Engineering and Computer Science

Master of Science in Computer Engineering Description

The Master's degree in Computer Engineering is designed to prepare students for career advancement, or for further studies at the doctoral level. It has two options, thesis and professional (non-thesis). It is a research-based program of study, requiring students to complete independent research that culminates in several projects, and, in one of the options, with a thesis project. Either option includes rigorous curriculum and allows students to concentrate their program in the following specialized areas: Computer Architecture and Distributed Computing; Advanced Computer Networks; VLSI Circuit Design; Robotics, Artificial Intelligence, and Machine Learning.

Admission to the program requires a Bachelor’s degree in computer engineering, electrical engineering or computer science from an accredited institution. Students not meeting this requirement will be considered for admission on an individual basis and may be admitted subject to the completion of appropriate undergraduate leveling courses to remove any deficiencies in preparation; in this case the department will recommend leveling courses, depending on the student's transcript.

Students must maintain a GPA of 3.0 or better, and make grades of C or better in all courses on the degree plan. No undergraduate courses can be counted towards this Master’s degree. A maximum of 12 graduate credit hours may be transferred.

Master of Science in Computer Engineering

Required Courses
CPEN 5341	Advanced Algorithms	3
CPEN 5343	Advanced Computer Architecture	3
CPEN 5351	Introduction to Convex Optimization	3
CPEN 5355	VLSI Architectures	3
CPEN 5378	Advanced Computer Networks	3
CPEN Electives		6
Total Hours		21

Additional Required Courses for Concentrations

Thesis

Electives - 5000-level: ELEN, COSC, MATH, or BCIS		6
CPEN 5099	Thesis Research	6

Total Hours		12

Professional (non-thesis)

CPEN Electives		6
Electives - 5000-level: ELEN, COSC, MATH, or BCIS		9
Total Hours		15

Master of Science in Mechanical Engineering Description

The Master of Science in Mechanical Engineering program is an industry-focused, practice-oriented degree that will deepen mechanical engineering skills in design, manufacturing, controls, robotics, energy, sustainability, and much more. What sets our program apart is its strong emphasis on integrating applied mechanics, computer simulations, design, and energy science and technology. The graduate program provides a strengthened technical background for mechanical engineering and other multidisciplinary problems that we intend to us as a thread in the curriculum.

Admission to the master's mechanical engineering program requires a bachelor's degree in mechanical engineering or related field of study from an accredited institution. Students not meeting this requirement will be considered for admission on an individual basis and may be admitted subject to the completion of appropriate undergraduate courses to remove any deficiencies in preparation.

Students must maintain a GPA of 3.0 or better, and make grades of C or better in all courses on the degree plan. Grades for courses completed at other institutions, or at Tarleton before the start of the master's degree, are not included in the degree plan GPA, but they are still subject to the requirement of C or better. No undergraduate courses can be counted towards the master's degree (Tarleton rule). A maximum of 12 graduate credit hours may be transferred.

Master of Science in Mechanical Engineering

Required Courses
Required Courses
MEEN 5310	Advanced Solid Mechanics	3
MEEN 5320	Optimization of Engineering Systems	3
MEEN 5330	Mechanics of Viscous Flow	3
MEEN 5333	Advanced Engineering Thermodynamics	3
MEEN 5332	Advanced heat transfer	3
MEEN 5360	Introduction to Robotics	3
Choose one from the following:		3
MATH 5305	Statistical Models
MATH 5306	Dynamical Systems
MATH 5330	Mathematical Modeling
MATH 5360	Numerical Analysis
MEEN 5390	Advanced Engineering Mathematics
Any other approved 5000 level course in MATH
Total hours		21

Additional Required Courses for Concentrations

Thesis

Choose one from the following:		3
MEEN 5311	Finite Element Analysis: Theory and Practice
MEEN 5331	Computational Methods for Fluid Mechanics and Heat Transfer
Choose one from the following:		3
MEEN 5321	Lean Six Sigma
MEEN 5340	Advanced Energy Systems
MEEN 5088	Master's Thesis	6
Total Hours		12

Professional (non-thesis)

MEEN 5311	Finite Element Analysis: Theory and Practice	3
MEEN 5321	Lean Six Sigma	3
MEEN 5331	Computational Methods for Fluid Mechanics and Heat Transfer	3
MEEN 5340	Advanced Energy Systems	3
Total Hours		12

Admission to the MEEN-MS program requires a Bachelor’s degree in mechanical engineering from an accredited institution, with a GPA of 3.0 or better. Students not meeting this requirement will be considered for admission on an individual basis and may be admitted subject to the completion of appropriate undergraduate courses to remove any deficiencies in preparation.

