.226, 600.344/444 or permission; 600.120 (or equivalent) recommended.

F 3-5:30
limit 20

600.425 (E)

DECLARATIVE METHODS (3) Eisner

Graduate level version of 600.325. [Analysis]

Prereq: 600.226, Calc II. Students can only receive credit for 600.325 or 600.425, not both.

MWF 3
limit 20

600.426 (E,Q)

PRINCIPLES OF PROGRAMMING LANGUAGES (3) Smith

Functional, object-oriented, and other language features are studied independent of a particular programming language. Students become familiar with these features by implementing them. Most of the implementations are in the form of small language interpreters. Some type checkers and a small compiler will also be written. The total amount of code written will not be overly large, as the emphasis is on concepts. The ML programming language is the implementation language used. [Analysis]

Prereq: 600.226. Freshmen and sophomores by permission only.

MW 1:30-2:45
limit 40

600.428 (E)

COMPILERS & INTERPRETERS (3) Froehlich

Graduate level version of 600.328. Students may receive credit for 600.328 or 600.428, but not both. [Systems]

Prereq: 600.120 & 600.226

MWF 10:00
limit 30

600.435 (E)

ARTIFICIAL INTELLIGENCE (3) Mitchell

Graduate level version of 600.335. [Applications]

Prereq: 600.226, 550.171; Recommended: linear algebra, prob/stat. Students can only receive credit for 600.335 or 600.435, not both.

WF 12-1:15
limit 30

600.436 (E)

ALGORITHMS FOR SENSOR-BASED ROBOTICS (3) Hager

[Formerly 600.336.] This course surveys the development of robotic systems for navigating in an environment from an algorithmic perspective. It will cover basic kinematics, configuration space concepts, motion planning, and localization and mapping. It will describe these concepts in the context of the ROS software system, and will present examples relevant to mobile platforms, manipulation, robotics surgery, and human-machine systems. [Analysis]

Prereq: 600.226, linear algebra, probability. Students may receive credit for only one of 600.336, 600.436 and 600.636.

TuTh 12-1:15
limit 30

600.439 (E)
New!!

COMPUTATIONAL GENOMICS (3) Langmead

Your genome is the blueprint for the molecules in your body. It's also a string of letters (A, C, G and T) about 3 billion letters long. How does this string give rise to you? Your heart, your brain, your health? This, broadly speaking, is what genomics research is about. This course will familiarize you with a breadth of topics from the field of computational genomics. The emphasis is on current research problems, real-world genomics data, and efficient software implementations for analyzing data. Topics will include: string matching, sequence alignment and indexing, assembly, and sequence models. Course will involve significant programming projects. [Applications]

Prereq: 600.120 & 600.226.

MW 3-4:15
limit 8

600.444 (E)

COMPUTER NETWORKS (3) Haberman

Graduate level version of 600.344. [Systems]

Prereq: 600.333 or 600.433 or permission. Students can only receive credit for 600.344 or 600.444, not both.

TuTh 9-10:15
limit 30

600.446 (E)

COMPUTER INTEGRATED SURGERY II (3) Taylor

This weekly lecture/seminar course addresses similar material to 600.445, but covers selected topics in greater depth. In addition to material covered in lectures/seminars by the instructor and other faculty, students are expected to read and provide critical analysis/presentations of selected papers in recitation sessions. Students taking this course are required to undertake and report on a significant term project under the supervision of the instructor and clinical end users. Typically, this project is an extension of the term project from 600.445, although it does not have to be. Grades are based both on the project and on classroom recitations. Students wishing to attend the weekly lectures as a 1-credit seminar should sign up for 600.452. Students may also take this course as 600.646. The only difference between 600.446 and 600.646 is the level of project undertaken. Typically, 600.646 projects require a greater degree of mathematical, image processing, or modeling background. Prospective students should consult with the instructor as to which course number is appropriate. [Applications]

Prereq: 600.445 or perm req'd. Students may receive credit for 600.446 or 600.646, but not both.

TuTh 1:30-2:45
limit 35

600.452 (E)

COMPUTER INTEGRATED SURGERY SEMINAR (1) Taylor

Lecture only version of 600.446 (no project).

Prereq: 600.445 or perm req'd. Students may receive credit for 600.446 or 600.452, but not both.

