Credits: 3

An introduction to organizing, analyzing, and presenting information using databases and spreadsheets. no programming involved, and no computing background expected.

College: School of Engineering

Department: Computer Science

Credits: 1

This seminar presents an overview of Computer Science for students who have not chosen a major. Weekly lectures address different topics in Computer Science. No technical background is assumed. The goal is to help students understand the problems that Computer Scientists attack and the impact of those solutions on society.

College: School of Engineering

Department: Computer Science

Credits: 3

The course introduces basic techniques for problem solving and visualization using computational environments such as Mathematica and MATLAB. Class will consist of a mixture of traditional lectures held in classrooms and self-paced modules covering topics in science and engineering that will be completed in Symonds II. No previous experience is required or expected. Cross-list: NSCI 230.

College: School of Engineering

Department: Computer Science

Credits: 4

Introduction to major topics in computer science, including real-world problems in a variety of areas. Teaches how to design and implement algorithmic solutions in Python and how to experimentally test and evaluate performance of computational systems.

Instructor permission required

College: School of Engineering

Department: Computer Science

Credits: 4

An integrated introduction to computation taught by solving real-world problems in audio, video and text processing, physical robotics, control and simulation of complex systems in nature, and swarm intelligence. Technical topics include how to model computational artifacts operating in the world; how to design and implement algorithmic solutions in Python; and how to experimentally test and evaluate performance of computational systems. Open to first-year students.

College: School of Engineering

Department: Computer Science

May not be enrolled in one of the following Class(es):

Senior

Junior

Credits: 4

This class focuses on the mathematics and programming skills necessary to build computer games. math topics will include basic geometric primitives, transformations, texturing, lighting/shading and collision detection. Programming topics will include C# and XNA with students expected to construct two simple games that will be playable on the Microsoft Xbox. Limited to first year students. Java Experience.

College: School of Engineering

Department: Computer Science

May not be enrolled in one of the following Class(es):

Senior

Junior

Credits: 3

Explore how modern game content is created, and how it interacts with the underlying technology. Beginning with an explanation of how games are developed and what role content plays in the process, the class will learn to use 3D Studio Max, Photoshop, and game-native scripting as they create working content for an established game project.

College: School of Engineering

Department: Computer Science

Credits: 4

Algorithms are the engines of a great majority of systems, natural and artificial alike. This course introduces algorithmic thinking as a discipline for reasoning about systems, taming their complexities, and elucidating their properties. Algorithmic techniques, along with their correctness and efficiency, will be taught through reasoning about systems of interactions, such as markets, that are ubiquitous in our highly connected world.

College: School of Engineering

Department: Computer Science

Pre-requisities: COMP 140 OR COMP 160

Credits: 3

Broad introduction to major topics in computer science. Includes algorithms, mathematical models of computation, machine organization and design, programming languages, communication, and artificial intelligence. This course is intended for majors outside of Science and Engineering.

College: School of Engineering

Department: Computer Science

Credits: 4

Introduction to computing focusing on the principles of object-oriented programming using design patterns coupled with progressively richer subsets of the Java programming language. Program design concepts such as structural and behavioral abstractions are emphasized in building contemporary dynamic software systems. Design Patterns are used as a vocabulary for codifying these abstractions and expressing fundamental computing principles. They are illustrated in the design and implementation of lists, trees and arrays and their associated algorithms that leverage both run-time and parametric polymorphism. The course utilizes UML diagrams for object modeling and unit testing as a part of an incremental, test-driven approach to writing programs. Recommended for Engineering and other non-Comp majors, plus students who have yet not committed to a COMP major.

College: School of Engineering

Department: Computer Science

Credits: 4

Continuation of COMP 201 covering advanced object-oriented data structures and their associated algorithms such as lazy evaluation, heaps, self-balancing trees, graphs, sorting, and generative recursion. Applications of Software Engineering principles such as abstract decomposition, decoupling, and command passing to large- and small- scale component-framework systems. Multi-threaded event-driven applications provide compelling illustrations for such principles. Recommended for Engineering majors, non-Engineering students, and potential Computer Science majors.

College: School of Engineering

Department: Computer Science

Pre-requisities: COMP 201

Credits: 4

How to systematically design programs in functional and object-oriented languages. Includes inductive data definitions, data-directed program design, test-driven software development, semantic reduction rules, recursive problem decomposition, procedural abstraction, functions as values, tail recursion and loops, object-oriented design patterns, algorithmic efficiency, programming in Scheme and Java.

College: School of Engineering

Department: Computer Science

Pre-requisities: COMP 140 OR COMP 160

Credits: 4

This course covers the principles of programming and program design. The course is organized around a number of individual programming assignments that fit together to complete a significant, real-world application. Each assignment emphasizes one or more of the basic principles of software design, including: encapsulation, abstraction, test-driven development, and functional and object-oriented programming. The Java programming language will be used. An introduction tot he basics of the Java language itself (including Java syntax and semantics) will be provided.

College: School of Engineering

Department: Computer Science

Pre-requisities: COMP 182

Credits: 4

This course introduces computer systems from the programmer's perspective. Topics include data representation, the compilation process, and system-level programming concepts such as interrupts and concurrency.

