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137 Bell Hall

915.747.6407

computationalscience@utep.edu

The University of Texas at El Paso offers studies leading to degrees of Doctor of Philosophy (PhD) and Master of Science (M.S.) in Computational Science (CPS), operating under the direction of the College of Science. The program combines Computer Science, Applied and Computational Mathematics, and Science and Engineering disciplines. CPS is an interdisciplinary program, crossing departmental and college boundaries, that yields an integrated knowledge base for the effective solution of complex systems in which computer usage plays a fundamental role. A CPS student is to acquire an integrated understanding of techniques such as mathematical modeling, algorithmic design, computer simulation, scientific visualization, statistical processing of large data sets, and high-performance computing on parallel and distributed systems.

### Requirements for Admission

- Bachelor’s or master’s degree in any field of Mathematics, Science, or Engineering from an accredited institution in the United States, or proof of equivalent education in a foreign institution;
- Demonstration of academic achievement and potential as indicated by the results of the Graduate Record Examination (GRE) and upper-level undergraduate and/or graduate coursework;
- TOEFL score of at least 550 (paper-based), 213 (computer-based) for international applicants whose first language is not English or who have not completed a degree at a university in the U.S. or at another English-speaking institution;
- A statement of academic and professional interests and goals from the applicant; and
- Three letters of recommendation from people knowledgeable of the field.

Prospective students who have insufficient skills in mathematics, natural sciences, computers, and programming should contact the Program Director to discuss procedures leading to acceptance into the program. Students who will not be fully prepared for the PhD program can be admitted to the M.S. program.

All entering students will be assigned one Core Faculty Advisor who will help them prepare a study plan and submit it to the CPS Program Committee for approval. A CPS student is expected to maintain an overall cumulative grade point average of 3.0 or better, and to complete the program, must take at least six (6) hours in each of the following areas: Computer Science, Mathematics, and Science/Engineering classes.

### Degree Requirements

Every CPS Ph.D. student is required to take a two-part qualifying exam. The first part, which tests the student's understanding of fundamental concepts in computational science, should be taken as soon as the student has completed all of CPS 5401, 5310 and MA'IR 5329. The second part, which tests the student's computational skills, should be taken right after completion of CPS 5320. A doctoral student failing either or both of the qualifying exams will be required to do one of the following:

1. Leave the program;

2. Repeat the part(s) of the qualifying exam when it is offered the next time; or

3. Opt for continuing with an academic or professional master's degree.

Only one retake of each part of the qualifying exam is permitted. Students are expected to pass both parts of the qualifying exam by the end of two years in the program. A student qualifying to continue working towards the Ph.D. will choose a dissertation topic and advisor(s) from the CPS faculty. The current CPS faculty list and their research areas can be found at the website.

http://science.utep.edu/computationalscience/index.php/2014-06-03-15-20-29/faculty

## Degree Plan

Required Credits: 70

Code | Title | Hours |
---|---|---|

PhD in Computational Science (All courses require a grade of C or better) | ||

Required Courses: | ||

CPS 5310 | Mathematical & Comp. Modeling | 3 |

CPS 5401 | Introduction to Comp Science | 4 |

CPS 5310 | Mathematical & Comp. Modeling | 3 |

CPS 5401 | Introduction to Comp Science | 4 |

Prescribed Electives: | ||

Select two courses from the following: | 6 | |

Anal./Model of Bio Structures | ||

Intro. Bioinformatics I | ||

Intro. Bioinformatics II | ||

Post-Genomic Analysis | ||

Biosystematics | ||

Biostatistics | ||

Finite Element Method (3-0) | ||

Human-Computer Interaction | ||

Parallel & Concurrent Program | ||

Advanced Operating Systems | ||

Advanced Algorithms | ||

Interval Computations | ||

Topics/Emerg.Comput Paradigms | ||

Topics/Intelligent Computing | ||

Model-Based Software Devlpmnt | ||

Topics in Software Assurance | ||

Computational Methods for EE | ||

Operating Systems | ||

Digital Signal Processing | ||

Image Processing | ||

Computer Architecture I | ||

Computer Architecture II | ||

Network Protocols | ||

Quantit Techniq Geological Sci | ||

Digital Image Processing | ||

Geophysical Inverse Theory | ||

Reflection Seismic Data Proces | ||

Geop App-Digital Signal Proces | ||

Elemnts of Applied Functl Anal | ||

Applied Mathematics | ||

Partial Differential Equations | ||

Finite Element Methods I | ||

Comp Methods of Linear Algebra | ||

Techniques in Optimization | ||

Numer Solution Part Diff Equat | ||

Numerical Optimization | ||

Interior-Point Methods for Lin | ||

Statistics in Research | ||

Multivariate Data Analysis | ||

Time Series Analysis | ||

Statistical Computing | ||

Topics in Applied Mathematics | ||

Topics in Optimization | ||

Solid Mechanics I | ||

Solid Mechanics II | ||

Special Topics Mechanical Engr | ||

Mathematical Physics | ||

Advanced Statistical Mechanics | ||

Solid State Physics | ||

Other Electives: | ||

Select seven courses from the following: | 21 | |

Anal./Model of Bio Structures | ||

Intro. Bioinformatics I | ||

Intro. Bioinformatics II | ||

Post-Genomic Analysis | ||

Biosystematics | ||

Biostatistics | ||

Finite Element Method (3-0) | ||

Human-Computer Interaction | ||

Parallel & Concurrent Program | ||

Advanced Operating Systems | ||

Advanced Algorithms | ||

Interval Computations | ||

Topics/Emerg.Comput Paradigms | ||

Topics/Intelligent Computing | ||

Model-Based Software Devlpmnt | ||

Topics in Software Assurance | ||

Computational Methods for EE | ||

Operating Systems | ||

Digital Signal Processing | ||

Image Processing | ||

Computer Architecture I | ||

Computer Architecture II | ||

Network Protocols | ||

Quantit Techniq Geological Sci | ||

Digital Image Processing | ||

Geophysical Inverse Theory | ||

Reflection Seismic Data Proces | ||

Geop App-Digital Signal Proces | ||

Elemnts of Applied Functl Anal | ||

Applied Mathematics | ||

Partial Differential Equations | ||

Finite Element Methods I | ||

Numerical Analysis | ||

Comp Methods of Linear Algebra | ||

Techniques in Optimization | ||

Numer Solution Part Diff Equat | ||

Numerical Optimization | ||

Interior-Point Methods for Lin | ||

Statistics in Research | ||

Multivariate Data Analysis | ||

Time Series Analysis | ||

Statistical Computing | ||

Topics in Applied Mathematics | ||

Topics in Optimization | ||

Solid Mechanics I | ||

Solid Mechanics II | ||

Special Topics Mechanical Engr | ||

Mathematical Physics | ||

Advanced Statistical Mechanics | ||

Solid State Physics | ||

Research: | ||

CPS 6396 | Graduate Research (Complete eight semesters) | 24 |

Thesis: | ||

CPS 6398 & CS 6399 | Dissertation and Dissertation | 6 |

Total Hours | 71 |

PROGRAM DIRECTOR: Ming-Ying Leung

## Professors

Ming-Ying Leung

Contact Information: mleung@utep.edu; 915-747-6836

Education: BS, University of Hong Kong; MPhil, University of Hong Kong; MS, Stanford University; Ph D, Stanford University

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