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Computer Science PhD

The Department of Electrical Engineering and Computer Sciences (EECS) offers two graduate programs in Computer Science: the Master of Science (MS), and the Doctor of Philosophy (PhD).

Master of Science (MS)

The Master of Science (MS) emphasizes research preparation and experience and, for most students, is a chance to lay the groundwork for pursuing a PhD.

Doctor of Philosophy (PhD)

The Berkeley PhD in EECS combines coursework and original research with some of the finest EECS faculty in the US, preparing for careers in academia or industry. Our alumni have gone on to hold amazing positions around the world.

Contact Info

[email protected]

215 Cory Hall

Berkeley, CA 94720

At a Glance

Department(s)

Electrical Engineering & Computer Sciences

Admit Term(s)

Application Deadline

December 9, 2024

Degree Type(s)

Doctoral / PhD

Degree Awarded

GRE Requirements

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PhD Admissions

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The Computer Science Department PhD program is a top-ranked research-oriented program, typically completed in 5-6 years. There are very few course requirements and the emphasis is on preparation for a career in Computer Science research. 

Eligibility

To be eligible for admission in a Stanford graduate program, applicants must meet:

• Applicants from institutions outside of the United States must hold the equivalent of a United States Bachelor's degree from a college or University of recognized good standing. See detailed information by region on  Stanford Graduate Admissions website. 
• Area of undergraduate study . While we do not require a specific undergraduate coursework, it is important that applicants have strong quantitative and analytical skills; a Bachelor's degree in Computer Science is not required.

Any questions about the admissions eligibility should be directed to  [email protected] .

Application Checklist

An completed online application must be submitted by the CS Department application deadline and can be found  here .

Application Deadlines

The online application can be found here . You may submit one application for a PhD program per respective academic term.

Computer Science, PhD

Computer science phd degree.

In the Computer Science program, you will learn both the fundamentals of computation and computation’s interaction with the world. Your work will involve a wide range of areas including theoretical computer science, artificial intelligence and machine learning, economics and computer science, privacy and security, data-management systems, intelligent interfaces, operating systems, computer graphics, computational linguistics, robotics, networks, architectures, program languages, and visualization.

You will be involved with researchers in several interdisciplinary initiatives across the University, such as the Center for Research on Computation and Society , the Data Science Initiative , and the Berkman Klein Center for Internet and Society .

Examples of projects current and past students have worked on include leveraging machine learning to solve real-world sequential decision-making problems and using artificial intelligence to help conservation and anti-poaching efforts around the world.

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Computer Science Degree

Harvard School of Engineering offers a  Doctor of Philosophy (Ph.D) degree in Computer Science , conferred through the Harvard Kenneth C. Griffin Graduate School of Arts and Sciences. Prospective students apply through Harvard Griffin GSAS; in the online application, select “Engineering and Applied Sciences” as your program choice and select "PhD Computer Science" in the Area of Study menu.

In addition to the Ph.D. in Computer Science, the Harvard School of Engineering also offers master’s degrees in  Computational Science and Engineering as well as in Data Science which may be of interest to applicants who wish to apply directly to a master’s program.

Computer Science Career Paths

Graduates of the program have gone on to a range of careers in industry in companies like Riot Games as game director and Lead Scientist at Raytheon. Others have positions in academia at University of Pittsburgh, Columbia, and Stony Brook. More generally, common career paths for individuals with a PhD in computer science include: academic researcher/professor, industry leadership roles, industry research scientist, data scientist, entrepreneur/startup founder, product developer, and more.

Admissions & Academic Requirements

Prospective students apply through the Harvard Kenneth C. Griffin Graduate School of Arts and Sciences (Harvard Griffin GSAS). In the online application, select  “Engineering and Applied Sciences” as your program choice and select "PhD Engineering Sciences: Electrical Engineering​." Please review the  admissions requirements and other information  before applying. Our website also provides  admissions guidance ,  program-specific requirements , and a  PhD program academic timeline . In the application for admission, select “Engineering and Applied Sciences” as your degree program choice and your degree and area of interest from the “Area of Study“ drop-down. PhD applicants must complete the Supplemental SEAS Application Form as part of the online application process.