College: School of Engineering

Department: Computer Science

Pre-requisities: ELEC 220 AND (COMP 211 OR COMP 215)

Credits: 3

This course provides an introduction to the use of mathematics in modeling and reasoning about problems in computer science. Topics include logic, proof methods (including mathematical and structural induction), reasoning about recursive and iterative programs, sets, functions and their asymptotic growth, counting, and modular arithmetic.

College: School of Engineering

Department: Computer Science

Pre-requisities: COMP 140

Credits: 3

Starting with the colorful history of numbers, we discover their use to characterize chance or luck through probability; students will participate in one major project and submit a report-application areas include physics, computer science, sports, finance, etc. The course is accessible to sophomores and juniors in science, engineering or business. Cross-list: ELEC 281, STAT 281.

College: School of Engineering

Department: Computer Science

Credits: Hours Variable

Theoretical and experimental investigations under staff direction. Equivalency: COMP 390.

Instructor permission required

College: School of Engineering

Department: Computer Science

Credits: 3

We will review the remarkable technology of the Information Age and examine its effects on the ways in which we live, work and think about the world around us. We will consider, for example, how the pervasive use of computers and networks is changing our ideas about property, privacy, authority, social relations, knowledge and identity. An we will discuss what further changes we might see as technology continues to advance.

College: School of Engineering

Department: Computer Science

Credits: 3

Information and computing technologies (ICT) have produced sweeping changes in societal, economic and political domains. Examining the relationship between ICT and public policy, this course will cover current issues including computer crime, immigration, intellectual property and online commerce to better understand the intersection of the microchip and democratic society.

College: School of Engineering

Department: Computer Science

Credits: 4

Discover how state-of-the-art object-orient programming and design techniques can create globe-spanning software systems that are both flexible and scalable. Learn how software design patterns are used in multiple programming paradigms. Explore highly decoupled systems with dynamically configurable behaviors. Highly recommended for anyone interested in building large systems and software engineering.

College: School of Engineering

Department: Computer Science

Pre-requisities: COMP 211 OR COMP 215

Credits: 4

The design, definition and abstract implementation of programming languages including methods for precisely specifying syntax and semantics.

College: School of Engineering

Department: Computer Science

Pre-requisities: COMP 211

Credits: 4

Design analysis of computer algorithms and data structures useful for applied problems. Laboratory assignments will use these techniques in conjunction with advanced programming methods. Cross-list: ELEC 322. COMP 280 may be taken the same semester to satisfy prerequiste requirement.

College: School of Engineering

Department: Computer Science

Pre-requisities: COMP 211 AND COMP 280

Credits: 4

Fundamentals of parallel programming: abstract models of parallel computers, parallel algorithms and data structures, and common parallel programming patterns including task parallelism, undirected and directed synchronization, data parallelism, divide-and-conquer parallelism, and map-reduce. Laboratory assignments will explore these topics through the use of parallel extensions to the Java language. Cross-list: ELEC 323.

College: School of Engineering

Department: Computer Science

Pre-requisities: COMP 211 OR COMP 215

Credits: 3

Study of gates, flip-flops, combinational and sequential switching circuits, registers, logical and arithmetic operations, introduction to the Verilog hardware description language. Cross-list: ELEC 326.

College: School of Engineering

Department: Computer Science

Pre-requisities: ELEC 220

Credits: 3

This elective course covers a wide variety of topics in computer security, including hands-on experience with breaking software and engineering software to be harder to break. For example, students will perform buffer overflow attacks and exploit web application vulnerabilities, while also learning how to defend against them. Grades will be based on a series of in-class projects.

College: School of Engineering

Department: Computer Science

Pre-requisities: COMP 310 OR COMP 314 OR ELEC 322

Credits: 4

2D graphics techniques including fast line and curve drawing and polygon filling. 3D graphics problems including representation of solids, shading, and hidden surface elimination. Fractals, graphics standards.

College: School of Engineering

Department: Computer Science

Pre-requisities: COMP 221 AND (COMP 280 OR COMP 182) AND COMP 215 AND (MATH 211 OR MATH 221) AND (MATH 212 OR MATH 222) AND (MATH 354 OR MATH 355)

Credits: 3

Large accessible data sets have opened new frontiers in evolutionary biology, and many fields. Learn to write computer programs to test hypotheses and discover patterns in diverse data. Understand the most common strategies in evolutionary bioinformatics, including dynamic programming, hidden Markov models, and graphical algorithms. No previous programming experience required. Biosciences Group B. Cross-list: EBIO 333. Recommended Prerequisite(s): MATH 101 and MATH 102.

College: School of Engineering

Department: Computer Science

Credits: 3

Information and Communication Technologies (ICT) have tremendous economic benefits, yet at an increasing cost to society with sustainability emerging as the major challenge. After an introduction, students will work on design projects based on ICT at the nexus of engineering, sciences and medicine. Cross-list: CHBE 381.

College: School of Engineering

Department: Computer Science

Credits: Hours Variable

See COMP 290. Equivalency: COMP 290.

