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Doctoral (PhD)

The objective of the PhD program is to help students develop research proficiency in conceptualizing and implementing computer models and tools that address societal needs. This proficiency will enable students to analyze and review critically the scientific work in their area of interest and in the broader field. Moving through the program students will demonstrate original thought by expanding the boundaries of their field, communicating their findings in a convincing and affirming manner. 

Admission

Admission will be based on strength of applicant, evidenced in a portfolio comprising an essay in context with Loyola’s values and mission, samples of work in the field, recommendation letters, and academic performance in prior degree programs. Admission requirements will be in line with the Graduate School guidelines.

Curriculum

The doctoral program will comprise 60 credits equally divided between waivable coursework and dissertation research. The program will comprise courses at the 400 level (Masters courses including COMP 488 Advanced Topics) and 500 level (directed study, doctoral research, dissertation supervision, and doctoral study). The 500-level courses will be under the supervision of qualified faculty. These courses will focus on the development and defense of a dissertation. Prior to registering for these course, students must complete a Qualifying Event (QE). The QE is a comprehensive assessment of an individual’s preparation for completing the dissertation work.  

A minimum of 60 credits will be required. Up to 30 credits may be waived for qualified students, subject to CAS and Graduate School policies. This waiver does not relieve students from the courses they must take to establish a successful Qualifying Event. 

Areas covered by COMP 488 Advanced Topics in Computer Science  

The topics in this course will be determined by the student’s advisor. Areas to consider include Instruction, Learning, and Curriculum Design, Mathematical and Statistical Methods for Computing, Research Methods, Algorithms and Complexity, Computer Systems, Software Engineering, Machine Learning, Natural Language Processing, Programming Languages and Compilers, Cybersecurity, Internet of Things, Architecture, Data Science, and other areas of interest to faculty members.  

Dissertation development courses 

As students complete their coursework and fulfill their qualifying event, they may enroll in COMP 600 Thesis Supervision. This is a highly directed course under the supervision of the student’s dissertation advisor. Students are expected to continue enrolling in this course as they progress with their dissertation work, going through the following stages: 

  • Review open problems in computing and identify ones 
  • Work with library resources and prepare a literature review 
  • Draft a dissertation proposal
  • Develop research methodology 
  • Refine research methodology based on committee feedback 
  • Draft an outline of thesis 
  • Development of thesis and research studies/prototypes 
  • Focus on findings 
  • Review of results 
  • Final draft 
  • Defense 
Typical curriculum plan and Qualifying Event

The figure below shows the typical curriculum plan for a Ph.D. in the proposed program. Students are required to take 21 credits of MS-level coursework. This amounts to 7 courses, four of which will be at the Advanced Topics level available only to graduate students. Early on, PhD students may take MS-level courses that are open to select undergraduate students as well.  

Students that meet Graduate School and departmental requirements, may transfer up to 21 credits of coursework from a previous MS program. This transfer will shorten their path to the PhD and will place them closer to the next stage of the curriculum plan.

phd curriculum visual

The next stage of the plan includes coursework to establish qualifications for doctoral research. This stage is akin to a qualifying exam and no transfer credit can be accepted. The qualifying process spreads over courses that cover any three of the four pillar areas of computer science (theory, systems, software, and AI). Courses are selected from the advanced 400-level courses including COMP 488 Advanced Topics in CS. A grade of A is required in each of these three courses covering three areas, to establish a Qualifying Event.

After successful completion of the Qualifying Event, students may begin registering for 500-level courses that focus on their chosen research direction and the successful development and defense of a PhD thesis. No credit transfers can be accepted here. 

Sample Courses for the PhD program  

The following courses, currently offered by the department of computer science, can help prepare prospective PhD students for their research work and establish a Qualifying Event:

TheorySystemsSoftwareArtificial Intelligence
COMP 460 Algorithms & Complexity COMP 410 Operating Systems COMP 474 Software Engineering COMP 429 Natural Language Processing
COMP 471 Theory of Programming Languages COMP 439 Distributed Systems COMP 473 Advanced Object Oriented Programming COMP 458 Big Data Analytics
COMP 409 Theory of Cryptography COMP 464 High-Performance Computing COMP 453 Database Programming COMP 479 Machine Learning
  COMP 462 Computer Architecture   COMP 487 Deep Learning

The objective of the PhD program is to help students develop research proficiency in conceptualizing and implementing computer models and tools that address societal needs. This proficiency will enable students to analyze and review critically the scientific work in their area of interest and in the broader field. Moving through the program students will demonstrate original thought by expanding the boundaries of their field, communicating their findings in a convincing and affirming manner. 