TuTh 1:30-2:45
limit 5

600.463 (E,Q)

ALGORITHMS I (3) Braverman

Graduate version of 600.363. Students may receive credit for 600.363 or 600.463, but not both. [Analysis]

TuTh 1:30-2:45
Sec 01: F 2
limit 30

600.466 (E)

INFORMATION RETRIEVAL & WEB AGENTS (3) Yarowsky

An in-depth, hands-on study of current information retrieval techniques and their application to developing intelligent WWW agents. Topics include a comprehensive study of current document retrieval models, mail/news routing and filtering, document clustering, automatic indexing, query expansion, relevance feedback, user modeling, information visualization and usage pattern analysis. In addition, the course explores the range of additional language processing steps useful for template filling and information extraction from retrieved documents, focusing on recent, primarily statistical methods. The course concludes with a study of current issues in information retrieval and data mining on the World Wide Web. Topics include web robots, spiders, agents and search engines, exploring both their practical implementation and the economic and legal issues surrounding their use. [Applications]

Prereq: 600.226

TuTh 3-4:15
limit 60

600.476 (EQ)
New!!

MACHINE LEARNING IN COMPLEX DOMAINS (3) Saria

Alt title: How to Become a Data Ninja
How can robots locate themselves in an indoor environment when navigating? How do you infer which patients need attention first in the ICU? How can one identify the start of an epidemic using tweets? How does one predict the way a traffic jam will spread through the local streets during an Orioles game? How can you communicate with your TV using only hand gestures? This class will cover the fundamental concepts of Probabilistic Graphical Models as a representation framework for addressing questions like the ones above. We will study algorithms for model estimation, exact and approximate inference. The class will have 4 interactive sessions during which students will learn through an open discussion format how to think about example open-ended real-world problems with the tools learnt in class. Students are also required to tackle a project of their choice within which they will experiment with the ideas learnt in class. [Analysis or Applications] Students may receive credit for 600.476 or 600.676, but not both.

Pre-reqs: When in doubt, send the instructor a copy of your transcript to see if the class is appropriate for you. Also, sit through the first few sessions and first homework to get a sense of fit. 1) Students will be asked to do assignments in Matlab. Matlab is typically easy to pick up if one is already familiar with a different programming language. 2) Students are expected to be mathematically mature. One should have taken at least an introductory course in probability and linear algebra. Though not required, exposure to optimization or machine learning is recommended. 3) Proficiency in at least one programming language is expected.

MW 1:30-2:45
limit 5

600.488 (EN)

FOUNDATIONS OF COMPUTATIONAL BIOLOGY AND BIOINFORMATICS II (3) Karchin

[Co-listed with 580.488.] This course will introduce probabilistic modeling and information theory applied to biological sequence analysis, focusing on statistical models of protein families, alignment algorithms, and models of evolution. topics will include probability theory, score matrices, hidden Markov models, maximum likelihood, expectation maximization and dynamic programming algorithms. Homework assignments will require programming in Python. Foundations of Computational Biology I is not a prereq. [Analysis]

Prerequisites: math through linear algebra and differential equations, at least one statistics and probability course, 580.221 or equiv., 600.226 or equiv.

MW 4:30-5:45
limit 5

600.504

UNDERGRADUATE INDEPENDENT STUDY

For undergraduate students. Permission of faculty sponsor is required. See below for faculty section numbers.

600.508

UNDERGRADUATE RESEARCH

Permission of faculty sponsor is required. See below for faculty section numbers.

600.510

COMPUTER SCIENCE INTERNSHIP

Individual work in the field with a learning component, supervised by a faculty member in the department. The program of study 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, which is the limit per semester.

Permission of faculty sponsor is required.

See below for faculty section numbers.

600.520

SENIOR HONORS THESIS (3)

For computer science majors only, a continuation of 600.519.

Prerequisite: 600.519

See below for faculty section numbers.

600.546 (E)

SENIOR THESIS IN COMPUTER INTEGRATED SURGERY (3)

Prereq: 600.445 or perm req'd.

Section 01: Taylor

600.602

COMPUTER SCIENCE SEMINAR

Required for all CS PhD students. Strongly recommended for MSE students.

TuTh 10:30-12
limit 90

600.636

(E)

ALGORITHMS FOR SENSOR-BASED ROBOTICS Hager

[Formerly 600.436.] Graduate level version of 600.436 (see description above). [Analysis]

Prereq: 600.226, calculus, prob/stat. Students may receive credit for only one of 600.336, 600.436 or 600.636.