Instructor permission required

College: School of Engineering

Department: Computer Science

Credits: 1

An introduction to technical communication in computer science. Includes oral, written, and visual presentations. Primarily for upper-level computer science undergraduates.

College: School of Engineering

Department: Computer Science

Credits: 4

This course focuses on the principles and practices of test-driven software development, which have been popularized under the banner of "Extreme Programming." To provide students with practical experience, the course engages students in the development of open source production programs written in JAVA or C#. The DRJAVA programming courses was developed by students in this course. Some of the major topics covered in course lectures include design patterns for controlling concurrency and refactoring transformations to improve legacy code.

College: School of Engineering

Department: Computer Science

Pre-requisities: COMP 211 OR COMP 310

Credits: 4

COMP 405 is a topics-driven exploration of cutting-edge object oriented design issues and concepts including mutable recursive data frameworks, design patterns for sorting, parsing and games, service-oriented architectures and cloud computing. Detailed knowledge and practice in abstract structure and behavioral representations, delegation model programming, design patterns and Java are required.

College: School of Engineering

Department: Computer Science

Pre-requisities: COMP 310

Credits: 3

An introduction of the fundamental techniques of algorithmic verification, including temporal logics, enumerative and symbolic model checking, and delaing with the state-explosion problem.

College: School of Engineering

Department: Computer Science

Pre-requisities: COMP 211 AND COMP 314

Credits: 3

Set theoretical concepts. Propositional and first-order logic. Soundness and completeness, incompleteness, undecidability. Logical issues in computer science.

College: School of Engineering

Department: Computer Science

Pre-requisities: (COMP 211 OR COMP 215) AND (COMP 182 OR COMP 280)

Credits: 4

COMP 410 is a pure discovery-based learning course designed to give students real-life, hands-on training in a wide variety of software engineering issues that arise in creating large-scale, state-of-the-art software systems. The class forms a small software development "company" that works to deliver a product to a customer. The topics encountered include and are not limited to, dealing with new technologies (e.g. C#, .NET, distributed computing), advanced object-oriented programming and design, interacting with customers, problem specification and tasking, individual and group communications, human resource management, group leadership, testing, integration and documentation. Traditional development cycle methodologies will be compared to recent, "agile" techniques.

College: School of Engineering

Department: Computer Science

Pre-requisities: COMP 314 OR COMP 310

Credits: 4

The design, definition and abstract implementation of programming languages including methods for precisely specifying syntax and semantics.

College: School of Engineering

Department: Computer Science

Pre-requisities: (COMP 211 OR COMP 310)

Credits: 4

Topics in the design of programming language translators, including parsing, run-time storage management, error recovery, code generation and optimization.

College: School of Engineering

Department: Computer Science

Pre-requisities: (COMP 314 OR ELEC 322 OR COMP 310 OR COMP 215) AND COMP 221

Credits: 4

This course focuses on modern principles for the construction of distributed programs, with an emphasis on design patterns, modern programming tools, and distributed object systems. The material will be applied in a substantial software design/construction project.

College: School of Engineering

Department: Computer Science

Pre-requisities: COMP 421

Credits: 4

Experience real customers, software, and situations. The class will be contracted by an industrial customer to design build, and deliver a product. Negotiate to finalize specifications, updates, and delivery schedules Encounter real-life issues such as team management, intellectual property, and vagueness and specification changes while developing a state-of-the-art software application.

College: School of Engineering

Department: Computer Science

Pre-requisities: COMP 410

Credits: 4

Introduction to advanced operating systems and distributed systems. The course covers concepts, architecture, algorithms, protocols and implementation focusing on distribution, scale, robustness in the face of failure, and security.

College: School of Engineering

Department: Computer Science

Pre-requisities: COMP 421

Credits: 4

Introduction to the design, construction, and analysis of concurrent programs with an emphasis on operating systems, including filing systems, schedulers, and memory allocators. Specific attention is devoted to process synchronization and communication within concurrent programs. Cross-list: ELEC 421.

College: School of Engineering

Department: Computer Science

Pre-requisities: (COMP 211 OR COMP 215) AND COMP 221

Credits: 4

Fundamentals of parallel computing including abstract models for parallel computation, parallel computer architectures, parallel algorithms, and data structures, programming models and methods, mapping and scheduling computation, analyzing computations for correctness and efficiency, and applications to science and engineering. Includes an extensive programming component.

College: School of Engineering

Department: Computer Science

Pre-requisities: (COMP 211 OR COMP 215) AND COMP 221

Credits: 4

ELEC 424 introduces mobile and embedded system design and applications to undergraduate students and provides them hands-on design experience. It consists of three interlearning parts: lectures, student project, and student presentations. Cross-list: ELEC 424.

College: School of Engineering

Department: Computer Science

Pre-requisities: ELEC 220

Credits: 4

Evolution of key architecture concepts found in advanced uniprocessor systems. Fundamental and advanced pipelining techniques and associated issues for improving processor performance. Illustrated with RISC processors such as the ARM processor. Examine several metrics for processor performance, such as Amdahl’s law. Key concepts of data and program memory systems found in modern systems with memory hierarchies and caches. Perform experiments in cache performance analysis. Influence of technology trends, such as Moore’s law, on processor implementation. Approaches for exploiting instruction level parallelism, such as VLIW. Introduction to parallel and multicore architectures. Introduction to processor architectures targeted for embedded applications. Cross-list: ELEC 425.

