Doctor of Philosophy (PhD) in Computer Science

Total Credits: 30-36 credits (excluding dissertation)

Core Courses

1. CSCI7101 - Theory of Computation

• - Credits: 3

• - Prerequisites: Master’s degree in Computer Science or related field; foundational knowledge in algorithms and discrete mathematics

• - Description: In-depth exploration of formal models of computation, automata theory, complexity classes, and decidability.

2. CSCI7201 - Advanced Artificial Intelligence

• - Credits: 3

• - Prerequisites: CSCI5301 (Machine Learning) or equivalent graduate coursework

• - Description: Advanced topics in AI, including knowledge representation, reasoning, planning, and multi-agent systems.

3. CSCI7301 - High-Performance Computing

• - Credits: 3

• - Prerequisites: CSCI5101 (Advanced Algorithms) or equivalent

• - Description: Techniques for developing scalable algorithms and systems for large-scale computations, parallel processing, and distributed architectures.

4. CSCI7401 - Advanced Machine Learning

• - Credits: 3

• - Prerequisites: CSCI5301 (Machine Learning) or instructor approval

• - Description: Cutting-edge research in deep learning, reinforcement learning, and probabilistic models.

5. CSCI7501 - Computational Ethics & Policy

• - Credits: 2

• - Prerequisites: Graduate standing or instructor approval

• - Description: Ethical considerations, societal impacts of computing, AI governance, and policy-making.

6. CSCI7601 - Doctoral Research Methods

• - Credits: 3

• - Prerequisites: Graduate standing

• - Description: Research design, methodology, data collection, analysis techniques, and academic integrity.

7. CSCI7701 - Doctoral Seminar

• - Credits: 2

• - Prerequisites: Graduate standing

• - Description: Presentation and discussion of current research, scholarly articles, and emerging trends in computer science.

8. CSCI7901 - Dissertation Research

• - Credits: 12

• - Prerequisites: Completion of coursework, qualifying exams, and approved research proposal

• - Description: Original, independent research culminating in a dissertation, including data collection, analysis, writing, and defense.

Prerequisites & Electives

Prerequisites:

1. - Master’s degree in Computer Science or a closely related field with research experience.

2. - Successful completion of foundational courses in algorithms, systems, and AI.

3. - Passing qualifying exams and approval of the research proposal.

Elective Courses (Examples):

1. - Natural Language Processing

2. - Data Mining & Big Data Analytics

3. - Quantum Computing

4. - Robotics & Autonomous Systems

5. - Secure Multi-party Computation

6. - Ethics in AI & Computing

7. - Blockchain & Cryptocurrency

8. - Advanced Cybersecurity

Electives are chosen to deepen expertise aligned with the research focus.

Program Structure & Timeline

1. - Year 1-2: Complete coursework, pass qualifying exams, and develop a research proposal.

2. - Year 3-4: Conduct original research, write the dissertation, and prepare for defense.

3. - Final Step: Dissertation defense and graduation.