Computer Science

      Michalis Faloutsos, Chair
      Computer Science Department
      Farris Engineering Center 100
      MSC01 1130
      1 University of New Mexico
      Albuquerque, NM 87131-0001
      (505) 277-3112

      Professors
      Michalis Faloutsos, Ph.D., University of Toronto
      Stephanie Forrest, Ph.D., University of Michigan
      Deepak Kapur, Ph.D., Massachusetts Institute of Technology
      Jared C. Saia, Ph.D., University of Washington

      Associate Professors
      David H. Ackley, Ph.D., Carnegie Mellon University
      Patrick G. Bridges, Ph.D., University of Arizona
      Jedidiah Crandall, Ph.D., University of California (Davis)
      Shuang Luan, Ph.D., University of Notre Dame
      Melanie Moses, Ph.D., University of New Mexico
      Darko J. Stefanovic, Ph.D., University of Massachusetts
      Lance R. Williams, Ph.D., University of Massachusetts

      Assistant Professors
      Dorian Arnold, Ph.D., University of Wisconsin (Madison)
      Trilce Estrada, Ph.D., University of Delaware
      Thomas Hayes, Ph.D., University of Chicago
      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
      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.


      Courses

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



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



      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 *442. 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 512. Advanced Image Synthesis. (3)



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



      CS 520. Topics in Interdisciplinary Biological and Biomedical Sciences. (3, unlimited 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 531. Pattern Recognition. (3)



      CS 532. Computer Vision. (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 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

      MSC11 6325
      1 University of New Mexico
      Albuquerque, NM 87131

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