Academic Background

Applicants typically have bachelor’s degrees in the natural sciences, mathematics, computer science, or engineering.

Standardized Tests

GRE General: Not Accepted

Computer Science Faculty & Research Areas

View a list of our computer science faculty  and  computer science affiliated research areas . Please note that faculty members listed as “Affiliates" or "Lecturers" cannot serve as the primary research advisor.

Computer Science Centers & Initiatives

View a list of the research centers & initiatives  at SEAS and the computer science faculty engagement with these entities .

Graduate Student Clubs

Graduate student clubs and organizations bring students together to share topics of mutual interest. These clubs often serve as an important adjunct to course work by sponsoring social events and lectures. Graduate student clubs are supported by the Harvard Kenneth C. Griffin School of Arts and Sciences. Explore the list of active clubs and organizations .

Funding and Scholarship

Learn more about financial support for PhD students.

• How to Apply

Learn more about how to apply  or review frequently asked questions for prospective graduate students.

In Computer Science

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PhD in Computer Science

Ranked among the top 25 graduate programs in the u.s..

Dive into AI, human-centered computing, or another area of computer science that intrigues you. Develop your research, teaching, and leadership skills. And work with the brightest minds in the field to advance computing for the common good with UMass Amherst’s PhD in computer science.

Designed to prepare you for teaching, research and leadership positions, our PhD program ranks among the top 25 in the nation and features world-renowned faculty, interdisciplinary research, and a spirit of collaboration that attracts the brightest students and faculty. You’ll also have the opportunity to conduct groundbreaking research with the industry-leading technology companies we collaborate with.

PhD in computer science course requirements:

• Six core courses in systems, AI and theory (18 credits)
• Portfolio/comprehensive exam
• Dissertation research (18 credits)
• Doctoral thesis proposal and defense

The PhD Student Handbook provides information and answers questions on a range of topics, such as assistantships, dissertation process, forming a committee, and more.

Related offerings

Students interested in our PhD in Computer Science may also be interested in these other offerings.

• MS in Computer Science — on Campus
• MS in Computer Science — Online

Benefits list

Faculty Expertise and Academic Rigor

Our PhD program features advanced coursework taught by award-winning faculty working at the forefront of computing’s fastest-growing fields. Our curriculum prepares you to take on today’s biggest societal challenges across many disciplines — from technology and finance to health care and the arts.

Student Experience

Find your place here with supportive 1:1 advising and community events like  HackHer413 . Build leadership skills and connections by participating in one of over a dozen active student organizations, including the ever-popular  BUILD UMass  and  UMass Robotics .   

Featured classes

This course introduces graduate and undergraduate students to concepts, practices, and tools for conducting effective research. Students will learn basic methods for activities such as reading technical papers and selecting research topics.

Principles underlying the design and analysis of efficient algorithms. Topics to be covered include: divide-and-conquer algorithms, graph algorithms, matroids and greedy algorithms, randomized algorithms, NP-completeness, and approximation algorithms

Intelligent visual computing is an emerging new field that seeks to combine modern trends in machine learning, computer graphics, and computer vision to intelligently process, analyze, and synthesize 2D/3D visual data. 

Featured faculty

Narges mahyar.

Human-computer interaction (HCI), information visualization, digital civics, social computing, crowdsourcing, and design thinking.

Ina Fiterau Brostean

Machine learning, ensembles, multimodal data fusion, hybrid models, health care applications.

Evangelos Kalogerakis

Computer graphics and vision, geometric modeling, 3D deep learning, animation, shape analysis and synthesis, scene modeling, 3D reconstruction.

Marco Serafini

Database systems, distributed systems, data science.

Alexandra Meliou

Data management, data quality, provenance, causality, explanations, data accessibility, and algorithmic bias.

In the spotlight

“Because of the flexibility that CICS offers, I’ve been able to chart my own path. I conduct research on the privacy implications in devices that use machine learning. UMass has such a friendly and collaborative nature with people of all different backgrounds that it really does feel like home."

Application information & deadlines

Fall admission, december 15, 2022.

