Computer Science (Ph.D.)

Computer Science (Ph.D.) | Graduate

From the use of AI technology to drive advancements in healthcare to the use of blockchain technology to accelerate business growth and predict disease outbreaks, computer science is driving economic growth and innovation. Our doctoral graduates are prepared for leading careers in academia, research, industry, and government.

The Ph.D. in Computer Science at Howard's Graduate School provides intensive preparation in the analysis, design, and application of computing systems to solve complex issues in healthcare, transportation, cybersecurity, data science, and many other areas. Our program welcomes applicants with a strong aptitude for mathematics or programming or a background in computer science, mathematics, business, or other related disciplines. Our Ph.D. program will prepare you, like so many of our graduate alumni, for a postdoctoral position, faculty appointment, or a career in research, industry, or government. As a doctoral student in Computer Science student, you may choose from five distinct areas of specialization: software engineering, cybersecurity, algorithms and machine learning, data communications, and computer systems. You will also gain foundational computer and information systems theory knowledge and practical training in programming languages, data mining and analysis, and modeling. In Washington, D.C., there is no shortage of employment opportunities at federal agencies and technology firms that you will have access to. Our students benefit from a highly collegial atmosphere and work closely with a faculty research advisor on grant-funded research. Our Computer Science faculty have expertise in various areas, including artificial intelligence, machine learning, data mining, distributed systems, information assurance, computer architecture, bioinformatics, human-computer interaction, privacy and security, networks, and intelligent interfaces. Qualified Ph.D. students can also enroll in the Graduate Certificate in Cybersecurity further enhancing their marketability in the industry.  

Program Snapshot

      ❱  72 credit hours
      ❱  Full-time
      ❱  On-campus format
      ❱  Degree: Ph.D. 

Application Deadlines

Spring 2025 entry: 
      ❱  Nov. 15, 2024 (final deadline)

Fall 2025 entry: 
      ❱  Dec. 1, 2024 (early deadline)
      ❱  Feb. 15, 2025 (priority deadline)
      ❱  Apr. 15, 2025 (final deadline)

Applicants should submit their applications as early as possible for earlier consideration of departmental funding opportunities. Applicants have until the final deadline to apply. However, applications will be reviewed on a rolling basis throughout the admissions cycle. 

Transfer credits accepted (reviewed by committee; 24 credits hours from a relevant master's degree may be transferred to Ph.D.)

• Degree Classification: Graduate
• Related Degrees: Ph.D.

Application for Admission

• Online EngineeringCAS application
• Statement of purpose/ Statement of academic interest (500-1,000 words)
• GRE scores not required 
• Official transcripts sent to EngineeringCAS
• 3 letters of recommendation
• Bachelor's degree from an accredited college or university or the international equivalent 
• Resume or Curriculum Vitae
• Autobiographical statement (500-750 words)

GRE Required?

• No

GRE Preferred Minimums    

• GRE Verbal Reasoning: N/A
• GRE Quantitative Reasoning: N/A
• GRE Analytical Writing: N/A

GPA Required Minimums    

• Overall GPA minimum: 3.0
• Undergrad GPA minimum: 3.0

Prerequisite Courses (Recommended)

The following course prerequisites are recommended. No expiration date for recommended prerequisites.

• Programming (6 semester credit hrs of programming coursework or working knowledge of at least 2 programming languages including C, C++, or Java)
• Data Structures (3 semester credit hrs or a course that exposes students to basic data structures of linked lists, stacks, queues, and trees. Applicants should have extensive experience in writing programs that implement algorithms for manipulating these data structures)
• Machine Organization (3 semester credit hrs or a course involving machine organization.This requirement can be fulfilled by a course in operating systems, assembly language programming, computer organization, computer architecture, or a similar course)
• Operating Systems (3 semester credit hrs or a course in operating systems)
• Algorithms (3 semester credit hrs or a course in computer science that requires data structures as a prerequisite. This requirement can be fulfilled by a course in algorithms, algorithm analysis, numerical analysis, or a similar course algorithm analysis, numerical analysis, or a similar course)
• Probability or Statistics (3 semester credit hrs of probability and statistics or an equivalent course)
• Calculus (6 semester credit hrs of a calculus course)
• Differential Equations, Linear or Abstract Algebra, or Discrete Math (3 semester credit hrs of upper-level courses in differential equations, linear algebra, abstract algebra, or discrete mathematics. The course should have calculus as a prerequisite)

Reference Requirements    

Evaluator type accepted:

• Professor (Required)
• Supervisor/Manager
• Coworker

Evaluator type not accepted:

• Friend
• Family Member
• Clergy
• Other