arizona state university phd computer science

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• Computer Science
• School of Computing and Augmented Intelligence

Computer Science PhD

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Arizona State University

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Data Science, Analytics and Engineering, PhD

• Program description
• At a glance
• Degree requirements
• Admission requirements
• Tuition information
• Application deadlines
• Program learning outcomes
• Career opportunities
• Contact information

Analytics, Big Data, Data Engineering, Data Science, approved for STEM-OPT extension, computing, statistics

Learn to meet the need for data-driven discovery of new knowledge and decision-making, which enhances enterprise performance as well as scientific investigation.

The PhD program in data science, analytics and engineering engages students in fundamental and applied research.

The program's educational objective is to develop each student's ability to perform original research in the development and execution of data-driven methods for solving major societal problems. This includes the ability to identify research needs, adapt existing methods and create new methods as needed. This is accomplished through a rigorous education with research and educational experiences.

Students complete a foundational core covering database management, information assurance, statistical learning and statistical theory before choosing to focus on data analytics or data engineering. The program culminates in the production of a dissertation.

This program may be eligible for an Optional Practical Training extension for up to 36 months. This OPT work authorization term may help international students gain skills and experience in the U.S. Those interested in an OPT extension should review ASU degrees that qualify for the STEM-OPT extension at ASU's International Students and Scholars Center website.

The OPT extension only applies to students on an F-1 visa and does not apply to students completing the degree through ASU Online.

• College/school: Ira A. Fulton Schools of Engineering
• Location: Tempe

84 credit hours, a written comprehensive exam, an oral comprehensive exam, a prospectus and a dissertation

Required Core (12 credit hours) CSE 511 Data Processing at Scale (3) CSE 543 Information Assurance and Security (3) CSE 572 Data Mining (3) or IEE 520 Statistical Learning for Data Mining (3) or EEE 549 Statistical Machine Learning: From Theory to Practice (3) IEE 670 Mathematical Statistics (3) or STP 502 Theory of Statistics II: Inference (3) or EEE 554 Probability and Random Processes (3)

Electives and Additional Research (39 credit hours)

Research (12 credit hours) DSE 792 Research (12)

Other Requirements (9 credit hours) data engineering coursework or data analytics coursework

Culminating Experience (12 credit hours) DSE 799 Dissertation (12)

Additional Curriculum Information All students must take qualifying exams covering the required core courses within one year of matriculation into the program.

The dissertation prospectus should be submitted and its oral defense completed no later than one year following completion of the 60th credit hour and also no later than the fourth year in the program.

Students must select coursework from either the data engineering or the data analytics requirements. Students should see the academic unit for the approved course list.

Students cannot take a data engineering or data analytics course and have it meet an elective requirement at the same time. Students need to take a different elective course to reach the number of credit hours required for the program. Other coursework may be used with the approval of the academic unit to fulfill these requirements.

Twelve credit hours of DSE 792 Research are required, and up to 24 credit hours are allowed on the plan of study. Students with research hours in excess of 12 will add these credit hours to their electives and additional research.

Electives include:

• additional DSE 792 Research credit hours (up to 12 credit hours allowed beyond the required 12)
• approved elective courses, of which up to three credit hours of DSE 790: Reading and Conference are permitted, with approval.

When approved by the student's supervisory committee and the Graduate College, this program allows 30 credit hours from a previously awarded master's degree to be used for this degree. If students do not have a previously awarded master's degree, the 30 hours of coursework are to be made up of electives to reach the required 84 credit hours.

Applicants must fulfill the requirements of both the Graduate College and the Ira A. Fulton Schools of Engineering.

Applicants are eligible to apply to the program if they have earned a bachelor's or master's degree in engineering, computer science, mathematics, statistics or a related field from a regionally accredited institution.

Applicants must have a minimum cumulative GPA of 3.00 (scale is 4.00 = "A") in the last 60 hours of their first bachelor's degree program or a minimum cumulative GPA of 3.00 (scale is 4.00 = "A") in an applicable master's degree program.

Applicants are required to submit:

• graduate admission application and application fee
• official transcripts
• two letters of recommendation
• letter of intent or written statement
• proof of English proficiency

Additional Application Information An applicant whose native language is not English must provide proof of English proficiency regardless of their current residency.

ASU does not accept the GRE® General Test at home edition.

If the student is assigned any deficiency coursework upon admission, those classes must be completed with a grade of "B" (scale is 4.00 = "A") or higher within two semesters of admission to the program. Deficiency courses do not apply to the total credit hours required to complete the degree program.

Deficiency courses are: CSE 205 Object-oriented Programming and Data Structures IEE 380 Probability and Statistics for Engineering Problem Solving MAT 242 Elementary Linear Algebra or MAT 342 Linear Algebra or MAT 343 Applied Linear Algebra MAT 267 Calculus for Engineers III

Program learning outcomes identify what a student will learn or be able to do upon completion of their program. This program has the following program outcomes:

• Apply the tools and methods from industrial statistics, operations research, machine learning, computer science and computer engineering on solving data analytic problems.
• Manage large, heterogeneous data sets for knowledge discovery.
• Conduct research resulting in an original contribution to knowledge in data sciences.

Graduates demonstrate proficiency with existing methodology and significant accomplishment at advancing the state of the art in their chosen area, enabling them to pursue careers in the following fields:

• advanced research

Computer Science and Engineering Program | CTRPT 105 [email protected] 480-965-3199

Doctoral Program (Ph.D.)