After receiving admission to graduate studies, the student choosing thesis option will consult with the graduate program coordinator concerning appointment of the chair of their advisory committee. The chair, in consultation with the student, will select the remainder of the committee, which will consist of no fewer than three members of the graduate faculty. The chair of the committee must be from the ENCS department, and at least one member must have an appointment to a department other than ENCS. The duties of the graduate program coordinator include responsibility for the proposed degree plan, the research proposal, the thesis and the final examination. In addition, the graduate program coordinator is responsible for advising the student on all academic matters, and, in the case of academic deficiency, initiating recommendations to the Office of Graduate Studies.

The student’s graduate program coordinator, in consultation with the student, will develop the degree plan, which must specify the thesis or non-thesis option. The degree plan may include additional coursework, if it is deemed necessary by the graduate faculty in order to address deficiencies. The degree plan must be completed and filed in accordance with Tarleton office of graduate studies requirements.

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For the thesis option, the student must prepare a thesis proposal for approval by the advisory committee and the head of the ENCS department. The Thesis Manual, which contains details regarding the preparation and submission of a thesis for approval, is available on the Graduate College website. Students who plan to pursue a thesis should obtain a copy of this manual early in their graduate program. A thesis proposal must be submitted to the Graduate Office at least one semester prior to a thesis submission. Preparation and submission of thesis must be in accordance with Tarleton office of graduate studies requirements.

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Courses used toward any degree at Tarleton or another institution may not be applied for graduate credit. If the course to be transferred was taken prior to the conferral of a degree at another institution, a letter from the registrar at that institution, stating that the course was not applied for credit toward the degree, must be submitted to the Office of Graduate Studies. A maximum of 12 credit hours may be transferred.

Courses

CPEN 5099. Thesis Research. 1-6 Credit Hours (Lecture: 1-6 Hours, Lab: 0 Hours).

Research for Master’s thesis in Computer Engineering Prerequisites: Graduate standing.

CPEN 5341. Advanced Algorithms. 3 Credit Hours (Lecture: 3 Hours, Lab: 0 Hours).

Amortized analysis, graph, network flow, string matching, matrix and polynomial algorithms, linear programming, NP-completeness, approximation algorithms, and an introduction to parallel algorithms. Prior knowledge or experience in data structures and algorithms recommended. Prerequisite: Approval of department head.

CPEN 5342. Parallel Computing and Algorithms. 3 Credit Hours (Lecture: 3 Hours, Lab: 0 Hours).

Taxonomy of parallel computers, shared-memory and message-passing architectures, theoretical models; patterns and strategies for designing parallel algorithms; parallel data structures; automatic parallelization of sequential programs; communication; synchronization and granularity; applications. Prior knowledge or experience in Computer Architecture is recommended.

CPEN 5343. Advanced Computer Architecture. 3 Credit Hours (Lecture: 3 Hours, Lab: 0 Hours).

The course is structured around the three primary building blocks of general-purpose computing systems: processors, memories, and networks. Topics include the limitations of scalar pipelines, superscalar execution, out-of-order execution, register renaming, memory disambiguation, branch prediction, and speculative execution; multithreaded, VLIW, and SIMD processors; non-blocking cache memories, and memory synchronization, consistency, and coherence; multi-core, shared-memory architectures. The course also covers techniques for quantitative analysis of computer systems, to understand and compare alternative design choices. Prior knowledge or experience in Computer Architecture is recommended. Prerequisite: Approval of department head.

CPEN 5348. Advanced VLSI Circuit Design. 3 Credit Hours (Lecture: 3 Hours, Lab: 0 Hours).

Analysis and design of key analog and mixed-signal IC blocks: analog switches, sampling circuits, switched-capacitor filters, ADCs, DACs, PLLs. Low-power design techniques and machine learning applications for analog and mixed-signal ICs. Prior knowledge or experience in Electronics II and Digital Signal Processing is recommended. Prerequisite: Approval of department head.

CPEN 5351. Introduction to Convex Optimization. 3 Credit Hours (Lecture: 3 Hours, Lab: 0 Hours).