TuTh 12-1:15
limit 30

600.639
New!!

COMPUTATIONAL GENOMICS Langmead

Graduate version of 600.439. Students may earn credit for 600.439 or 600.639, but not both. [Applications]

Prereq: 600.120 & 600.226.

MW 3-4:15
limit 8

600.643

ADVANCED TOPICS IN COMPUTER SECURITY Rubin

Topics will vary from year to year, but will focus mainly on network perimeter protection, host-level protection, authentication technologies, intellectual property protection, formal analysis techniques, intrusion detection and similarly advanced subjects. Emphasis in this course is on understanding how security issues impact real systems, while maintaining an appreciation for grounding the work in fundamental science. Students will study and present various advanced research papers to the class. There will be homework assignments and a course project. [Systems or Applications]

Prereq: 600.443 or 600.424; or permission of instructor.

MW 1:30-2:45
limit 20

600.646

COMPUTER INTEGRATED SURGERY II Taylor

Advanced version of 600.446. [Applications]

Prereq: 600.445 or perm req'd. Students may receive credit for 600.446 or 600.646, but not both.

TuTh 1:30-2:45
limit 20

600.662
New!!

TOPICS IN ILLUMINATION AND REFLECTANCE MODELING FOR COMPUTER VISION AND MEDICAL IMAGING APPLICATIONS Wolff

The vast majority of all imagery on which computer vision is performed starts with a source of illumination in conjunction with a material reflectance property. Having a rigorous understanding of these phenomena is important for most students who want to be involved with further research in computer vision and computer integrated surgery, particularly for experimentation and development of new systems. This short course is for individuals who have already taken Computer Vision, and want to delve deeper into underlying physical modeling of light illumination, reflection, colorimetry, polarization and even sensor fusion of images taken at different wavelengths. Short Course: meets 4 weeks 2/1-3/1.

Prereq: 600.361/461 or perm req'd.

Fr 1:30-4
4 weeks 2/1-3/1
limit 20

600.666

INFORMATION EXTRACTION Khudanpur

Introduction to statistical methods of speech recognition (automatic transcription of speech) and understanding. The course is a natural continuation of 600.465 but is independent of it. topics include elementary information theory, hidden Markov models, the Baum and Viterbi algorithms, efficient hypothesis search methods, statistical decision trees, the estimation-maximization (EM) algorithm, maximum entropy estimation and estimation of discrete probabilities from sparse data for acoustic and language modeling. Weekly assignments and several programming projects. [Applications]

Prerequisites: 550.310 or equivalent, expertise in C or C++ programming. Co-listed with 050.666 and 520.666.

??
limit 15

600.667

ADVANCED DISTRIBUTED SYSTEMS AND NETWORKS Amir

The course explores the state of the art in distributed systems, networks and Internet research and practice, trying to see what it would take to push the envelop a step further. The course is conducted as a discussion group, where the professor and students brainstorm and pick interesting semester-long projects with high potential future impact. Example areas include robust scalable infrastructure (distributed datacenters, cloud networking, scada systems), real-time performance (remote surgery, trading systems), hybrid networks (mesh networks, 3-4G/Wifi/Bluetooth). Students should feel free to bring their own topics of interest and ideas. [Systems]

Prereq: a systems course (distributed systems, operating systems, computer networks, parallel programming), or permission of instructor.

TuTh 3-4:15
limit 15

600.668

New!!

ADVANCED TOPICS IN SOFTWARE SECURITY Checkoway

[Co-listed with 650.668] Topics vary but mainly focus on recent advances in exploitation techniques and defenses for software including software running on embedded systems software, browsers, and nontraditional devices such as microcontrollers in PCs. [Systems]

Prereq: 600.460 or 650.442, or permission of instructor.

TuTh 1:30-2:45
limit 30

600.676
New!!

MACHINE LEARNING IN COMPLEX DOMAINS Saria

Alt title: How to Become a Data Ninja
Graduate version of 600.476. [Analysis or Applications] Students may receive credit for 600.476 or 600.676, but not both.

Pre-reqs: When in doubt, send the instructor a copy of your transcript to see if the class is appropriate for you. Also, sit through the first few sessions and first homework to get a sense of fit. 1) Students will be asked to do assignments in Matlab. Matlab is typically easy to pick up if one is already familiar with a different programming language. 2) Students are expected to be mathematically mature. One should have taken at least an introductory course in probability and linear algebra. Though not required, exposure to optimization or machine learning is recommended. 3) Proficiency in at least one programming language is expected.