Application deadline.

Computer Science

With a UMass Amherst computer science degree you’ll have the skills to apply advanced computer science techniques to solving today’s most complex problems.

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PhD Program

In many ways, the PhD program is the cornerstone of Computer Science at Boston University.  Our PhD students serve some of the most central roles of our department, from pursuing sponsored research together with supervising faculty members as Research Assistants, to serving as Teaching Fellows in support of our undergraduate and graduate curriculum.

Pursuing the PhD degree enables you to become an expert in a technical subfield of Computer Science and advance the state of the art by contributing original research in that discipline. Most PhD students also gain practical experience in the classroom, as well as, becoming a visible member of the research community by publishing research and delivering oral presentations at conferences and research seminars.

Upon completing your PhD degree, you will be able to set your own research direction, teach and advise students, and work at the forefront of cutting-edge research in academia or at an industrial laboratory.

Learning Outcomes

• Produce and defend original research in the field of Computer Science.
• Master broad knowledge of Computer Science across algorithms, software, systems, theory of computation, and in one of the areas of artificial intelligence, computer graphics, cryptography & security, and data science .
• Demonstrate in-depth knowledge of a particular subject area within Computer Science.
• Actively participate in the Computer Science research community, for example by attending academic conferences and submitting research results for publication in professional conferences and journals.
• Be able to effectively communicate the results of research.

We invite you to learn more about our program through the links below.

PhD Program Information

• Program Milestones
• Breadth Requirements
• Subject Exams
• Specimen Curriculum

Fellowships & Awards

• Computer Science Fellowship Opportunities
• Research Excellence Award
• Teaching Excellence Award
• Teaching Fellow Expectations

More Information

• PhD in Computer Science – Graduate School of Arts & Sciences (GRS) Bulletin
• Graduate School of the College of Arts and Sciences (GRS) PhD Requirements
• Graduation Calendar
• PhD Profile for Computer Science

Apply Today

To apply to the Ph.D. program, please fill out an online application .

Deadline: December 15 for Fall admission.

With questions about admissions, please contact us at [email protected] .

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PhD Program Admissions

Applying to our PhD Program

We’re thrilled that you are interested in our PhD program in computer science! This page provides an overview of the application process, some guidelines, and answers to specific questions. Please check our FAQ before emailing [email protected] with any questions not answered here.

Our program accepts a large number of applicants each year from a diverse range of backgrounds. Our applicants come directly from undergraduate or master’s programs, as well as industry positions, and from within United States and numerous countries around the world.

Visit the interactive PhD program statistics page   to view historical program data pertaining to admissions, enrollment, retention/attrition/completion, and time to degree conferral. (Select “ Computer Science” from the “Choose Program” drop-down menu.)

Ready to start your PhD application?

We’re ready for you. Click on the link below to start your application to become a PhD student at Johns Hopkins University

The Application: General Advice

The most important question we ask when reviewing applications is "Will this individual excel at research?" Every part of your application is helpful insofar as it answers this question. The three major components of an application are the statement, letters of recommendation, and grades.

This is one of the most important parts of your application; it lets us get to know you and creates a narrative of your academic career and future plans. Before you write your statement, start by thinking about what you want us to learn about you. Make a list of important achievements, perspectives, and goals. Build your statement around this list. We are looking for students who have made the most of the opportunities they have been presented with and who are smart, creative, and motivated. Keep in mind that we also have your CV and letters of recommendation, so we don’t necessarily need a list of all your accomplishments. However, your statement can fill in the narrative around what you did and, more specifically, why you did it. What motivates you? What are your research interests and why? These details aren’t found elsewhere in your application, so focus on them in your statement.

There are a few things we suggest not including in your statement. While it’s tempting to give a rationale for why you are applying to our program, don’t include it if it’s uninformed. Consider: “I want to apply to Johns Hopkins because it’s one of the premiere academic programs.” We know that already! If you do have specific reasons to be interested in our program (e.g. location, a specific project, a faculty member, etc.), be sure to mention them.