College: School of Engineering

Department: Computer Science

Pre-requisities: ELEC 326

Credits: 4

Network architectures, algorithms, and protocols. Local- and Wide-area networking. Intra- and inter-domain routing. Transmission reliability. Flow and congestion control. TCP/IP. Multicast. Quality of Service. Network Security - Networked applicatIons. Cross-list: ELEC 429.

College: School of Engineering

Department: Computer Science

Pre-requisities: COMP 221

Credits: 4

Query Introduction to relational database systems, SQL programming, Database application programming, and Database design.

College: School of Engineering

Department: Computer Science

Pre-requisities: (COMP 211 OR COMP 215) AND (COMP 182 OR COMP 280)

Credits: 3

This multidisciplinary course will consider how elections are conducted to enhance participation, to accurately measure the will of the electorate, and to be sufficiently rigorous to convince all parties that the results are legitimate. This course will consider the design and evaluation of election technologies, ranging from voter registration through the polling booth and vote tabulation. This course will consider three questions: how do individual voters interact with the voting technology, how are voting technologies engineered to be accurate and secure, and how do the social aspects of voting fulfill democratic goals for elections? A central requirement for this course will be group research projects, many operating in our community, built around the November election. Cross-list: POLI 420, PSYC 420.

College: School of Engineering

Department: Computer Science

Credits: 4

This is a foundational course in artificial intelligence, the discipline of designing intelligent agents. That course will cover the design and analysis of agents that do the right thing in the face of limited information and computational resources. The course revolves around two main questions: how agents decide what to do, and how they learn from experience. Tools from computer science, probability theory, and game theory will be used. Interesting examples of intelligent agents will be covered, including poker playing programs, bots for various games (e.g. WoW), DS1 -- the spacecraft that performed an autonomous flyby of Comet Borrely in 2001, Stanley -- the Stanford robot car that won the Darpa Grand Challenge, Google Maps and how it calculates driving directions, face and handwriting recognizers, Fedex package delivery planners, airline fare prediction sites, and fraud detectors in financial transactions. Cross-list: ELEC 440.

Instructor permission required

College: School of Engineering

Department: Computer Science

Pre-requisities: (COMP 280 AND COMP 314)

Credits: 4

As connected smartphones and tablets such as the iPhone and iPad become more popular, updated programming models and design concepts are required to take advantage of their capabilities. COMP/ELEC 446 will consider programming models including natively running applications, web services and mobile tailored web pages. We will explore applications primarily on the Apple iPhone, iPod and iPad but will briefly cover Google Android and Microsoft Windows Phone. We will also briefly touch on the development of web services to support mobile applications. The course culminates with a large project taking up most of the second half of the semester. Curriculum centers around and teaches iOS and code (iPhone/iPad); however final projects may also be completed in any major mobile system if the student has a foundation in Eclipse (Android) or Visual Studio (WP). Cross-list: ELEC 446. Recommended Prerequisite(s): COMP 215 or prior Object Oriented Programming experience.

Instructor permission required

College: School of Engineering

Department: Computer Science

Credits: 4

Robots have fascinated people for generations. Today, robots are built for applications as diverse as exploring remote planets, de-mining war zones, cleaning toxic waste, assembling cars, inspecting pipes in industrial plants and mowing lawns. Robots are also interacting with humans in a variety of ways: robots are museum guides, robots pets entertain, and robots assist surgeon sin life threatening operations. The field of robotics studies not only the design of new mechanisms but also the development of algorithms, and frameworks to make these mechanism useful in the physical world, integrating science, engineering, mathematics and more recently biology and sociology, in a unique way. This class will present fundamental algorithmic advances that enable today’s robots to move in real environments and plan their actions. The class involves a significant programming project. Cross-list: ELEC 450, MECH 450.

College: School of Engineering

Department: Computer Science

Pre-requisities: COMP 215 AND COMP 221

Credits: 4

This project-based class involves teams of 2-4 CS and Visual Arts students designing and building computer games suitable for Xbox Live Arcade using C# and XNA. For CS students, Comp 160 or Comp 360 is recommended as a prerequisite. For Visual Arts students, previous experience in drawing using Photoshop is suggested. Cross-list: ARTS 460.

Instructor permission required

College: School of Engineering

Department: Computer Science

Credits: 4

Contemporary introduction to problems in computational biology spanning sequence to structure. The course has three modules: the first introduces students to the design and statistical analysis of gene expression studies; the second covers statistical machine learning techniques for understanding experimental data generated in computational biology; and the third introduces problems in the modeling of protein structure using computational methods from robotics. The course is project oriented with an emphasis on computation and problem-solving. Cross-list: BIOE 470, STAT 470. Recommended Prerequisite(s): COMP 280 and (STAT 310 or STAT 331).

