The doctoral program in information technology at Towson University, provides the
knowledge and research opportunities you need to position yourself for top-level leadership
or faculty positions in academia.
With a broad scope of research areas within computer science, information systems
and information technology, the Doctor of Science (D.Sc.) program prepares students
to become professors, scientists and entrepreneurs. You’ll explore data structures
and algorithms, operating systems, computer networks, cybersecurity, database systems,
project management, software engineering and human-computer interaction.
Graduates assume leadership roles in their current careers or in academic, research,
government and state-of-the-art industry positions. About half of our alumni are currently
working as professors or research scientists across the country and abroad. Many in
the private sector are promoted to higher-level positions with their current employers
or start their own ventures to develop innovative products.
Degree Requirements and Course Descriptions
The D.Sc. requires 18 credits of coursework, a qualifying examination and a minimum
of 24 credits of dissertation beyond the master’s program. Doctoral students are required
to demonstrate research capabilities and publish in reputed journals or conferences
in order to graduate. View admission and degree requirements and course descriptions in the Graduate Catalog.
AIT 790 Research Methodology, IT Technical Writing and Presentation is a required course (counted as the required 18 credits of coursework) for all D.Sc.
in IT students. This course should be taken before completing the qualifying exams.
Permission to register for dissertation credits (AIT 997) will not be granted until
AIT 790 is completed with a grade B or better.
Publications: A dissertation consisting of peer reviewed published work is required. Students are
strongly recommended to have at least three research publications in peer-reviewed
international conferences and/or journals before graduation.
Students will demonstrate a comprehensive knowledge of the fundamentals in four of
the following seven areas: data structures and algorithms, operating systems, computer
networks, database systems, project management, software engineering, and human computer
interaction.
Students will conduct and document scholarly research.
Students will present scholarly research.
Computer Science (CS) Track
Students have the option to select the Computer Science track. In addition to the
general degree requirements for the doctorate in IT, three specific CS courses (9
credits) must be taken for the track in Computer Science, with additional requirements
for the qualifying examination (given below). An IT doctoral student taking these
three courses, passing the qualifying exam in the specified areas, and successfully
completing the research requirements for the degree in a CS-related area will be eligible
to graduate with a Computer Science track.
Students who have completed one or more of the three courses as part of their master’s
degree would be required to take an additional course for each of the three courses
already completed. The additional courses must be approved by the director of the
D.Sc. in IT program.
(Note: Students in D.Sc. in IT program do not have to choose a track. You may have
more flexibility to choose the courses and qualifying exam topics without a track.)
Required Courses
COSC 600 (Advanced Data Structures and Algorithms)
COSC 519 (Operating Systems)
COSC 650 (Computer Networks)
Qualifying Exam Requirements
Students in the computer science track must pass the following areas of the qualifying
exam:
operating systems
advanced data structures and algorithms
computer networks
And ONE of the following areas:
database management systems
computer security
software engineering
Publications
Publications in this track are expected to be related to computer science.
D.Sc. in IT Forms, Guidelines, Announcements & more
accomplished and dedicated faculty mentors with diverse research interests, including
cybersecurity, artificial intelligence, universal usability, data mining, e-learning,
digital signal processing and bare machine computing
advantageous location in high-tech Baltimore/Washington corridor
small-school attention with big-school resources and facilities
