Schedule of Classes

Introduction to the design of solutions to computer solvable problems. Algorithm design, solution implementation using a high-level programming language, program correctness and verification.

Linear lists, strings, arrays, and orthogonal lists; graphs, trees, binary trees, multilinked structures, sorting techniques; dynamic storage allocation; applications.

Boolean algebra; number systems; Boolean function synthesis; binary arithmetic; codes; combinational logic devices; sequential circuits; state machine design and implementation.

Historical, technical, and critical approach to the evolution of computer and video game architectures and game design, from its beginnings to the present day.

The principles of object-oriented programming are examined using Java. Topics include graphics, graphical user interfaces and multi-threaded programming. Duplicates credit in former CSCI 105.

The object-oriented paradigm for programming-in-the-large (using the Java language); UNIX tools for software development.

Models for discrete structures; finite state automata, regular sets. Selected applications of logic and combinatorics to program correctness, algorithms and complexity, programming language semantics and databases.

History of video games; overview of game genres; phases of video game development (concept, preproduction, production, post-production); roles of artists, programmers, designers, and producers.

Explores the aesthetic development/technical implementation necessary to achieve unique, compelling, intuitive visual design in games. Students will develop group visual game design portfolios.

Upper and lower bounds on sorting and order median. Deterministic and random computation, data structures, NP-completeness, cryptography, Turing machines and undecidability.

Organization and operation of the processor, memory and I/O of a minicomputer at the machine language level; assembly language programming; data representation and computer arithmetic.

Underlying concepts and principles required for programming video games (topics include vectors, transformations, 3-D math, geometric primitives, matrices).

Basic issues in concurrency, deadlock control, synchronization scheduling, memory management, protection and access control, inter-process communication, and structured design. Laboratory experiences with Unix-like operating system.

Designing, building and programming mobile robots; sensors, effectors, basic control theory, control architectures, some advanced topics, illustrations of state-of-the-art. Teamwork; final project tested in a robot contest. Junior standing or higher.

Network architectures; layered protocols, network service interface; local networks; long-haul networks; internal protocols; link protocols; addressing; routing; flow control; higher level protocols.

Operation and timing of 8/16/32-bit microprocessors; asynchronous and synchronous SRAM interface; burst and pipelined bus cycles, parallel and serial I/O, interrupt controller, DMA controller, bus protocols; hardware/simulation labs. Recommended preparation: EE 457

Intensive introduction to programming principles, discrete mathematics for computing, software design and software engineering concepts. Not available for credit to computer science majors, graduate or undergraduate.

Register Transfer level machine organization; performance; arithmetic; pipelined processors; exceptions, out-of-order andspeculative execution, cache, virtual memory, multi-core multi-threaded processors, cache coherence.

Rounding errors in digital computation; solution of linear algebraic systems; Newton's method for nonlinear systems; matrix eigenvalues; polynomial approximation; numerical integration; numerical solution of ordinary differential equations.

Concepts and algorithms underlying the understanding and construction of intelligent systems. Agents, problem solving, search, representation, reasoning, planning, communication, perception, robotics, neural networks.

Programming methodologies; intra-group and inter-group communication; software life-cycle; software economics. A large software project is a central aspect of the course.

Hardware for interactive graphic systems; picture representations; data structures for graphics; picture processing techniques; languages for graphics; survey of applications such as animation and simulation.

Techniques for building the core components of a game engine; 2-D/3-D graphics, collision detection, artificial intelligence algorithms, shading, programming input devices.

Individual research and readings. Not available for graduate credit.

a: Design, iterative prototyping, and development of a 1st playable level.

An original project will be constructed applying computer technology (in either hardware or software) to produce a result useful in the physics classroom or laboratory.

Computational linear algebra; solution of general nonlinear systems of equations; approximation theory using functional analysis; numerical solution of ordinary and partial differential equations.

a: Initial value problems; multistep methods, stability, convergence and error estimation, automatic stepsize control, higher order methods, systems of equations, stiff problems; boundary value problems; eigenproblems. b: Computationally efficient schemes for solving PDE numerically; stability and convergence of difference schemes, method of lines; fast direct and iterative methods for elliptic equations. Prerequisite: 501 or 502a or consent of instructor.

Populations, permutations, combinations, random variables, distribution and density functions, conditional probability and expectation,; binomial, poisson, and normal distributions; laws of large numbers, central limit theorem. Prerequisite: Consent of Instructor.

Theories of management and their application to software projects. Economic analysis of software products and processes. Software cost and schedule estimation, planning and control.

Conditions for optimality; nonlinear programming algorithms for constrained and unconstrained problems. Special problems such as quadratic, separable, fractional, geometric programming.

The principles of developing game engines targeted at modern PC and game console hardware.

Design and implementation of networked games, from the origins of the supporting technologies in distributed systems, visual simulations, networked virtual environments, and shipped games. Recommended preparation: CSCI 480 or CSCI 580 or an equivalent course in graphics.

Explore the complex engineering process required to design and build a real-time graphics engine to support physical realism on mobile devices. Recommended preparation: CSCI 480 or CSCI 580 or an equivalent course in graphics.

Team projects intended to address the multifaceted technical and creative challenges that are inherent to comprehensive game development. Recommended preparation: CSCI 522 or CTIN 488.

Protecting computer networks and systems using cryptography, authentication, authorization, intrusion detection and response. Includes lab to provide practical experience working with such systems.