MW 1:30-2:45
limit 20

600.688

FOUNDATIONS OF COMPUTATIONAL BIOLOGY AND BIOINFORMATICS II Karchin

[Co-listed with 580.688.] Graduate version of 600.488. Foundations of Computational Biology I is not a prereq. [Analysis]

Prerequisites: math through linear algebra and differential equations, at least one statistics and probability course, 580.221 or equiv., 600.226 or equiv.

MW 4:30-5:45
limit 20

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

600.716
NEW!!

SELECTED TOPICS ON INNOVATIVE DATA SYSTEMS Ahmad

This weekly reading group will survey and dissect the cutting-edge on innovative data systems research. Topics will encompass methods and abstraction in core systems and data management areas (e.g., cloud computing, scalable programming and storage), as well as use-cases and "war" stories from industry, and science and engineering applications. Our semester schedule is posted at damsel.cs.jhu.edu/blockparty.

Th 1:30-2:30

600.726

SELECTED TOPICS IN PROGRAMMING LANGUAGES Smith

This seminar course covers recent developments in the foundations of programming language design and implementation. topics covered include type theory, process algebra, higher-order program analysis, and constraint systems. Students will be expected to present papers orally.
Prereq: permission of instructor

Wed 10-12

600.728

SELECTED TOPICS IN CATEGORY THEORY Filardo

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

W 4:30-5:30

600.745

SEMINAR IN COMPUTATIONAL SENSING AND ROBOTICS Kazanzides

Seminar series in robotics. topics include: Medical robotics, including computer-integrated surgical systems and image-guided intervention. Sensor based robotics, including computer vision and biomedical image analysis. Algorithmic robotics, robot control and machine learning. Autonomous robotics for monitoring, exploration and manipulation with applications in home, environmental (land, sea, space), and defense areas. Biorobotics and neuromechanics, including devices, algorithms and approaches to robotics inspired by principles in biomechanics and neuroscience. Human-machine systems, including haptic and visual feedback, human perception, cognition and decision making, and human-machine collaborative systems. Cross-listed Mechanical Engineering, Computer Science, Electrical and Computer Engineering, and Biomedical Engineering.

W 12-1:15
limit 60

600.746

SELECTED TOPICS IN MEDICAL IMAGE ANALYSIS Taylor & Prince

This weekly seminar will focus on research issues in medical image analysis, including image segmentation, registration, statistical modeling, and applications. It will also include selected topics relating to medical image acquisition, especially where they relate to analysis. The purpose of the course is to provide the participants with a thorough background in current research in these areas, as well as to promote greater awareness and interaction between multiple research groups within the University. The format of the course is informal. Students will read selected papers. All students will be assumed to have read these papers by the time the paper is scheduled for discussion. But individual students will be assigned on a rotating basis to lead the discussion on particular papers or sections of papers. Co-listed with 520.746.

Tu 3-4:50

600.764

SEMINAR IN ALGORITHMS Braverman

This course will explore algorithms and theoretical computer science with a focus on algorithms for massive data. Examples of topics include streaming algorithms, approximation algorithms, online algorithms. Students will be encouraged to select a paper and lead a discussion. External speakers will be invited to present current work as well. This course is a good opportunity for motivated students to learn modern algorithmic methods. Prereq: 600.463 or equivalent.

Fr 3
limit 20

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.

Pre-req: 600.465 or permission of instructor.

Th 12-1:15

600.766

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

The weekly machine translation 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.

Fr 10:30(was Tu 12-1)

600.775

DATA INTENSIVE COMPUTING & MACHINE LEARNING SEMINAR Dredze

This seminar is recommended for all students interested in data intensive computing research areas (e.g., machine learning, computer vision, natural language processing, speech, computational social science). The meeting format is participatory. Papers that discuss best practices and the state-of-the-art across application areas of machine learning and data intensive computing will be read. Student volunteers lead individual meetings. Faculty and external speakers present from time-to-time.

Pre-req: a machine learning course or permission of instructor.

Mon 12-1:15

600.802

DISSERTATION RESEARCH

See below for faculty section numbers.

600.804

GRADUATE RESEARCH

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

See below for faculty section numbers.

600.810

GRADUATE INDEPENDENT STUDY

Permission Required.

See below for faculty section numbers.