PhD in Computer Science and Engineering

(Prerequisite: RM8500) In this course, students will explore Database Concepts, Advanced Design and Implementation, Data modeling and the importance of Data models. This course also includes Best Practices in database design and management as well as usage of data specifications. (3 credits)

(Prerequisite: RM8500) In this course, students will examine the use of operating systems, their impact of improving areas such as memory management, process scheduling, file systems, and device drivers. This course will also examine the techniques and technologies of non-distributed operating systems that benefit researcher, academicians, and practitioners. (3 credits)

(Prerequisite: RM8500) In this course, students will explore Software Engineering techniques and deepen their understanding of high-level languages and system programming. Some of the principles discussed include abstraction, algorithms, data structures, and web development. Students will also apply the methods and techniques for creating software systems using the best practices in modeling, architecture, process analysis, design, and object-orientated design patterns. This course will provide students with the principles and concepts involved in the analysis and design of large software systems. (3 credits)

(Prerequisite: RM8500) In this course students will learn Advanced Data Analysis techniques which are oftentimes associated with Data Mining. Students will evaluate various optimization and simulation models in an effort to determine which models are best suited for various markets. Students will conduct extensive analysis to determine relationships among variables within various environmental settings. (3 credits)

In this course students will research and analyze virtualization technology needed in today’s rapidly changing IT workplace. The course will focus on virtualization in software-defined data centers. Students learn to build virtual networks, implement high-availability clusters, enhance performance and security, and manage the virtual data center. (3 credits)

In this course, students will focus on the managerial aspects of information security assurance. Topics covered include access control models, information security governance, and information security program assessment and metrics. Coverage on the foundational and technical components of information security is included to reinforce key concepts. The course includes up-to-date information on changes in the field, such as national and international laws and international standards like the ISO 2700 series. (3 credits)

During this course students will learn research skills necessary for conducting research in the field of Computer Science and Engineering. Some of the principles will include formulating research questions, data analysis, theory, and identification of various research methods. This course is designed for Computer Science students planning to conduct research that involves human interaction with computer technology, controlled experiments, action research, archival analysis, case studies, and surveys.

(Prerequisites: RM8500, CS6500) This course is designed for students interested in conducting research on advanced topics in Communications Networks. This course will also examine current and emerging research topics in communication networks. Topics covered include network measurements, internet routing peer to peer networks, network protocols, network security, wireless and sensor networks. Due to the rise in Cybersecurity, A significant portion of this course will focus on Security and Networking related issues.

(Prerequisites: RM8500, CS6600) This course covers algorithms and architectures necessary for parallel and distributed database management systems. While the main focus of this course is on relational systems, issues related to all large-scale database systems will also be addressed. Some of the areas examined will include MapReduce-based distributed data management, Parallel data management, distribution architectures, distribution design, distributed query processing and optimization.

(Prerequisites: RM8500, DS7200) – This engineering related course is designed to help students understand the fabrication and design techniques associated in the design of Large-Scale Systems. Various topics will be introduced to include CMOS logic, MOSFET theory, design techniques, capacitance requirements, power consumption, performance estimation, effective circuit design, and clocking. This course will also cover the design of elementary data paths for microprocessors, including moderate-speed adders, and multipliers.

In this course, doctoral students are introduced to the purpose and nature of primary research. Students explore the foundations and concepts of applied field research. (3 credits)

(Prerequisite: Program Core Courses completed) In this course, students compare, contrast, and evaluate qualitative and quantitative methods of data analysis for solving business problems and conducting business-related field research. In week 4, the Comprehensive and qualifying exam is released as a separate course shell, IA9130. The Exam is expected to be completed concurrently while completing RM9100 and is due in week 8.

Students complete the Comprehensive & Qualifying Examination in weeks 4-8 of the RM9100 courses. The DC9130-CX course is administered concurrently with RM9100.

(Prerequisites: all program core/RM9100, DC9130-CX) This course is part of a two-course advanced research methodology sequence that is designed to assess the student’s ability to conduct independent research under the guidance of an instructor. These courses will assess the student’s ability to listen to the instructor and incorporate the instructor’s feedback. These courses will also assess the student’s ability to work productively with the instructor to accomplish the following goals including, but not limited to: choosing an appropriate a topic that aligns with the parameters set forth in the class syllabus; refining the topic; conducting the literature review; designing the study that that aligns with the parameters set forth in the class syllabus; collecting appropriate evidence; interpreting the findings; critically assessing/analyzing the evidence in relation to the problem under investigation and the research questions; critically assessing/analyzing the evidence in relation to the problem under investigation and the hypotheses (quantitative research); and writing scholarly doctoral-level research that adheres to APA guidelines. The assessment of the aforementioned personal attributes and skill-sets, in addition to the formal research knowledge and skill-sets under investigation in these two classes, are paramount to improving the student’s success later in the program when h/she is researching and writing his/her own, original dissertation project with his/her Chair.