This course introduces convex optimization problems, the basics of convex analysis, algorithms for convex optimization and their complexities, and applications of convex optimization. The course also trains students to recognize convex optimization problems that arise in scientific and engineering applications, and to use software tools to solve convex optimization problems. Prior knowledge or experience in Calculus III and Matrix Algebra is recommended. Prerequisite: Approval of department head.

CPEN 5355. VLSI Architectures. 3 Credit Hours (Lecture: 3 Hours, Lab: 0 Hours).

The course covers the most important methodologies for designing custom or semi-custom VLSI systems for typical signal processing and communications applications. Techniques for the inner and outer receiver, mapping of algorithms onto array structures, digital signal processing (DSP) systems, and field programmable gate arrays (FPGAs), programmable signal processors. Prior knowledge or experience in Computer Architecture is recommended. Prerequisite: Approval of department head.

CPEN 5361. Deep Neural Networks. 3 Credit Hours (Lecture: 3 Hours, Lab: 0 Hours).

Introduction to the principles and theory of neural networks, with emphasis on deep neural networks. Topics include convolutional networks, recurrent and LSTM networks, reinforcement learning, preprocessing, regularization, tuning and optimization, as well as mathematical and programming tools. Applications to classification, image recognition, autonomous vehicles. Prior knowledge or experience in Data Science, Machine Learning is recommended. Prerequisite: Approval of department head.

CPEN 5366. Robot Vision. 3 Credit Hours (Lecture: 3 Hours, Lab: 0 Hours).

This course aims at bridging the gap between computer vision and deep learning. It covers topics such as object detection and recognition, machine learning algorithms for computer vision, and advanced techniques for 3D computer vision. Real world applications and projects will be implemented in the areas of autonomous vehicles and robotics. Prior knowledge or experience in Computer Vision, Python, and C/C++ programming is recommended. Prerequisite: Approval of department head.

CPEN 5377. Wireless and Mobile Communication Networks. 3 Credit Hours (Lecture: 3 Hours, Lab: 0 Hours).

Advanced architectures for wireless communication networks; advanced wireless technologies; challenges and issues in designing such networks; queueing theory and other stochastic models. Prior knowledge or experience in Computer Networks or Communication Systems Theory, Probability, one semester of programming is recommended. Prerequisite: Approval of department head.

CPEN 5378. Advanced Computer Networks. 3 Credit Hours (Lecture: 3 Hours, Lab: 0 Hours).

This course concentrates on routing and inter-networking in IP networks, while addressing contemporary topics like wireless networks, security, voice and video over IP, the Internet of Things (IoT), software-defined networking, and network virtualization. Prior knowledge or experience in Computer Networks is recommended. Prerequisite: Approval of department head.

CPEN 5379. Performance of Computer and Communication Networks. 3 Credit Hours (Lecture: 3 Hours, Lab: 0 Hours).

Application of probability, Markov chains, and queueing theory to the analysis and design of computer and communication networks. Case studies in traffic shaping and multiplexing, static routing, dynamic routing, and peer-to-peer file sharing systems. Both continuous-time and discrete-time models are explored. Prior knowledge or experience in Computer Networks or Communication Systems Theory, Probability is recommended. Prerequisite: Approval of department head.

Dr. Mircea Agapie, Department Head
Department of Engineering and Computer Science
Hydrology and Engineering Building, Room 114
Box T-0390
Stephenville 76401
(254) 968-9863
(254) 968-9503
agapie@tarleton.edu
http://www.tarleton.edu/encs

Chair

Agapie, Mircea

Professors

Martinez, Denise
Agapie, Mircea

Associate professor

Reese, Richard

Assistant professors

Abu Ghazaleh, Haitham
Albert, Lynal
Huang, Arthur
Lee, Hoe-Gil
Tronicek, Zdenek
Venjataranan, Kartik
Vuddandam, Rajesh
Wyers, Eric
Xu, Jun

Engineering and Computer Science

Master of Science in Computer Engineering Description

Master of Science in Computer Engineering

Master of Science in Computer Engineering

Additional Required Courses for Concentrations

Thesis

Professional (non-thesis)

Master of Science in Mechanical Engineering Description

Master of Science in Mechanical Engineering

Master of Science in Mechanical Engineering

Additional Required Courses for Concentrations

Thesis

Professional (non-thesis)

Courses

Chair

Professors

Associate professor

Assistant professors

Writing-intensive Requirements

Shared Credit Course

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