In terms of your motivation, be specific! Don’t write: “I’ve wanted to do a PhD in CS since I was six years old.” We don’t trust that six-year-olds make good career decisions. If you write “I have always found AREA X fascinating,” explain why.

Letters of Recommendation

The two most important factors of a recommendation letter are: 1) select someone who knows you well, and 2) select someone who knows how to write a letter.

First, it’s tempting to ask Professor X. to write a letter for you because they are a well-known person in the field. While we can better contextualize letters from people we know, it’s only helpful if the letter contains meaningful information. If Professor X. writes, “I’ve met the applicant a few times and they seem sharp,” that’s not useful information. It’s more important to select someone who knows you well and can discuss your achievements in detail.

Second, your letter writer should know how to write a letter. Academic research programs look for different things than a company. We often read letters from work supervisors that say nice things, but don’t speak to the qualities we find most important.

Of course, it’s a balance. You want someone who knows you well, but they still need to know how to write a good letter of recommendation.

We understand that three letters are a lot, especially for an undergraduate applying directly to a PhD program. We don’t expect each candidate to have three amazing letters. Your choices should be about balance: you want people who know you well, can write good academic letters, and know the research field. Use your choice of your three letter-writers to create this balance.

There isn’t much you can do about your grades—you have the grades you have. However, we do not use any grade cutoffs or thresholds in admissions. We want to see that you did well and excelled in whatever program you were in. Did you push yourself to take upper-level classes? Did you do well in the classes most directly related to your research area? If you have special circumstances that explain some of your grades, please include a description of them in your statement.

The Whiting School of Engineering does not require GRE General Test scores for applications to our PhD programs.

TOEFL or IELTS

Non-native English speakers must take the TOEFL or IELTS exams. Details on accepted exams, scores, and exceptions to this requirement can be found here .

Application Tips

There are many helpful guides for PhD applications. Here are a few we recommend:

• How to be a Successful PhD Student (co-authored by our own Mark Dredze )
• What Readers Look for in a Statement of Purpose
• Student Perspectives on Applying to NLP PhD Programs
• A Survival Guide to a PhD

Application Deadlines

Application Deadline:

The deadline for fall is December 15th. (No recruiting for spring admissions.)

The application will be available for submission on or around August 15.

Vivien Thomas Scholars

The Vivien Thomas Scholars Initiative (VTSI) is an endowed fellowship program at Johns Hopkins for PhD students in STEM fields. It provides full tuition, stipend, and benefits while also providing targeted mentoring, networking, community, and professional development opportunities. Students who have attended a historically black college and university or other minority serving institution for undergraduate study are eligible to apply. To be considered for the VTSI, all application and supplementary materials must be received by December 1, 2021.

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Phd program, find your passion for research.

Duke Computer Science gives incoming students an opportunity to investigate a range of topics, research problems, and research groups before committing to an advisor in the first year. Funding from the department and Duke makes it possible to attend group meetings, seminars, classes and colloquia. Students may work on multiple problems simultaneously while finding the topic that will motivate them through their first project. Sharing this time of learning and investigation with others in the cohort helps create lasting collaborators and friends.

Write a research proposal the first year and finish the research the second under the supervision of the chosen advisor and committee; present the research results to the committee and peers. Many students turn their RIP work into a conference paper and travel to present it.

Course work requirements are written to support the department's research philosophy. Pass up to four of the required six courses in the first two years to give time and space for immersing oneself in the chosen area.

Years three through five continue as the students go deeper and deeper into a research area and their intellectual community broadens to include collaborators from around the world. Starting in year three, the advisor funds the student's work, usually through research grants. The Preliminary exam that year is the opportunity for the student to present their research to date, to share work done by others on the topic, and to get feedback and direction for the Ph.D. from the committee, other faculty, and peers.

Most Ph.D students defend in years five and six. While Duke and the department guarantee funding through the fifth year, advisors and the department work with students to continue support for work that takes longer.

Teaching is a vital part of the Ph.D. experience. Students are required to TA for two semesters, although faculty are ready to work with students who want more involvement. The Graduate School's Certificate in College Teaching offers coursework, peer review, and evaluation of a teaching portfolio for those who want to teach. In addition, the Department awards a Certificates of Distinction in Teaching for graduating PhD students who have demonstrated excellence in and commitment to teaching and mentoring.