This course is part of a two-course advanced research methodology sequence that is designed to assess the student’s ability to conduct independent research under the guidance of an instructor. These courses will assess the student’s ability to listen to the instructor and incorporate the instructor’s feedback. These courses will also assess the student’s ability to work productively with the instructor to accomplish the following goals including, but not limited to: choosing an appropriate a topic that aligns with the parameters set forth in the class syllabus; refining the topic; conducting the literature review; designing the study that that aligns with the parameters set forth in the class syllabus; collecting appropriate evidence; interpreting the findings; critically assessing/analyzing the evidence in relation to the problem under investigation and the research questions; critically assessing/analyzing the evidence in relation to the problem under investigation and the hypotheses (quantitative research); and writing scholarly doctoral-level research that adheres to APA guidelines. The assessment of the aforementioned personal attributes and skill-sets, in addition to the formal research knowledge and skill-sets under investigation in these two classes, are paramount to improving the student’s success later in the program when he/she is researching and writing his/her own, original dissertation project with his/her Chair.

(Prerequisite: Program Core, Pre-Dissertation and Research Methodologies completed) In this course, students identify a research site, describe a plan for access to the research site, identify a problem affecting the research site that can be developed into a feasible topic area for field research, and develop a working bibliography of recent and relevant peer-reviewed research that supports the theoretical framework of the proposed topic. Students apply the concept of problem-driven research as the basis for selecting a feasible and non-trivial research topic or problem.

Prerequisites: all program core, all pre-dissertation, RM9150

In this course, students continue to evaluate the feasibility of their proposed research site and the potential solutions to be studied. Students present their proposed project at the Dissertation Bootcamp at the end of this course.

This is the first course in Phase II of the doctoral plan. Phase II consists of the Research Preparation courses (DC8110, 8120, 8121, and 8130) in which doctoral students follow a structured approach to designing their dissertation study, refining their research question/s, and developing the operational details for their study. The focus is on clearly specifying the assessment criteria and organizational requirements needed to justify a proposed improvement in professional practice, and on designing and implementing such an assessment. The goal of the entire course sequence is to complete the dissertation proposal (Chapters 1, 2, 3 and 4.1). In this seminar, students will revisit the foundations of research methods and apply them to the modifications required for creating the required dissertation deliverables. DC8110 is the first course in which students start developing the dissertation proposal (Chapters 1-4.1). Concepts covered include: research problems, questions and hypotheses, data types, quantitative and qualitative approaches, research designs, variables and scales, data collection instruments, and sampling.

This is the second course in Phase II of the doctoral plan. Phase II consists of the Research Preparation courses (DC8110, 8120, 8121, and 8130) in which doctoral students follow a structured approach to designing their dissertation study, refining their research question/s, and developing the operational details for their study. The focus is on clearly specifying the assessment criteria and organizational requirements needed to justify a proposed improvement in professional practice, and on designing and implementing such an assessment. The goal of the entire course sequence is to complete the dissertation proposal (Chapters 1, 2, 3 and 4.1). In this seminar, students will revisit the foundations of research methods and apply them to the modifications required for creating the required dissertation deliverables. DC8120 is the second course in which students continue developing the dissertation proposal (Chapters 1-4.1). Concepts covered include: research problems, questions and hypotheses, data types, quantitative and qualitative approaches, research designs, variables and scales, data collection instruments, and sampling.

This is the second course in Phase II of the doctoral plan. Phase II consists of the Research Preparation courses (DC8110, 8120, 8121, and 8130) in which doctoral students follow a structured approach to designing their dissertation study, refining their research question/s, and developing the operational details for their study. The focus is on clearly specifying the assessment criteria and organizational requirements needed to justify a proposed improvement in professional practice, and on designing and implementing such an assessment. The goal of the entire course sequence is to complete the dissertation proposal (Chapters 1, 2, 3 and 4.1). In this seminar, students will revisit the foundations of research methods and apply them to the modifications required for creating the required dissertation deliverables. DC8120 is the second course in which students continue developing the dissertation proposal (Chapters 1-4.1). Concepts covered include: research problems, questions and hypotheses, data types, quantitative and qualitative approaches, research designs, variables and scales, data collection instruments, and sampling.

Prerequisites: all program core, all pre-dissertation, phase I, DC8110, DC8120, DC8121

Dissertation writing

(Prerequisites: all program core, all pre-dissertation, phase I, phase II, phase III) In this course, candidates present their findings to the Dissertation Committee at the defense. (1 credit)