Computer Science

Computer Science Department
Farris Engineering Center 157
MSC01 1130
1 University of New Mexico
Albuquerque, NM 87131-0001
(505) 277-3112

Professors
Stephanie Forrest, Ph.D., University of Michigan
Deepak Kapur, Ph.D., Massachusetts Institute of Technology
George F. Luger, Ph.D., University of Pennsylvania

Associate Professors
David H. Ackley, Ph.D., Carnegie Mellon University
Lance R. Williams, Ph.D., University of Massachusetts
Jared C. Saia, Ph.D., University of Washington
Darko J. Stefanovic, Ph.D., University of Massachusetts
Shuang Luan, Ph.D., Univerisity of Notre Dame

Assistant Professors
Dorian Arnold, Ph.D., University of Wisconsin (Madison)
Patrick G. Bridges, Ph.D., University of Arizona
Jedidiah Crandall, Ph.D., University of California (Davis)
Thomas Hayes, Ph.D., University of Chicago
Joseph Kniss, Ph.D., University of Utah
Melanie Moses, Ph.D., University of New Mexico
Lydia Tapia, Ph.D., Texas A & M, College Station

Professors Emeriti
Edward S. Angel, Ph.D., University of Southern California
John M. Brayer, Ph.D., Purdue University
Charles P. Crowley, Ph.D., University of Washington
Edgar J. Gilbert, Ph.D., University of California (Berkeley)
Paul A. Helman, Ph.D., University of Michigan
Harold K. Knudsen, Ph.D., University of California (Berkeley)
Bernard M. E. Moret, Ph.D., University of Tennessee
Henry D. Shapiro, Ph.D., University of Illinois
Brian T. Smith, Ph.D., University of Toronto
Patricia A. Stans, Ph.D., New Mexico State University
Robert L. Veroff, Ph.D., Northwestern University


Introduction

The program of this department is intended to provide students with a well rounded general education and a broad set of skills and knowledge in the basic areas of computer programming and computer science. The B.S. program is accredited by the Computing Accreditation Commission of ABET, http://www.abet.org. The core requirements in mathematics, computer science and electrical engineering cover the basic principles and methodologies of discrete mathematics, problem analysis and algorithmic development, assembly language, high level programming languages, language design and implementation, operating systems, data structures, analysis of algorithms, computer architecture and software engineering.


Courses

CS 131L. Introduction to Unix® and the World Wide Web. (2)



CS 132L. Introduction to Unix® and the World Wide Web. (1)



CS 150L. Computing for Business Students. (3)



CS 151L. Computer Programming Fundamentals for Non-Majors. (3)



CS 152L. Computer Programming Fundamentals. (3)



CS 241L. Data Organization. (3)



CS 251L. Intermediate Programming. (3)



CS 259L. Data Structures with JAVA. (5)



CS 261. Mathematical Foundations of Computer Science. (3)



CS 293. Social and Ethical Issues in Computing. (1)



CS 341L. Introduction to Computer Architecture and Organization. (3)



CS 351L. Design of Large Programs. (4)



CS 357L. Declarative Programming. (3)



CS 361L. Data Structures and Algorithms. (3)



CS 362. Data Structures and Algorithms II. (3)



CS 365. Introduction to Scientific Modeling. (3)



CS *375. Introduction to Numerical Computing. (3)



CS 390. Topics in Computer Science for Non-Majors–Undergraduate. (1-3, no limit Δ)



CS 394. Computer Generated Imagery and Animation. (3)



CS 412. Introduction to Computer Graphics: Scanline Algorithms. (3)



CS 413. Introduction to Ray and Vector Graphics. (3)



CS 422 / 522. Digital Image Processing. (3)



CS **423. Introduction to Complex Adaptive Systems. (3)



CS 427 / 527. Principles of Artificially Intelligent Machines. (3)



CS 429 / 529. Introduction to Machine Learning. (3)



CS *441. Modern Computer Architecture. (3)



CS *442. Introduction to Parallel Processing. (3)



CS 444/544. Introduction to Cybersecurity. (3)



CS 454 / 554. Compiler Construction. (3)



CS **460. Software Engineering. (3)



CS 464 / 564. Introduction to Database Management. (3)



CS *471. Introduction to Scientific Computing. (3)



CS 473 / 573. Physics and Computation. (3)



CS **481. Computer Operating Systems. (3)



CS **485. Introduction to Computer Networks. (3)



CS 491. Special Topics–Undergraduates. (1-6 to a maximum of 12 Δ)



CS **492. Introduction to Computers in Manufacturing. (3)



CS **494. Advanced Topics in Computer Generated Imaging. (3)



CS 499. Individual Study–Undergraduate. (1-3 to a maximum of 6 Δ)



CS 500. Introduction to the Theory of Computation. (3)



CS 506. Computational Geometry. (3)



CS 509. Parallel Algorithms. (3)



CS 510. Randomized Algorithms. (3)



CS 511. Algorithms in the Real World. (3)



CS 512. Advanced Image Synthesis. (3)



CS 513. Real-Time Rendering and Graphics Hardware. (3)



CS 515. Scientific and Information Visualization. (3)



CS 520. Topics in Interdisciplinary Biological and Biomedical Sciences. (3, unlimited Δ)



CS 522 / 422. Digital Image Processing. (3)



CS 523. Complex Adaptive Systems. (3)



CS 524. Collaborative Interdiciplinary Teaching. (3)



CS 527 / 427. Principles of Artificially Intelligent Machines. (3)



CS 528. Advanced Topics in Artificial Intelligence. (3)



CS 529 / 429. Introduction to Machine Learning. (3)



CS 530. Geometric and Probabilistic Methods in Computer Science. (3)



CS 531. Pattern Recognition. (3)



CS 532. Computer Vision. (3)



CS 537. Automated Reasoning. (3)



CS 544/444. Introduction to Cybersecurity. (3)



CS 547. Neural Networks. (3)



CS 550. Programming Languages and Systems. (3)



CS 551. Individual Study–Graduate. (1-3 to a maximum of 6 Δ)



CS 554 / 454. Compiler Construction. (3)



CS 555. Advanced Topics in Compiler Construction. (3)



CS 557. Selected Topics in Numerical Analysis. (3)



CS 558. Software Foundations. (3)



CS 561. Algorithms/Data Structure. (3)



CS 564 / 464. Introduction to Database Management. (3)



CS 565. Topics in Database Management. (3)



CS 569. Computational Medicine. (3)



CS 573 / 473. Physics and Computation. (3)



CS 575. Introductory Numerical Analysis: Numerical Linear Algebra. (3)



CS 576. Introductory Numerical Analysis: Approximation and Differential Equations. (3)



CS 580. The Specification of Software Systems. (3)



CS 581. Fundamentals of Software Testing. (3)



CS 583. Object-Oriented Testing. (3)



CS 585. Computer Networks. (3)



CS 587. Advanced Operating Systems. (3)



CS **590. Topics in Computer Science for Non-Majors–Graduate. (1-3, no limit Δ)



CS 591. Special Topics–Graduate. (1-6, no limit Δ)



CS 592. Colloquium. (1 to a maximum of 4 Δ)



CS 599. Master’s Thesis. (1-6, no limit Δ)



CS 609. Advanced Parallel Algorithms. (3)



CS 650. Reading and Research. (3 to a maximum of 6 Δ)



CS 691. Seminar in Computer Science. (1-6 to a maximum of 12 Δ)



CS 699. Dissertation. (3-12, no limit Δ)



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Office of the Registrar

MSC 11 6325
1 University of New Mexico
Albuquerque, NM 87131

Phone: (505) 277-8900
Fax: (505) 277-6809