Fall 2012 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.

Tu 4:30
limit 35, 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 (sections 01-03) concurrently. Students may receive credit for 600.107 or 600.112, but not both. (www.cs.jhu.edu/~joanne/cs107)

Prereq: familiarity with computers.

MW 1:30-2:45
limit 90

600.108 (E)

INTRO PROGRAMMING LAB (1) Selinski/Froehlich

Satisfactory/Unsatisfactory only. Must be taken in conjunction with 600.107 or 600.112. 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. Sections 1-3 are for 107 students, sections 4-6 are for 112 students.

Co-req: 600.107 or 600.112.

Sec 1: Wed 4:30-7:30p
Sec 2: Thu 6:00-9:00p
Sec 3: Fri 1:30-4:30p
Sec 4: Wed 4:30-7:30p
Sec 5: Thu 6:00-9:00p
Sec 6: Fri 12:00-3:00p
limit 16/section

600.112 (E)

INTRODUCTION TO PROGRAMMING FOR SCIENTISTS AND ENGINEERS (3) Froehlich

An introductory "learning by doing" programming course for scientists, engineers, and everybody else who will need basic programming skills in their studies and careers. We cover the fundamentals of structured, modular, and (to some extent) object-oriented programming as well as important design principles and software development techniques such as unit testing and revision control. We will apply our shiny new programming skills by developing computational solutions to a number of real-world problems from a variety of disciplines. Students new to computer programming are encouraged to enroll into 600.108 Intro Programming Lab concurrently with this course. Students may receive credit for 600.107 or 600.111 or 600.112, but not more than one. [Note: This course may not be used for the CS major or minor requirements, except as a substitute for 600.107.]

Prereq: none.

MW 12-1:15
limit 90

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, 600.111 or equivalent.

MWF 3:00-4:15
limit 50 (+25 CS freshmen)

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. (www.cs.jhu.edu/~joanne/cs226)

Prereq: AP CS or 600.107 or 600.120 or equivalent.

MWF 12-1:15
limit 75

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] (www.cs.jhu.edu/~yarowsky/cs415.html)

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

TuTh 3-4:15
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] (http://pl.cs.jhu.edu/oose/index.shtml)

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

600.323 (E)

NEW COURSE!

DATA-INTENSIVE COMPUTING (3) Burns

Data-Intensive Computing is an experiential education course in computing with massive data sets that covers the software, algorithms, and systems used to ingest, store, and analyze. Specific topics include: NoSQL software systems including key/value stores and graph databases, scientific python, array databases, (semi)-external memory array and graph algorithms, extract-transform-load (ETL) processing, spatial indexing, OpenCL GPU code acceleration, and performance management of clusters. The course will utilize the unique computing resources at JHU, including the DataScope (5PB of storage), the GPU cluster (110 TFlops), and the Homewood High Performance Computing Cluster (1600 cores). The entire course will take place in several lengthy lab sessions each week. Course time will be divided roughly into team projects (30%), ad-hoc tasks (50%), presentation (10%) and using collaboration tools for concurrent reading and authoring and interactive self-assessment. [Systems]

Prereq: 600.320/420. Students may receive credit for 600.323 or 600.423, but not both.

MW 3-7p
limit 8

600.333 (E)

COMPUTER SYSTEM FUNDAMENTALS (3) Froehlich

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. [Systems]

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

MWF 10
limit 50

600.337 (E)

DISTRIBUTED SYSTEMS (3) Amir

The course teaches how to design and implement efficient tools, protocols and systems in a distributed environment. The course provides extensive hands-on experience as well as considerable theoretical background. Topics includes basic communication protocols, synchronous and asynchronous models for consensus, multicast and group communication protocols, distributed transactions, replication and resilient replication, overlay and wireless mesh networks, peer to peer and probabilistic protocols. [Systems] (www.cnds.jhu.edu/courses/cs437)

Prereq: 600.120, 600.226. Students may receive credit for 600.337 or 600.437, but not both.

TuTh 3-4:15
limit 15

600.361 (E,Q)

COMPUTER VISION (3) Hager

This course gives an overview of fundamental methods in computer vision from a computational perspective. Methods studied include: camera systems and their modelling, computation of 3-D geometry from binocular stereo, motion, and photometric stereo; and object recognition. Edge detection and color perception are covered as well. Elements of machine vision and biological vision are also included. [Applications] (https://cirl.lcsr.jhu.edu/Vision_Syllabus)

Prereq: 600.226 & linear algebra

TuTh 9-10:15
limit 20

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 9-10:15
limit 30

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] (www.cs.jhu.edu/~yarowsky/cs415.html)

Prereq: 600.226.

TuTh 3-4:15
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] (http://pl.cs.jhu.edu/oose/index.shtml)

Prereq: 600.226 and 600.120/121.

MW 1:30-2:45
limit 40

600.423 (E)

NEW COURSE!

DATA-INTENSIVE COMPUTING (3) Burns

Graduate student version of 600.323. [Systems]

Prereq: 600.320/420. Students may receive credit for 600.323 or 600.423, but not both.

MW 3-7p
limit 8

600.429 (E)
NEW COURSE!

FUNCTIONAL PROGRAMING AT WORK - HASKELL AND DOMAIN SPECIFIC LANGUAGES (3) Peterson

This course studies pure functional programming in the Haskell language and the use of functional programming to build domain specific languages (DSLs): customized, application specific programming languages. This course starts with an introduction to Haskell and its essential ideas of lazy evaluation and type inference. Advanced functional programming topics will include type classes, monads and monad transformers, arrows, templates, dependent types, parser combinators, and multiple parameter type classes. The class will study existing DSLs and DSL implementation techniques, including languages for reactive programming, computer vision, hardware design, computer music, and parallel processing. Students will implement a DSL of their choice in Haskell. [Systems]

Pre-req: 600.226.

