Graduate Program

Admissions Coordinator
Shuang Luan

Department of Computer Science Application Deadlines

Fall Semester Application Deadlines
Priority for admission and consideration for financial aid will be given to applications received by January 15. International applications will be accepted until March 1, and domestic applications will be accepted until July 15.
Spring Semester Application Deadlines
Priority for admission and consideration for financial aid will be given to applications received by August 1. International applications will be accepted until August 1, and domestic applications will be accepted until November 15.


Degrees Offered

M.S. in Computer Science
Ph.D. in Computer Science


Admission

In addition to the University-wide requirements for admission to graduate study, the prospective M.S. or Ph.D. candidate must submit verbal, quantitative and analytical GRE scores (general test) as well as satisfy the following criteria for admission to graduate study:

  1. Knowledge of computer science equivalent to CS 152L, 261, 251L, 341L, 351L, 357L, 361L, 362, 441, 460 and 481.
  2. Knowledge of mathematics essential to computer science equivalent to MATH 162, 163, 314 and STAT 345.

Students lacking adequate undergraduate training may be admitted, at the discretion of the admissions committee, with the understanding that course work required to remove the deficiencies in undergraduate background will not be credited toward the graduate degree.

Each student will be assigned a graduate advisor. The student should see his or her graduate advisor before registering for the first time. The student and the advisor together will work out a course of studies which meets the student’s career objectives and which constitutes a coherent program satisfying the graduation requirements. No course shall be counted toward the required semester hours which has not been agreed on by the student and the advisor as a part of this coherent program. It is the responsibility of the student to meet the requirements and to keep the department office informed of compliance with them; in particular, the student should meet with his or her graduate advisor at least once a semester to review progress toward the degree.


Master’s Program

The M.S. in Computer Science can be completed under Plan I or Plan II.

Graduation (M.S. Plan I)

In addition to all Office of Graduate Studies requirements for the master’s degree, the department also requires the following:

  1. Thirty-two semester hours of approved graduate courses.
  2. At least 2 semester hours of CS 592 (Colloquium), taken at the University of New Mexico.
  3. At least 26 of the 32 hours must be in courses offered by the Computer Science Department at the 500 level or above.
  4. Completion of a minimum of two courses from each category below with a grade of B- or better:
    •  a. Mathematical Methods – CS 500, CS 530, CS 550, CS 561
    •  b. Empirical Methods – CS 512, CS 527, CS 529, CS 532, course in Complex Adaptive Systems (contact department for a list of acceptable courses).
    • c. Engineering/System Building Methods – CS 554, CS 580, CS 585, CS 587.
  5. Passing the master’s examination. For Plan I students, the master’s examination is the defense of thesis. For Plan II students, the master’s examination is an oral examination demonstrating mastery of core areas above.

A brochure describing the program and requirements can be obtained from the department.

Graduation (M.S. Plan II)

In addition to all Office of Graduate Studies requirements for the master’s degree, the department also requires the following:

  1. Thirty-two semester hours of approved graduate courses.
  2. At least 2 semester hours of CS 592 (Colloquium), taken at the University of New Mexico.
  3. In addition to Colloquium, at least 24 of the 32 hours must be in courses offered by the Computer Science Department at the 500 level or above.
  4. Completion of a minimum of two courses from each category below with a grade of B- or better:
    • a. Mathematical Methods – CS 500, CS 530, CS 550, CS 561
    • b. Empirical Methods – CS 512, CS 527, CS 529, CS 532, course in Complex Adaptive Systems (contact department for a list of acceptable courses).
    • c. Engineering/System Building Methods – CS 554, CS 580, CS 585, CS 587.
  5. Passing the master’s examination. For Plan I students, the master’s examination is the defense of thesis. For Plan II students, the master’s examination is an oral examination demonstrating mastery of core areas above.

Doctoral Program

The Ph.D. in Computer Science is offered through a cooperative program involving the Computer Science Departments at the University of New Mexico, New Mexico State University (Las Cruces, NM) and the New Mexico Institute of Mining and Technology (Socorro, NM). Doctoral students at the University of New Mexico may specialize in areas of current interest to the University of New Mexico faculty, or, by special arrangement, they may work in areas of interest to faculty at either of the other two universities.

Graduation (Ph.D.)

In addition to all Office of Graduate Studies requirements for the Ph.D. degree the department also requires the following:

  1. Exactly 4 semester hours of CS 592 (Colloquium), taken from the University of New Mexico. If the student enters the program with a master’s degree, the requirement is reduced to 2 hours of CS 592.
  2. At least 24 of the semester hours, exclusive of dissertation, must be completed at one of the three New Mexico universities.
  3. At least 30 semester hours, exclusive of dissertation, must be in courses numbered 500 or above. Of these hours, at most 12 may come from individual study courses (at The University of New Mexico, CS 551 and CS 650). If the student enters the program with a master’s degree, the requirement is reduced to 18 hours in courses numbered 500 and above–at most 9 of these hours may come from individual study courses.
  4. Passing marks on the written comprehensive examinations, on the oral candidacy examination and on a final oral examination in the student’s area of specialization.
  5. Every student who has passed the written comprehensive examinations must give one Colloquium per year (scheduled as part of the regular departmental colloquium series) surveying the student’s work to date.
  6. Teaching requirement for the doctorate: As a requirement for the Ph.D. in Computer Science, all students will complete a one-semester teaching assignment. Typically and preferably, this assignment will involve running a class section, including classroom lecturing; there will, however, be some flexibility in tailoring this assignment to each particular student. The student is encouraged to fulfill this requirement early in his or her studies, as the teaching experience is expected to help solidify the student’s mastery of core Computer Science material.

Students will take three sets of examinations. The first is the comprehensive examination which tests the student’s knowledge in the core areas of computer science (theory, systems and languages). Upon passing that exam, the student is allowed to work toward the doctorate. The student’s advisor and the graduate advisor or department chairperson then appoint a doctoral committee which will determine the student’s remaining program of study and conduct the candidacy examination. The candidacy examination verifies that the student possesses the specialized knowledge required for his/her area of research and ensures that the proposed dissertation topic is adequate in scope, originality and significance. The student is admitted to candidacy for the doctorate upon completion of the comprehensive and candidacy examination, with the approval of the doctoral committee and the Dean of Graduate Studies. Finally, the committee evaluates the student’s doctoral dissertation and conducts the final oral examination on the student’s area of specialization.

A brochure describing the program and requirements can be obtained from the department.

NOTE: CS 401, Theoretical Foundations of Computer Science, is primarily for graduate students who are deficient in mathematical proof techniques. This course does not carry graduate credit.


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