General overview of the ph.d. degree.

The Ph.D. program is designed to provide students with advanced coursework and substantive research experience to prepare graduates to be the leaders in industry and academia. There is an emphasis on producing original work to present at conferences or published in peer-reviewed journals. Students who successfully complete the Ph.D. program go on to take leadership, entrepreneurial, and scholarly positions.

PhD students progress through four phases in their study.  Initially, students are required to begin  coursework  while identifying a faculty mentor to serve as their research advisor.  As students progress in coursework and research, they will be evaluated each semester on their progress towards their  Qualifying Exam  by the completion of a Portfolio (initially evaluated in the 3rd semester and completed by their 5th semester).  Students are required to complete a minor either as a CS internal minor or in another degree program at the UA (see PhD Planning Sheet ).  As research progresses and coursework is completed, students next identify their committee and propose their dissertation work during their  Comprehensive Exam , completed by their 7th semester.  Finally, once students complete their research, they will defend their  Dissertation .

Progress Through the Degree

Students should become familiar with the  Graduate College Policies  and  CSC Graduate Program Policies  and refer to them throughout the program.  Submission of  Ph.D. GradPath Forms  are required throughout the program starting with the first semester.

Students are evaluated for  satisfactory progress  every fall and spring semester. Semesters are counted from when students enter the Ph.D. program. The table below indicates when evaluations take place, along with what benchmarks are used to determine satisfactory progress.

The table below shows what the ideal progression through the Ph.D. program looks like.  View the  Ph.D. Curriculum  for a more in-depth look at the required courses.

Note: The timeline can be shifted earlier; shifting later requires approval of faculty.

*Students may elect to replace one elective course in the major and up to two courses in the internal minor with independent studies (CSC 599/699).

**4th minor course only required if minor requires four courses.

***Students cannot register for 920 until they pass their comp exam.

Software engineering

Program information Admissions Faculty Tuition and fees Career services Request information How and when to apply Attend an event

Program description

Receive an asu-infosys scholarship.

*GRE waiver: GRE score is  Only waived for ASU students with an undergraduate degree(Junior/Senior year) in software engineering and with a 3.75+ GPA. GRE waiver does not apply to PhD applicants.

Application deadlines

Fall:    15th January Spring: 15th September

School of Computing and Augmented Intelligence (formerly CIDSE) Graduate advising office [email protected]

• Program information
• Tuition and fees
• Career services

Computer science (BS)

Become a part of the computing evolution with innovative curriculum and cutting-edge research experiences.

Students working towards the bachelor of science (BS) degree in computer science at the School of Computing and Augmented Intelligence will learn to solve technical problems requiring critical and creative thinking in traditional and innovative computer science applications. The coursework will challenge students to apply design and development principles in the construction of software systems of varying complexity and to communicate effectively with a wide range of audiences.

The computer science program also offers students the chance to focus their degree on either software engineering (SE) or cybersecurity. Concentrations allow students to take core classes within a subject area that will meet the computer science and/or technical elective requirements within one’s degree.

We are pleased to welcome a new online computer science bachelor’s degree offering through ASU Online, coming Fall 2023. Students in the School of Computing and Augmented Intelligence will now be able to access the same curriculum and award-winning computer science faculty in an online format, helping build a foundation for all to be successful.

Degree offered

Computer science (BS) with concentrations in cybersecurity and software engineering

Ira A. Fulton Schools of Engineering

Tempe Online

What is a major map?

A major map outlines a major’s official requirements, elective and required courses, and optimal course sequencing to help students stay on the right track to graduation.

View major map

Admission requirements

All students are required to meet general university admission requirements.

Freshman Transfer International Readmission Ira A. Fulton Schools of Engineering

Affording college

Scholarships Find and apply for relevant scholarships.

Be sure to check out Fulton Schools’ scholarships available to both new and continuing students at scholarships.engineering.asu.edu .

Financial Aid ASU has many financial aid options. Almost everyone, regardless of income, can qualify for some form of financial aid. In fact, more than 70 percent of all ASU students receive some form of financial assistance every year.

Computer Science (BS)

• About the Degree
• Degree Requirements: Ground campus
• Degree requirements: Online campus
• Concentrations
• Computer Science and Engineering Faculty
• Objectives and Outcomes
• Accelerated Master’s Program

Why computer science?

Graduates with a degree in computer science find employment working in a variety of capacities ranging from computer and software design to development of information technologies. Their jobs are often distinguished by the high level of theoretical expertise they apply to solving complex problems and the creation and application of new technologies. Some computer science-related jobs may include:

• creating video games and systems
• designing artificial intelligence systems
• developing network security applications
• inventing and implementing more efficient computing systems for managing and information, including information retrieval and search on the internet

With the theoretical foundation built in the program, computer science graduates can excel in system and software development, as well as in designing effective computing solutions for emerging and challenging problems in modern society. Skills in system development and research can lead to entrepreneurial activity that produces innovative computing products and services. Learn more about the objectives and outcomes of the BS degree in computer science.

Accreditation

The computer science, BS program at Arizona State University is accredited by the Computing Accreditation Commission of ABET, http://www.abet.org . Student enrollment and graduation data are available at engineering.asu.edu/enrollment .