Engineering and Computational Sciences

Ph.D. in Engineering and Computational Sciences (ENCS)

Associate Dean of Research and Graduate Studies
Dr. Catherine Armwood-Gordon, carmwood@tnstate.edu, Office: 615-963-5416

The Ph.D. in Engineering and Computational Sciences ENCS is a multidisciplinary research-based program that integrates the strengths of various disciplines of computer science, electrical and computer engineering, mechanical and manufacturing engineering, civil engineering, and systems engineering. The curriculum provides advanced knowledge and research experiences in the following concentration areas: (1) Engineering Systems and (2) Computational Sciences. The program prepares graduates for successful engagement in research and development, academia, and various research-based engineering industries.

Requirement	Hours	Description
Group I : PhD Common Core	12	4 common courses for all PhD students.
Group II: Concentration Core	9	3 courses required for students in a specific concentration. Students Select Engineering Systems Concentration or Computational Sciences Concentration
Group III: Specialty Electives	27	9 courses across specialty areas within a concentration. Should be selected in consultation with the student’s advisor and dissertation committee.
Group IV: Dissertation Hours	24	Dissertation research hours.
Professional Development and Ethics	0	This course will introduce PhD students to ethical issues related to the research enterprise and the responsible conduct of research, it will also cover topics related to professional development and preparation for careers in academia, research, and industry.
PhD Seminar	0	This course exposes students to the most recent research developments in the areas of Data Sciences, Cyber-Security, Networking and Engineering Systems Design, Modeling, and Manufacturing. Students attend weekly seminars delivered by invited engineers, computer scientists, and other professionals. Enrollment required each semester.
Total hours required	72

Admissions Policy:

For admission to the Ph.D. in ENCS program, the student must:

Have a Master of Science in an engineering discipline or computer science, a Master of Engineering, or a master’s degree in a closely related field. Students with B.S. degrees with documented exceptional academic performance will also be considered.
Submit a certificate of proficiency in English with the required scores as noted in the current TSU Graduate Catalog (for students that have a B.S. and/or master’s degree(s) from a foreign university).
Have a minimum cumulative grade point average (GPA) of 3.30 on a 4.0 scale for their master’s degree to be eligible for unconditional admission to the Ph.D. program.
Have above average grades in all of the pre-requisite courses in related mathematics, engineering, and computer science courses:
1. Differential Equations
2. Engineering Design
3. Computer Programming

Degree Requirements:

Students must maintain a 3.0 GPA during matriculation..
The Ph.D. Program requires a total of 72 credit hours after the B.S. degree as outlined in the curriculum.
Passing of the Comprehensive Written Examination, administered in two parts: Group I courses (2 courses from the common core) and Group II courses (2 courses from the concentration courses).
Passing of the dissertation proposal within 2 semesters after passing the comprehensive written exam (and at least one semester before defending the dissertation research).
After the approval of the dissertation proposal, students must complete dissertation research and submit completed dissertation to the advisory committee for approval.
Upon approval by the advisory committee and the graduate school, the student must defend the research before the advisory committee at a public seminar before the faculty, students, alumni and/or industrial representatives.
Upon successful oral defense of the research, submission of the written dissertation, and approval by the Coordinator of the Ph.D. program, the major advisor with the consent of the Ph.D. Advisory Committee will initiate recommendation for awarding of the degree.

ENCS Courses

Course Name	Course Number	Credit Hours
Group I: Common PhD Courses (12 Hours)
Advanced Computing	ENCS 6020	3
Advanced Applied Mathematics	ENCS 6010	3
Modeling and Simulation of Cyber Physical Systems	ENCS 6030	3
Software Engineering or Systems Engineering	COMP 5100	3
Software Engineering or Systems Engineering	CISE 5040	3
Group IIA: Engineering Systems Concentration Courses (9 Hours)
Engineering Design Optimization	ENCS 6200	3
Engineering Management And Quality Control	ENCS 6210	3
Engineering Statistics And Probability	ENCS 6260	3
Engineering Systems Concentration Specialty Electives (27 Hours)
Robotics, Control Systems and Manufacturing
Advanced Robotic Systems	ENCS 6110	3
Artificial Intelligence Robotics	ENCS 7100	3
Mechatronics Systems Design	ENCS 6120	3
Principles of Cyber Physical Systems	ENCS 7110	3
Systems Engineering and Modeling
Intelligent Systems and Machine Learning	CISE 5110	3
Finite System Analysis	ENCS 6280	3
Estimation Theory and System Identification	ENCS 7200	3
Advanced Materials
Fundamentals of Nanomaterials	ENCS 5300	3
Micro- and Nano-fabrication and Characterization Techniques	ENCS 6300	3
Solid State Physics and Devices	ENCS 7300	3
Transportation and Environmental Systems
Transportation Facilities Evaluation and Design	ENCS 6410	3
Transportation and Environmental Sustainability	ENCS 6420	3
Pavement, Environmental and Ground Water Design	ENCS 6430	3
Environmental and Transportation Risk Analysis	ENCS 6440	3
Thermal Sciences and Energy
Analysis of Modern Energy Conversion and Conservation Systems	ENCS 6530	3
Introduction to Computational Fluid Dynamics	MEEN 5430	3
Special Topics in Power Engineering	EECE 5330	3
Group IIB: Computational Sciences Concentration Courses (9 Hours)
Advanced Algorithms Design and Analysis	COMP 5200	3
Network Programming and Computing	COMP 6700	3
Distributed Algorithm Design and Data Analysis or Digital and Computer Communications	COMP 6400	3
	ENCS 6960	3
Computational Sciences Concentration Specialty Electives (27 Hours)
Data Sciences and Analytics
Hybrid and Relational Databases	COMP 5400	3
Machine Learning	COMP 6200	3
Data Mining	ENCS 6620	3
HPC and Bio-Informatics
Introduction to High-Performance Computing	COMP 5520	3
Introduction to Bioinformatics	COMP 5800	3
Bioinformatics and Computational Biology	COMP 6100	3
High-Performance Computing Applications	ENCS 7700	3
Cyber-security and Networking
Cryptography and Computer Security	COMP 5720	3
Introduction to Cyber Security	ENCS 6800	3
Graph Theory and Networks Analysis	ENCS 7800	3
Communications and Signal Processing
Digital and Computer Communications	ENCS 6960	3
Machine Learning	COMP 6200	3
Computer Vision	ENCS 7900	3
Applied Signal Processing	ENCS 7930	3
Group III: Other Courses (24 Hours)
Professional Development and Ethics	ENCS 7070	0
PhD Seminar	ENCS 7080	0
Dissertation Courses	ENCS 7090	24

ENCS Course Descriptions PhD in .pdf

Thesis Dissertation Guidelines

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