Admission

Admission will be based on strength of applicant, evidenced in a portfolio comprising an essay in context with Loyola’s values and mission, samples of work in the field, recommendation letters, and academic performance in prior degree programs. Admission requirements will be in line with the Graduate School guidelines.

Curriculum

The doctoral program will comprise 60 credits equally divided between waivable coursework and dissertation research. The program will comprise courses at the 400 level (Masters courses including COMP 488 Advanced Topics) and 500 level (directed study, doctoral research, dissertation supervision, and doctoral study). The 500-level courses will be under the supervision of qualified faculty. These courses will focus on the development and defense of a dissertation. Prior to registering for these course, students must complete a Qualifying Event (QE). The QE is a comprehensive assessment of an individual’s preparation for completing the dissertation work.  

A minimum of 60 credits will be required. Up to 30 credits may be waived for qualified students, subject to CAS and Graduate School policies. This waiver does not relieve students from the courses they must take to establish a successful Qualifying Event. 

Areas covered by COMP 488 Advanced Topics in Computer Science  

The topics in this course will be determined by the student’s advisor. Areas to consider include Instruction, Learning, and Curriculum Design, Mathematical and Statistical Methods for Computing, Research Methods, Algorithms and Complexity, Computer Systems, Software Engineering, Machine Learning, Natural Language Processing, Programming Languages and Compilers, Cybersecurity, Internet of Things, Architecture, Data Science, and other areas of interest to faculty members.  

Dissertation development courses 

As students complete their coursework and fulfill their qualifying event, they may enroll in COMP 600 Thesis Supervision. This is a highly directed course under the supervision of the student’s dissertation advisor. Students are expected to continue enrolling in this course as they progress with their dissertation work, going through the following stages: 

  • Review open problems in computing and identify ones 
  • Work with library resources and prepare a literature review 
  • Draft a dissertation proposal
  • Develop research methodology 
  • Refine research methodology based on committee feedback 
  • Draft an outline of thesis 
  • Development of thesis and research studies/prototypes 
  • Focus on findings 
  • Review of results 
  • Final draft 
  • Defense 
Typical curriculum plan and Qualifying Event

The figure below shows the typical curriculum plan for a Ph.D. in the proposed program. Students are required to take 21 credits of MS-level coursework. This amounts to 7 courses, four of which will be at the Advanced Topics level available only to graduate students. Early on, PhD students may take MS-level courses that are open to select undergraduate students as well.  

Students that meet Graduate School and departmental requirements, may transfer up to 21 credits of coursework from a previous MS program. This transfer will shorten their path to the PhD and will place them closer to the next stage of the curriculum plan.

phd curriculum visual

The next stage of the plan includes coursework to establish qualifications for doctoral research. This stage is akin to a qualifying exam and no transfer credit can be accepted. The qualifying process spreads over courses that cover any three of the four pillar areas of computer science (theory, systems, software, and AI). Courses are selected from the advanced 400-level courses including COMP 488 Advanced Topics in CS. A grade of A is required in each of these three courses covering three areas, to establish a Qualifying Event.

After successful completion of the Qualifying Event, students may begin registering for 500-level courses that focus on their chosen research direction and the successful development and defense of a PhD thesis. No credit transfers can be accepted here. 

Sample Courses for the PhD program  

The following courses, currently offered by the department of computer science, can help prepare prospective PhD students for their research work and establish a Qualifying Event:

TheorySystemsSoftwareArtificial Intelligence
COMP 460 Algorithms & Complexity COMP 410 Operating Systems COMP 474 Software Engineering COMP 429 Natural Language Processing
COMP 471 Theory of Programming Languages COMP 439 Distributed Systems COMP 473 Advanced Object Oriented Programming COMP 458 Big Data Analytics
COMP 409 Theory of Cryptography COMP 464 High-Performance Computing COMP 453 Database Programming COMP 479 Machine Learning
  COMP 462 Computer Architecture   COMP 487 Deep Learning