Computer Science

Darko Stefanovic, Chair
Computer Science Department
Farris Engineering Center 100
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
Gruia-Catilin Roman, Ph.D., University of Pennsylvania
Jared C. Saia, Ph.D., University of Washington
Darko Stefanovic, Ph.D., University of Massachusetts

Associate Professors
David H. Ackley, Ph.D., Carnegie Mellon University
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
Shuang Luan, Ph.D., University of Notre Dame
Melanie Moses, Ph.D., University of New Mexico
Lance R. Williams, Ph.D., University of Massachusetts

Assistant Professors
Trilce Estrada, Ph.D., University of Delaware
Patrick Kelley, Ph.D., Carnegie Mellon University
Abdullah Mueen, Ph.D., University of California (Riverside)
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)
George F. Luger, Ph.D., University of Pennsylvania
Arthur B. Maccabe, Ph.D., Georgia Tech
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 undergraduate program is accredited by the Computing Accreditation Commission of ABET. 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.


Associated Programs

Undergraduate Program


Graduate Program



Courses

CS 105L. Introduction to Computer Programming. (3)



CS 108L. Computer Science for All: An Introduction to Computational Science and Modeling. (3)



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 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 442 / 542. Introduction to Parallel Processing. (3)



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



CS 454 / 554. Compiler Construction. (3)



CS 456 / 556. Advanced Declarative Programming. (3)



CS **460. Software Engineering. (3)



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



CS 467 / 567. Principles and Applications of Big Data. (3)



CS *471. Introduction to Scientific Computing. (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 495 / 595. Advanced Topics in Computer Science. (3, no limit Δ)



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 510. Mobile Computing. (3)



CS 512. Introduction to Computer Graphics. (3)



CS 520. Topics in Interdisciplinary Biological and Biomedical Sciences. (3, no limit Δ)



CS 521. Data Mining Techniques. (3)



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



CS 523. Complex Adaptive Systems. (3)



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



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



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



CS 533. Experimental Methods in Computer Science. (3)



CS 542 / 442. Introduction to Parallel Processing. (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 556 / 456. Advanced Declarative Programming. (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 567 / 467. Principles and Applications of Big Data. (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 595 / 495. Advanced Topics in Computer Science. (3, no limit Δ)



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



CS 600. Computer Science Research Practicum. (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