Computer Science, PhD

Program Overview

ASU's Computer Science PhD program prepares students for advanced research in various areas, including AI, data science, and computer systems. The rigorous curriculum includes core courses, electives, and extensive research opportunities. Graduates are equipped for careers in research, academia, and industry, with potential paths as research scientists, data engineers, and software engineers.

Program Outline

Degree Overview:

Objectives:

• Prepare students to conduct fundamental and applied research in computer science.
• Develop and implement independent research projects.
• Generate and evaluate new theories, algorithms, and software modules to advance the field.

Description:

• Rigorous program for students with high research potential.
• Covers a wide range of areas, including:
• Artificial intelligence, machine learning, and statistical modeling
• Big data and data mining
• Computational biology
• Computer design and architecture
• Computer system security and cryptography
• Cyber-physical systems and Internet of Things
• Distributed computing and consensus protocols
• Networking and computer systems
• Novel computing paradigms (e.g., biocomputing, quantum computation)
• Social computing
• Theory, algorithms, and optimization
• Visualization and graphics
• Offers research opportunities in diverse areas.
• Can be completed in conjunction with a Master's degree.

Outline:

Structure:

• 84 credit hours total
• 18 credit hours of CSE 792 Research required, up to 54 allowed
• Additional electives and research
• Culminating Experience: 12 credit hours of CSE 799 Dissertation

Content:

• Required Core Areas (9 credit hours):
• Foundations (3 credit hours)
• Systems (3 credit hours)
• Applications (3 credit hours)
• Depth Area (3 credit hours)
• Electives (42 credit hours)
• Research
• May vary depending on research focus and chosen electives.

Assessment:

• Written comprehensive exam
• Oral comprehensive exam
• Prospectus
• Dissertation defense

Teaching:

• Taught by renowned faculty with expertise in various research areas.
• Utilizes diverse teaching methods, including lectures, seminars, and research supervision.
• Provides opportunities for independent research and collaboration.

Careers:

Potential Career Paths:

• Research scientist
• Data scientist/engineer
• Machine learning engineer
• AI scientist/engineer
• Computer science professor
• Software engineer

Outcomes:

• Graduates are prepared for careers in research and education in various settings, including academia, government, and industry.

Other:

• STEM-OPT extension available for international students on F-1 visas.
• May be eligible for concurrent degrees with other programs.
• Accelerated completion options available for qualified students.