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.

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.

Fundamental concepts of intelligent agents and multiagent interactions using science fiction short stories and movie clips; topics include decision theory, game theory, auctions, swarms, teamwork, emotions.

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

HTML progrmming for creating home pages, installation and modification of Web server, writing progrms that offer enhanced services, manipulation of graphics, video and sound.

Computer organization and architecture. Concepts include: computer evolution and performance, system busses, cache memory, internal and external memory, input/output, operating system support, computer arithmetic.

Object-oriented programming techniques, basic data structures, elementary complexity analysis to model, simulate & solve engineering problems.

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.

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

Architectural principles underlying modern game console hardware design; introduction to the programming techniques, optimization strategies, and hardware insights to create powerful games.

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; MIPS instruction set architecture; performance; computer arithmetic; organization and detailed implementation of non-pipelined and pipelined processors; cache and virtual memory.

Techniques and tools needed to construct/evaluate models of computer systems and applications. Analytical and simulation methods, capacity planning, performance/reliability evaluation, and decision-making.

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. Duplicates credit in former CSCI 477.

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.

File input/output techniques, basic methods for file organization, file managers, principles of databases, conceptual data models, and query languages.

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.

b: Design, iterative stage 2 prototyping and development of a refined game.

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.

Selected topics in computer science.

Linear equations and matrices, Gauss elimination, error estimates, iteration techniques; contractive mappings, Newton's method; matrix eigenvalue problems; least-squares approximation, Newton-Cotes and Gaussian quadratures; finite difference methods. Prerequisite: linear algebra and calculus.

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

Exploration of parallel programming paradigms, parallel computing architectures, hands-on parallel programming assignments, contemporary and historical examples and their impact, context with parallel algorithms. Recommended preparation: CSCI 102 or CSCI 455; EE 452 or EE 457.

Markov processes in discrete or continuous time; renewal processes; martingales; brownian motion and diffusion theory; random walks, inventory models, population growth, queuing models, shot noise.

Individual analysis, planning, development and maintenance of a software product or development artifact, using the principles and practices of PSP. Analysis of project's lessons learned.

Fundamental techniques of computer animation and simulation, knowledge and/or experience in the design, scripting, production and post-production stages of computer animation.

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.

Networked game communication architectures, protocol development, architecting networked game AI clients/services. Character following, knowledge representation and reasoning, dynamic play strategies, search, learning, and planning. 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.

This course provides students in various areas of game specialization the practice of design, iterative stage 2 prototyping and development of a refined game.

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.

Investigate computational systems in which several software agents or software agents and humans interact.

Examination of the issues which enable computers to employ and understand natural language; knowledge representation, memory modeling, parsing, language analysis, story understanding, and generation. Recommended preparation: CSCI 562.

Fundamental skills for modeling and controlling of dynamic systems for robotic applications and graphics animations; control theory; kinematics; dynamics; sensor processing; real-time operating systems; robot labs.

Survey of techniques for the design of large-scale, distributed, networked, embedded systems. Examples include sensor/actuator networks, wearable computing, distributed robotics and smart spaces.

Foundations and techniques in information integration as it applies to the Web, including view integration, wrapper learning, record linkage, and streaming dataflow execution. Recommended preparation: CSCI 571, CSCI 573

Introduction to nanotechnology. Nanorobotic systems: sensing; actuation and propulsion; control; communication; power; programming and coordination of robot swarms. Nanomanipulation and nanoassembly with atomic force microscopes. Graduate standing in natural science or engineering.

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

Asynchronous channels and architectures; implementation design styles; controller synthesis; hazards, and races; Petri-nets; performance analysis, and optimization; globally asynchronous locally synchronous design. Open only to graduate students.

Computer algorithms for system optimization. Search techniques, gradient methods, parameter optimization in control systems. Optimization with constraints; linear and nonlinear programming. Random search techniques.

Structure of real-time computer systems; analog signals and devices; scheduling, synchronization of multiprocessors; reliability, availability; serial/parallel computations; real-time operating systems and languages; design examples.

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

Distribution free classification, discriminant functions, training algorithms; statistical classification, parametric and nonparametric techniques, potential functions; non-supervised learning.

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

Formal grammars; parsing methods and lexical analysis; code generation; local and global code optimization; and dynamic allocation.

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

Advanced topics in AI, covering reasoning under uncertainty, decision theory, knowledge-based and inductive learning. Recommended preparation: a previous undergraduate or graduate level course in AI

Mobile ad hoc networks: ad hoc and geographic routing, resource discovery, medium access control, IP-mobility, mobility modeling, wired-wireless networks. Lab: wireless LAN measurement, mobile-IP, ad hoc routing. Recommended preparation: programming, network simulation

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++

b: Software development, test, implemetation, and maintenance methods. CASE tools and software envirnments. Software product engineering, configuration management, quaility engineering, documentation. Application via projects.

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

Formal systems, first order logic, truth, completeness, compactness, Godel incompleteness, recursive functions, undecidability. Selected applications, e.g., theorem proving, artificial intelligence, program verification, databases, computational complexity.

Mathematical models and computer representations for three-dimensional solids; underlying topics from set theory, geometry and topology. Fundamental algorithms; applications to CAD/CAM and robotics.

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.

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.

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.

Review of neural mechanism of visuo-motor coordination, and methods for constructing models of these mechanisms. Topics include locomotion, cognitive maps, looking, reaching and grasping.

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.

Computational research in music cognition, including computational methods for music analysis, such as the abstracting and extracting of pitch and time structures. Computational research in expressive performance, the manipulation of parameters (e.g., tempo, loudness, articulation) to focus attention, facilitate parsing, and create emotional affect. Open to graduate engineering students only. Recommended preparation: programming experience (C++ or Java), basic signal processing and music theory.

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.