College: School of Engineering

Department: Computer Science

Credits: 3

Finite automata, regular expressions, regular languages, pushdown automata, context-free languages, Turing machines, recursive languages, computability, and solvability. It is strongly recommended that students complete three semesters of Mathematics before enrolling in this course.

College: School of Engineering

Department: Computer Science

Credits: 3

Methods for designing and analyzing computer algorithms and data structures. The focus of this course will be on the theoretical and mathematical aspects of algorithms and data structures. Cross-list: ELEC 420.

College: School of Engineering

Department: Computer Science

Pre-requisities: (COMP 280 OR COMP 182) AND (STAT 310 OR ECON 307 OR STAT 331 OR ELEC 331 OR ELEC 303 OR STAT 312)

Credits: 3

This course will introduce basic principles of image acquisition, formation and processing of several medical imaging modalities such as X-Ray, CT, MRI, and US that are used to evaluate the human anatomy. The course also includes visits to a clinical site to gain experience with the various imaging modalities covered in class. Cross-list: BIOE 485, ELEC 485. Recommended Prerequisite(s): MATH 211 and MATH 212.

College: School of Engineering

Department: Computer Science

Credits: 3

This course focuses on functional imaging modalities used specifically in nuclear medicine such as Gamma cameras, SPECT, and PET imaging. The course will introduce the basic principles of image acquisition, formation, processing and the clinical applications of these imaging modalities and lays the foundations for understanding the principles of radiotracer kinetic modeling. A trip to a clinical site in also planned to gain experience with nuclear medicine imaging. Cross-list: BIOE 486, ELEC 486.

College: School of Engineering

Department: Computer Science

Pre-requisities: ELEC 485 OR BIOE 485 OR COMP 485

Credits: Hours Variable

Theoretical and experimental investigation under staff direction.

Instructor permission required

College: School of Engineering

Department: Computer Science

Credits: 3

A combination of in-service teaching and a seminar.

Department permission required

College: School of Engineering

Department: Computer Science

Credits: 3

Introduction to the kinematics, dynamics, and control of robot manipulators and to applications of artificial intelligence and computer vision in robotics. Cross-list: ELEC 498, MECH 498.

College: School of Engineering

Department: Computer Science

Pre-requisities: MATH 354 OR MATH 355 OR CAAM 335

Credits: 3

Review of major neural machine learning (Artificial Neural Network) paradigms. Analytical discussion of supervised and unsupervised neural learning algorithms and their relation to information theoretical methods. Practical applications to data analysis such as pattern recognition, clustering, classification, function approximation/regression, non-linear PCA, projection pursuit, independent component analysis, with lots of examples from image and digital processings. Details are posted at www.ece.rice.edu/~erzsebet/ANNcourse.html. Cross-list: ELEC 502, STAT 502. Pre-requisite: ELEC 430 and ELEC 431 or equivalent or permission of instructor.

College: School of Engineering

Department: Computer Science

Credits: 4

This course is a graduate-level introduction to computer-aided program design, a field that studies logical and algorithmic techniques for formally verifying programs, and mechanized derivation of programs that are correct by construction. Topics covered will include classical automated program verification in particular abstract interpretation and model checking - as well as recent developments in algorithmic program synthesis.

College: School of Engineering

Department: Computer Science

Pre-requisities: (COMP 482 OR ELEC 420) OR COMP 481

Credits: 4

Multi-stage programs can generate other programs at runtime, compile them, and execute them. Such programs can be significantly faster than single-stage ones. This course introduces multi-stage languages, their applications, theory, and implementation techniques. Coursework includes reading assignments, discussions, and various kinds of programming exercises using one such language (MetaOCaml).

College: School of Engineering

Department: Computer Science

Pre-requisities: COMP 311 OR COMP 411

Credits: 4

Advanced topics in the design of an optimizing compiler. This course will focus on analysis and optimization of programs for uniprocessor machines, including program analysis (data-flow analysis, construction of static single-assignment form) and program transformation (redundancies, constant values, strength reduction, etc.). The course uses a variety of readings from the literature and includes an implementation project. Recommended Prerequisite: COMP 412.

College: School of Engineering

Department: Computer Science

Credits: 3

A modern computer is a system with enormous complexity in both software and hardware. The course presents the principles for managing such complexity using examples from modern computing systems. It covers emergent issues from system complexity such as energy efficiency, bug finding, and heterogeneous hardware. It also covers designing experiments and writing systems papers. The course consists of lectures, student presentation of classic papers, and a final project. Cross-list: ELEC 513.

College: School of Engineering

Department: Computer Science

Credits: 3

An interdisciplinary course addressing the energy issues facing computing in the coming decade and beyond. In a student research-griven format we will ask how IT may address its power consumption problem and serve as a vehicle for energy efficiency, sustainability, and reduced carbon emissions across all human activity. Cross-list: ELEC 514.

College: School of Engineering

Department: Computer Science

Must be enrolled in one of the following Class(es):

Graduate

Credits: 3

Advanced compilation techniques for vector and parallel computer systems, including the analysis of program dependence, program transformations to enhance parallelism, compiler management of the memory hierarchy, interprocedural data flow analysis, and parallel debugging. Recommended Prerequisite: COMP 412.