MoWe 4:30-5:45
limit 40

600.433 (E)

COMPUTER SYSTEMS (3) Froehlich

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

MWF 10
limit 20

600.437 (E)

DISTRIBUTED SYSTEMS (3) Amir

Graduate version of 600.337. Students may receive credit for 600.337 or 600.437, but not both. [Systems] (www.cnds.jhu.edu/courses/cs437)

Prereq: 600.120, 600.226.

TuTh 3-4:15
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 30

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 45

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] (http://www.cisst.org/~cista/445/index.html)

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

TuTh 1:30-2:45
limit 50

600.454 (E)

NEW LISTING!

PRACTICAL CRYPTOGRAPHIC SYSTEMS (3) Green

[Co-listed with 650.445.] This semester-long course will teach systems and cryptographic design principles by example: by studying and identifying flaws in widely-deployed cryptographic products and protocols. Our focus will be on the techniques used in practical security systems, the mistakes that lead to failure, and the approaches that might have avoided the problem. We will place a particular emphasis on the techniques of provable security and the feasibility of reverse-engineering undocumented cryptographic systems. [Systems]

MW 3-4:15
limit 30

600.460 (E)

NEW LISTING!

SOFTWARE VULNERABILITY ANALYSIS (3) Checkoway

[Co-listed w/JHUISI course 650.460.] This course will examine vulnerabilities in C source, stack overflows, writing shell code, etc. Also, vulnerabilities in web applications: SQL Injection, cookies, as well as vulnerabilities in C binary fuzzing, and exploit development without source among other topics. [Applications]

TuTh 1:30-2:45
limit 15

600.461 (E,Q)

COMPUTER VISION (3) Hager

Graduate version of 600.361. Students may receive credit for 600.361 or 600.461, but not both. [Applications] (https://cirl.lcsr.jhu.edu/Vision_Syllabus)

Prereq: 600.226 & linear algebra

TuTh 9-10:15
limit 50

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]

Prereq: 600.226 and 550.171 or Perm. req'd.

TuTh 9-10:15
limit 30

600.464 (E,Q)

RANDOMIZED ALGORITHMS (3) Kosaraju

The course emphasizes algorithmic design aspects, and how randomization can be a helpful tool. The topics covered includee: tail inequalities, linear programming relaxation & randomized rounding, de-randomization, existence proofs, universal hashing, markov chains, metropolis and metropolis-hastings methods, mixing by coupling and by eigenvalues, counting problems, semi-definite programming and rounding, lower bound arguments, and applications of expanders. [Analysis] (www.cs.jhu.edu/~cs464)

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 20

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] (www.cs.jhu.edu/~jason/465)

Prerequisite: 600.226.

MWF 3
limit 40

600.467 (E)

WIRELESS NETWORKS (3) ??

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.

CANCELLED
limit 20

600.471 (EQ)

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]
(syllabus.html)

Prereq: multivariate calculus.

MW 12-1:15
limit 40

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 90

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 & 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] (www.cs.jhu.edu/~yanif/teaching/bdslss)

Pre-req: 600.315/415 or equivalent.

WF 1:30-2:45
limit 30

600.644

CANCELLED

ADVANCED COMPUTER NETWORKS (3) Terzis

This is a graduate level course on computer networking. The course involves both a reading/lecture/discussion component and a project component. We will read about 50 research papers on various aspects of computer networking: software defined networks, congestion/flow control, network measurements, routing, content distribution networks, wireless, and data center networks. Students are expected to read papers before the class, submit a one page summary for each paper, and participate in the discussion during the class. The class projects can be either of the following types: design/implementation, measurement, and simulation. The lecture will be conducted in an interactive fashion. The instructor will lead the discussion, but we expect everyone to participate. You will be graded for both the paper summaries and class discussion. [Systems]

Prereq: Prerequisite: 600.344/444 or permission of instructor.

CANCELLED
limit 30

600.657

Cancelled, see 600.660

ADVANCED TOPICS FOR COMPUTER GRAPHICS (3) Kazhdan

This course presents advanced methodologies and their applications to computer graphics. [Applications]

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

TuTh 3-4:15
limit 15

600.660

FFT IN GRAPHICS & VISION (3) Kazhdan

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]

Prereq: linear algebra and comfort with mathematical derivations.

TuTh 3-4:15
limit 15

600.664

RANDOMIZED ALGORITHMS (3) Kosaraju

Graduate level version of 600.464. [Analysis] (www.cs.jhu.edu/~cs464)

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 20

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

tbd
limit 15

600.728

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

tbd
limit 15

500.745

SEMINAR IN COMPUTATIONAL SENSING AND ROBOTICS Kazanzides, Whitcomb, Vidal, Etienne-Cummings

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 with Mechanical Engineering, Computer Science, Electrical and Computer Engineering, and Biomedical Engineering.

Wed 12-1:30
limit 80

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.

tbd
limit 20

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.

tbd
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.

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.

Fr 10:30-11:30
limit 20

600.780

NEW COURSE!

SELECTED TOPICS IN COMPUTATIONAL GENOMICS Langmead

This course will survey current areas where computer science approaches have been applied to genomics research. Chiefly, the course focuses on DNA sequencing data analysis, including sequence alignment, de novo assembly, error correction, and DNA data compression. Subject matter will be partially guided by student interests. Students will present papers orally.

tbd
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.