Overview of the theory of human emotion, techniques for recognizing and synthesizing emotional behavior, and design application.

Linear programming models for resource allocation; simplex and revised simplex methods; duality; sensitivity; transportation problems; selected extensions to large scale, multiobjective, and special structured models.

Introduction to software methods in robotics including sensing, sensor fusion, estimation, fault tolerance, sensor planning, robot control architectures, planning and learning.

Protocol design for computer communication networks, network routing, transport protocols, internetworking.

Advanced issues in Computer Organization, Naming, Kernel Design, Protection Mechanism and Security Policies, Reliable Computing, data base OS, Secure Networks, Systems Specification, Decentralized Systems, Real Time Systems.

Modern secret codes. Public key cryptosystems of Rivest-Shamir-Adleman, Diffie-Hellman and others. The underlying number theory and computational complexity theory.

Computer architecture from a design perspective: Pipelined processors, speculative execution, VLIW, vector processors, memory systems, interconnection networks, shared-memory and message-passing multiprocessors, chip multiprocessors.

Students complete laboratory exercises in operating system and network management, distributed systems, TCP/IP, SNMP, NFS, DNS, etc. Term project required. Recommended preparation: 551, 555

Foundations of symbolic intelligent systems, search, logic, knowledge representation, planning, learning. Recommended preparation: good programming and algorithm analysis skills

Acquiring computer-tractable linguistic knowledge has always been a bottleneck in building natural language systems. We will examine statistical techniques for extracting knowledge automatically from online text.

Introduce neural modelling, distributed artificial intelligence and robotics approaches to vision, motor control and memory.

Statistical methods for building intelligent and adaptive systems that improve performance from experiences; Focus on theoretical understanding of these methods and their computational implications. Recommended preparation: Undergraduate level training or coursework in linear algebra, multivariate calculus, basic probability and statistics; an undergraduate level course in Artificial Intelligence may be helpful but is not required.

Explores fundamental techniques such as recursion, Fourier transform ordering, dynamic programming for efficient algorithm construction. Examples include arithmetic, algebraic, graph, pattern matching, sorting, searching algorithms.

Advanced study of programming languages with application to the Web. Languages for client-side and server-side processing. Examples taken from: HTML, Java, JavaScript, Perl, XML and others. Recommended preparation: knowledge of at least two programming languages

Description and recognition of objects, shape analysis, edge and region segmentation, texture, knowledge based systems, image understanding.

State-of-the-art technology for networked multimedia systems such as: system design, I/O technologies, data management, data compression, networking and telecommunications. Design of real-world multimedia solution. Recommended preparation: familiarity with C or C++

A: Software life-cycle processes; planning considerations for product definition, development, test, implemetation, maintenance. Team project. Graduate standing.

Study of concepts, principles and scope of software system architectures, including architectural styles, languages, connectors, middleware, dynamism, analysis, testing and domain-specific approaches.

Course outlines the process of creating images from 3D models. Includes transformations, shading, lighting, rastorization, texturing, and other topics.

Database system architecture; conceptual database models; semantic, object-oriented, logic-based, and relational databases; user and program interfaces; database system implementation; integrity, security, concurrency and recovery.

Federated and multi-database systems, database networking, conceptual and schematic diversity, information sharing and exchange, knowledge discovery, performance issues.

Techniques to efficiently store, manipulate, index and query geospatial information in support of real-world geographical and decision-making applications.

The design and implementation of user interface software. Study of issues relating to human/computer interaction. Visual design and real-time interfaces.

Research leading to the master's degree. Maximum units which may be applied to the degree to be determined by the department. Graded CR/NC.

Credit on acceptance of thesis. Graded IP/CR/NC.

Credit on acceptance of thesis. Graded IP/CR/NC.

Credit on acceptance of thesis. Graded IP/CR/NC.

Hands-on training on the basics of parallel computing and scientific visualization in the context of computer simulations in science and engineering.

Introduction of Ph.D. students to the broad range of computer science research. Two semesters registration required. Open to Computer Science doctoral students only. Graded CR/NC.

Course content to be selected each semester from recent developments in computer science.

Sensor network applications, design and analysis. Deployment; energy-efficiency; wireless communications; data-centric operation; capacity and lifetime; collaborative signal processing; reliability, fault-tolerance and security. Recommended preparation: EE 465, good programming/mathematical skills

Fault models; test generation; fault simulation; self-checking and self-testing circuits; design for testability; fault tolerant design techniques; case studies.

Fundamental techniques for design and analysis of algorithms. Topics include: dynamic programming; network flows; theory of NP-completeness; linear programming; approximation, randomized, and online algorithms; basic cryptography. Recommended preparation: familiarity with algorithms and discrete mathematics.

Advanced techniques in database management. Topics include optimization, cache management, data mining and knowledge discovery, decision support, spatial indexes, parallel and distributed systems, extendible storage.

Current topics in network and distributed systems; verbal and written presentation skills, effective critiquing, and evaluation.

Research leading to the doctorate. Maximum units which may be applied to the degree to be determined by the department. Graded CR/NC.

Credit on acceptance of Dissertation. Graded CR/NC.

Credit on acceptance of Dissertation. Graded CR/NC.

Credit on acceptance of Dissertation. Graded CR/NC.

Credit on acceptance of Dissertation. Graded CR/NC.

Credit on acceptance of Dissertation. Graded CR/NC.