College: School of Engineering

Department: Computer Science

Pre-requisities: COMP 314 AND (COMP 221 OR COMP 320

Credits: 3

While high-level programming languages can be very helpful for general-purpose programming, they can be unsuitable for programming systems that interact directly with the physical world. Such systems include real-time and embedded systems. This seminar explores the design space for high-level languages that can support the more specialized task of resource-aware programming (RAP). Recommended Prerequisite: COMP 211 and COMP 280.

College: School of Engineering

Department: Computer Science

Credits: 3

Energy efficiency has become critically important for modern computing systems, from batter-powered mobile devices to wall-powered high-performance servers. The course presents the fundamentals of energy characteristics of modern systems, and introduces basic energy-saving mechanisms and mthodologies for system energy characterization. It also covers emerging technologies in energy-efficient design. Cross-list: ELEC 518.

Instructor permission required

College: School of Engineering

Department: Computer Science

Credits: 4

Design and Implementation of network systems, including hardware and software architectures of network routers and servers. Students will design and implement wither the hardware or software components of a network system, depending on their experience and preferences. This course is suitable for students with expertise in either software or hardware. Cross-list: ELEC 519. Recommended Prerequisite: COMP 221

College: School of Engineering

Department: Computer Science

Credits: 4

Distributed systems: workstations, local area networks, server machines. Multiprocess structuring and interprocess communication. File access and memory management. User interfaces: window systems and command interpreters. Case studies of selected distributed systems. Emphasis on performance aspects of system software design. Cross-list: ELEC 520.

College: School of Engineering

Department: Computer Science

Credits: 4

Advanced topics in the design and implementation of state-of-the-art operating systems for general-purpose computation, emphasizing solutions to performance and scalability bottlenecks that are common with today's commercial and scientific workloads: process and thread management; NUMA memory management, super page support; SMP memory and address translation coherence; low-overhead, high-throughput I/O systems; robustness versus performance in file systems.

College: School of Engineering

Department: Computer Science

Pre-requisities: COMP 421

Credits: 3

Multi-core microprocessors are becoming the norm. The course will focus on emerging multi-core processor architectures and challenges to using them effectively. Topics include multi-core microcompressors, memory hierarchy, synchronization, programming systems, scheduling, and transactional memory.

College: School of Engineering

Department: Computer Science

Pre-requisities: (COMP 221 AND COMP 425) or permission of instructor

Credits: 3

Fundamental topics in computer-aided design for VLSI: logic synthesis and formal verification, timing analysis and optimization, technology mapping, logic and fault simulation, testing, and physical design will be covered. Relevant topics in algorithms and data structures, generic programming, and the C++ standard template library will also be covered. Cross-list: ELEC 523.

College: School of Engineering

Department: Computer Science

Credits: 3

Study of network protocols for mobile and wireless networking, particularly at the media access control, network, and transport protocol layers. Focus is on the unique problems and challenges presented by the properties of wireless transmission and host or router mobility. Cross-list: ELEC 524. Recommended Prerequisite(s): COMP 421 OR ELEC 421.

College: School of Engineering

Department: Computer Science

Pre-requisities: COMP 429 OR ELEC 429

Credits: 3

Virtualized computer architectures. Processor, memory and storage virtualization techniques. Resource allocation and scheduling of virtual machines. Cloud architectures and infrastructure. Utility computing. Cross-list: ELEC 525.

College: School of Engineering

Department: Computer Science

Pre-requisities: (ELEC 425 OR COMP 425)

Credits: 3

Design of high performance computer systems, including shared-memory and message-passing multiprocessors and vector systems. Hardware and software techniques to tolerate and reduce memory and communication latency. Case studies and performance simulation of high-performance systems. Cross-list: ELEC 526.

College: School of Engineering

Department: Computer Science

Pre-requisities: COMP 425 OR ELEC 425

Credits: 4

This class will focus on computer security in real systems. We will cover theory and practice for the design of secure systems (formal modeling, hardware and compiler-enforced safety, software engineering processes, tamper-resistant and tamper-reactive hardware, firewalls, cryptography, and more). Recommended Prerequisite(s): (COMP 311 or COMP 412) and (COMP 421 or COMP 429).

College: School of Engineering

Department: Computer Science

Credits: 4

Fundamental topics in performance analysis of computer systems: workload, characterization, measurement techniques, probability and statistics, experimental design, simulation, and analytical modeling. These techniques will be used to understand the performance of computer systems, serial and parallel programs, networks and client-server computing. Assignments will focus on applying these techniques in practice.

College: School of Engineering

Department: Computer Science

Credits: 4

Graduate level course on the study of protocols and systems for wide-area inter-networks with an emphasis on the challenges presented by the scale and complexity of the Internet. Topics include network architecture, router design, intra- and inter- domain routing, multicast services, congestion control, quality of service, network security, active and overlay network, network management. Cross-list: ELEC 529.

