Online Doctor of Philosophy in Engineering Management

Program Description

The online Ph.D. in Engineering Management is designed for professionals seeking to advance their careers in engineering and technical management roles. Throughout the program, students engage in rigorous coursework and research, gaining a deep understanding of engineering principles and their application in a management context. Graduates are equipped with the skills to effectively lead engineering teams, oversee complex projects, implement innovative strategies, and shape the future of engineering management.

Doctoral candidates are expected to undertake rigorous research that contributes original insights to the theory or practice of managing complex engineering systems. Their dissertations typically address strategic, organizational, or operational challenges at the intersection of engineering, technology, and management. Research areas may include innovation management, decision analytics, project and risk management, sustainability, or technology policy. Graduates are well-equipped for academic and research careers, as well as leadership roles in industry, government, and consulting, where they apply their expertise to drive organizational performance and inform evidence-based decision-making.

Curriculum

The program consists of a minimum of 60 credit hours divided into two stages: the classroom phase (24 credit hours) and the research phase (36 credit hours). During the research phase, the student writes and defends research on a topic related to Engineering Management. The topic is selected by the student and approved by the research advising committee.

Learn More About the Courses

SEAS 8205 Cybersecurity for Engineers: Equip engineering managers with the skills to assess cybersecurity risks, implement secure design principles, manage incident response, and leverage emerging technologies to protect critical systems, data, and infrastructure. (4 credit hours)

SEAS 8210 AI & Tech Management: Learn to evaluate AI technologies, manage implementation, mitigate risks, and leverage AI insights for strategic decision-making. Explore innovation, ethics, and AI-driven competitive advantage in technology management. (4 credit hours)

SEAS 8215 Uncertainty Modeling: Fundamental probability concepts, including probability laws, conditional probability, and Bayes’ theorem. It explores probability distributions and joint distributions, with applications in real-world scenarios. Simulate distributions and apply probabilistic methods to queueing theory and reliability modeling. (4 credit hours)

SEAS 8220 Data Science: Learn to design data collection methods, manage datasets, and apply analytical techniques to extract insights. Explore tools and strategies for effective data-driven decision-making in diverse fields. (4 credit hours)

SEAS 8225 Computational Modeling: Techniques for modeling and simulating complex systems, covering data generation, Monte Carlo methods, system dynamics, agent-based and discrete event simulation. Optimization techniques, including linear and nonlinear optimization with sensitivity analysis, and apply forecasting methods for predictive modeling. (4 credit hours)

SEAS 8299 Praxis Development for Engineering Management: Aims and purposes of the praxis. Development of praxis research strategies; developing Chapters 1 & 2 of the praxis; overview of research methods and required data. Restricted to students who have completed all required coursework for the Doctor of Engineering. (4 credit hours)

SEAS 8288 Praxis Research for Engineering Management: Independent applied research in engineering management culminating in the final praxis report and final examination for the degree of Doctor of Engineering. May be repeated for credit. Restricted to students in the D.Eng. in the field of engineering management program. (36 credit hours)

Classroom Phase Schedule

Classroom courses last 14 weeks each and meet on Saturday mornings from 9:00 AM—12:00 PM and afternoons from 1:00—4:00 PM (all times Eastern). All classes meet live online through synchronous distance learning technologies (Zoom). All classes are recorded and available for viewing within two hours of the lecture. This program is taught in a cohort format in which students take all courses in lock step. Courses cannot be taken out of sequence, attendance at all class meetings is expected, and students must remain continuously enrolled. Leaves of absence are permitted only in the case of a medical or family emergency, or deployment to active military duty.

Please see below for the dates of our upcoming cohort.

Semester	#Courses	#Credit Hours	Tentative Dates
Spring 2026	2	8	January 17—April 18, 2026
Summer 2026	2	8	May 16—August 15, 2026
Fall 2026	2	8	September 6—December 12, 2026

No classes on Thanksgiving weekend; Asynchronous class on July 4th.

Research Phase Schedule

Upon successful completion of the classroom phase, students are admitted to candidacy for the Ph.D. and will be registered for a minimum total of 36 credit hours (ch) of SEAS 8288 Dissertation Research: 

• 9 ch in Spring 2027
• 3 ch in Summer 2027 
• 9 ch Fall 2027
• 6 ch Spring 2028
• 6 ch Summer 2028
• 3 ch Fall 2028  

More than 36 credit hours of SEAS 8288 may be approved, depending on the candidate’s progress. Approved candidates will be registered for the standard number of ch per semester of extension.   

Tuition

Tuition is billed at $1700 per credit hour for the 2025-2026 year. A non-refundable tuition deposit of $995, which is applied to tuition in the first semester, is required when the student accepts admission.