College: School of Engineering

Department: Computer Science

Pre-requisities: COMP 429 OR ELEC 429

Credits: 3

CMOS transistors, building elements of modern computing are entering the nanometer era. This course aims at providing basic knowledge of nanotechnologies-based computing. It starts with addressing immediate challenges facing CMOS-based computing. It then covers emerging non-standard CMOS and non CMOS devices, their physical properties, fabrications, circuit design, and impacts on the existing design flow and computing paradigms. Cross-list: CHEM 527, ELEC 527.

College: School of Engineering

Department: Computer Science

Pre-requisities: (COMP 311 OR COMP 412) AND (COMP 421 OR COMP 429 OR ELEC 429)

Credits: 3

The course covers wide range of topics pertaining to security of Hardware Embedded system, including cryptographic processors, secure memory access, hardware IT protection by monitoring and watermarking FPGA security, physical and side-charmed attacks, Trojan horses. Cross-list: ELEC 528.

College: School of Engineering

Department: Computer Science

Credits: 4

COMP 540 is about learning models from data. The course is designed to give students a foundational understanding of modern algorithms in learning and data mining, as well as hands-on experience with its applications in science and engineering.

College: School of Engineering

Department: Computer Science

Pre-requisities: (STAT 331 OR STAT 310) AND (MATH 355 OR CAAM 335) or permission of instructor

Credits: 4

Advanced topics in the design and application of algorithms for solving problems in the physical world.

College: School of Engineering

Department: Computer Science

Credits: 4

This course will introduce the key concepts of modern robotics. The course will cover sensing, state estimation, localization, basic motion planning, and multi-robot coordination. The course will have a large laboratory component, with lectures to cover important concepts. There will be considerable software development in C, familiarity with programming is required. The course will be self-contained, there are no prerequisites, and advanced undergraduates and new graduate students are encouraged to enroll. Lab times will be arranged in the first week of class.

College: School of Engineering

Department: Computer Science

Credits: 4

A survey of core topics in Computer Graphics and Geometric Modeling, including fractals, ray tracing, hidden surface Algorithmic, Bezier, B-spline, blossoming techniques and subdivision procedures.

College: School of Engineering

Department: Computer Science

Must be enrolled in one of the following Level(s):

Graduate

Must be enrolled in one of the following Class(es):

Graduate

Credits: 4

Exploration of curves and surfaces (e.g. parametric form, implicit form, and conversion between forms), the representation of solid (e.g., wireframes, occtrees, boundary representations, and constructive solid geometry), and applications (e.g., graphics, motion planning, simulation, and finite element mesh generation.

College: School of Engineering

Department: Computer Science

Pre-requisities: COMP 460

Credits: 3

Pairwise and multiple sequence alignment, Markov chains and HMMs, Phylogenetic reconstruction, Haplotype inference, Computational models of RNA structure, Gene finding, Genome rearrangements, and comparative genomics. Cross-list: BIOC 571.

College: School of Engineering

Department: Computer Science

Credits: 3

This course covers computational aspects of biological network analysis, a major theme in the area of systems biology. The course addresses protein-protein interaction networks, signaling, and metabolic networks, and covers issues related to reconstructing, analyzing, and integrating various types of networks. Cross-list: BIOC 572, BIOE 564.

College: School of Engineering

Department: Computer Science

Credits: 1

This seminar introduces pre- and postdoctoral students in biomedical informatics to topics relevant to professional development in the discipline, which is no longer concentrated in labs as it was in its early days, but is now important in hospitals, outpatient clinics, companies and even the community. In these settings, researchers and practitioners are likely to encounter not only difficult technical challenges, but vexing problems of organizational change and development as well. We will consider some of these challenges, drawing on the insights of experts in psychology, organizational change, management and communications along with industry representatives and entrepreneurs. The seminar mixes lectures and readings with group and individual exercises.

Instructor permission required

College: School of Engineering

Department: Computer Science

Credits: 3

Parallel architectures; shared memory, VLSI, message-passing. Structure and relation between architectures. Parallel time, work, and efficiency. Parallel algorithms for fundamental computational problems and applications. Network routing.

College: School of Engineering

Department: Computer Science

Credits: 3

Fundamental and advanced topics in symbolic computational symbolic-numerical arithmetic in basic domains, computing by homomorphic images, indefinite summation, computer analysis and the method of Groebner bases. The course also includes applications of symbolic computation to geometric modeling and theorem proving.

College: School of Engineering

Department: Computer Science

Credits: Hours Variable

Advanced theoretical and experimental investigations under staff direction.

College: School of Engineering

Department: Computer Science

Credits: 1

This seminar course meets weekly to discuss current research results by graduate students in the Computer Science Department. Senior students are expected to present their results.

College: School of Engineering

Department: Computer Science

Credits: 1

This is a seminar on technical writing and preparing publications for peer review. The focus is on conference papers, around 6-10 pages in length. The main topics are: 1) The structure of a conference publication, with guest lectures from the faculty. 2) Good daily writing habits with a group accountability system. 3) Editing techniques and the development a departmental "writing community" with interactive editing sessions. This course will cover a few topics from ENGI 600, but the main focus will be on short computer science conference documents and interactive peer editing. ENGI 600 is still the correct course to take for writing in general, thesis preparation, or journal publications. This course will complement COMP 600, and to develop the same community for writing as this class does for presentations.

College: School of Engineering

Department: Computer Science

Credits: 3

Advanced topics in ANN theories, with a focus on Self-Organizing Maps and unsupervised learning. The course will be a mix of lectures and seminar discussions with active student participation, based on most recent research publications. Students will have access to professional software environment to implement theories. Cross-list: ELEC 602.

College: School of Engineering

Department: Computer Science

Pre-requisities: ELEC 502 OR COMP 502 or permission of instructor

Credits: 1

Methods, tools and theories for the computer-aided verification of concurrent systems.

College: School of Engineering

Department: Computer Science

Credits: 1

A discussion of programming language semantics in computer science.

College: School of Engineering

Department: Computer Science

Credits: 2

Topics in construction of programming language translators.

College: School of Engineering

Department: Computer Science

Credits: 3

Topics in advanced language implementation.

College: School of Engineering

Department: Computer Science

Credits: 2

This course will explore topics in parallel programming environments and compilers for parallel computers.

College: School of Engineering

Department: Computer Science

Credits: Hours Variable

While high-level programming languages can be very helpful for general-purpose programming, they can be unsuitable for programming systems that interact directly with the physical world. Such systems include real-time and embedded systems. This seminar explores the design space for high-level languages that can support the more specialized task of resource-aware programming (RAP).

Instructor permission required

College: School of Engineering

Department: Computer Science

Credits: 1

Content varies at discretion of instructor.

College: School of Engineering

Department: Computer Science

Credits: 3

Subjects covering virtual memory and security structures, pipelines and vector processing, instruction set definitions, multi-threading, will be discussed. Both contemporary and "ancient systems" will be analyzed.

College: School of Engineering

Department: Computer Science

Credits: 1

This course will explore research topics in computer networking with an emphasis on the Internet. Topics include network algorithms and protocols, quality of service, network measurement, network management, network security, overlay networking.

College: School of Engineering

Department: Computer Science

Credits: 3

Topics in mult-itier wireless networks

Instructor permission required

College: School of Engineering

Department: Computer Science

Credits: 1

This course will cover the topic of indexing for different topic of indexing for different type of large, (typically) disk-based data sets. Indexing generally refers to the design, implementation, and use of data structures that allow you to quickly find database objects that satisfy a particular selection criteria. For example, in a database containing a large number of survelillance photographs, you may want to find all photographs that are similar to the picture of a known criminal, without having to check each and every photograph in the database explicitly. In the course, we will study data structures that are appropriate for this problem, as well as for many other database search problems.

College: School of Engineering

Department: Computer Science

Credits: 1

In this seminar, we will study programming models for accelerators and heterogeneous processors being developed in industry and academia that span the range across FPGAs, stream processors, and processing units with local memories (including GPGPUs). The seminar will have a participatory format. We will meet weekly to study different heterogeneous processors and their software environments. In some cases, real hardware will be available for experimentation as well.

College: School of Engineering

Department: Computer Science

Credits: 3

A reading course covering the latest developments in statistical machine learning and pattern recognition. Recommended Prerequisite(s): COMP 440.

Instructor permission required

College: School of Engineering

Department: Computer Science

Credits: 1

Methods, tools and theories for reasoning about problems with physical constraints.

Instructor permission required

College: School of Engineering

Department: Computer Science

Credits: Hours Variable

SPRING 2013 - SPECIAL TOPICS IN ROBOTICS Robot Navigation and Multi-Robot Systems - This seminar will explore important topics in robot navigation and multi-robot systems. Students will read, present, and discuss research papers covering the relevant topics. The instructor will give background lectures where appropriate. Topics will include: outdoor navigation, vision-based navigation, multi-robot manipulation, network configuration estimation. Students will be responsible for: reading papers, writing one-paragraph paper summaries, presenting to the class, and periodically solving analysis problems assigned by the instructor.

College: School of Engineering

Department: Computer Science

Credits: 3

Instructor permission required

College: School of Engineering

Department: Computer Science

Credits: 1

Recent advances in computational methods and tools for biology and biomedicine.

Instructor permission required

College: School of Engineering

Department: Computer Science

Credits: Hours Variable

College: School of Engineering

Department: Computer Science

Credits: Hours Variable

This course is a discussion based seminar about state of the art embedded and digital signal processing systems, with emphasis on both hardware architectures as well as software tools, programming models, and compilers. The seminar focuses on state of the art academic and commercial offerings in these areas. Cross-list: ELEC 693.

College: School of Engineering

Department: Computer Science

Credits: 3

Survey of the component and standards trends that are the basis of personal computers and digital appliances with the aim of predicting technologies, solutions, and new products five years into the future. Examples of these technologies are dual Core processors, iPods and their evolution, mobile wireless data devices, and even Google vs. Microsoft. Students will each pick a topic important to the digital lifestyle and through a series of one-on-one sessions develop a depth of understanding that is presented to the class. Cross-list: ELEC 694.

College: School of Engineering

Department: Computer Science

Credits: Hours Variable

College: School of Engineering

Department: Computer Science