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PhD in Computer Science

Immerse yourself in machine learning and AI, human-centered computing, robotics, — or any area of computer science that intrigues you. Develop your research, teaching, and leadership skills. And work with the brightest minds in the field to advance computing for the common good. 

UMass Amherst’s PhD in computer science is designed to prepare you for teaching, research and leadership positions. Our program ranks among the top 25 in the nation.  

Interdisciplinary research, world-renowned scholars, and our collaborative spirit attract top students and faculty. We also partner with industry-leading technology companies to conduct groundbreaking research. As a PhD student at CICS, you'll find the community and resources you need to pursue your passion and use computing to take on the world's toughest challenges

PhD in computer science course requirements: 

• Six core courses in systems, AI and theory (18 credits) 
• Portfolio/comprehensive exam 
• Dissertation research (18 credits) 
• Doctoral thesis proposal and defense 

Related offerings

Students interested in our PhD in Computer Science may also be interested in these other offerings.

• MS in Computer Science — On Campus
• MS in Computer Science — Online

Featured classes

This course introduces graduate and undergraduate students to concepts, practices, and tools for conducting effective research. Students will learn basic methods for activities such as reading technical papers and selecting research topics.

Principles underlying the design and analysis of efficient algorithms. Topics to be covered include: divide-and-conquer algorithms, graph algorithms, matroids and greedy algorithms, randomized algorithms, NP-completeness, and approximation algorithms

Intelligent visual computing is an emerging new field that seeks to combine modern trends in machine learning, computer graphics, and computer vision to intelligently process, analyze, and synthesize 2D/3D visual data. 

In the spotlight

“Because of the flexibility that CICS offers, I’ve been able to chart my own path. I conduct research on the privacy implications in devices that use machine learning. UMass has such a friendly and collaborative nature with people of all different backgrounds that it really does feel like home."

Application information & deadlines

Fall admission, december 15, 2024.

Application deadline

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Computer science.

Computer Science, PhD

The Doctor of Philosophy, the highest degree offered by the University, is conferred in recognition of marked scholarship in a broad field of knowledge as well as distinguished critical or creative achievement within a special area of the general field (the special area being the subject of the doctoral dissertation). The Doctor of Philosophy (PhD) in Computer Science program in the College of Engineering and Applied Science (CEAS) is designed to meet the traditional high standards for such programs. The PhD in Computer Science is administered by the division of Computer Science in the department of Electrical Engineering and Computer Science. Some aspects of the program are delegated to the CEAS Graduate Office.

The program is flexible, allowing the student to develop a plan of studies tailored to meet individual needs. Evaluation of the study plan is based on its appropriateness as a computer science program, the availability within the University of appropriate course offerings, and the availability within the division of Computer Science of a faculty member who is qualified to serve as the student’s major professor.

The PhD degree requires a minimum of 66 credits beyond the baccalaureate, including a dissertation. The student must also satisfy a residence requirement.

Many of the courses leading toward graduate degrees in CEAS are offered in the late afternoon or evening. So, students can complete much of their coursework on a part-time basis.

Admission Requirements

Credits and courses, additional requirements, application deadlines.

Application deadlines vary by program, please review the application deadline chart for specific programs. Other important dates and deadlines can be found by using the One Stop calendars .

An applicant must meet  Graduate School requirements  plus these program requirements to be considered for admission to the program:

• Applicants holding a MS degree in computer science will generally be admitted without deficiencies. Applicants holding a BS degree in computer science may be admitted only if they are exceptionally strong, such as with a record including successful completion of courses normally taken at the graduate level in computer science.
• Applicants holding MS degrees from domains outside of computer science may be admitted with specific program-defined course deficiencies, provided that the deficiencies amount to no more than two courses. The student is expected to satisfy deficiency requirements within three enrolled semesters. The deficiencies are monitored by the Graduate School and the division of Computer Science. No course credits earned in making up deficiencies may be counted as program credits required for the degree. The mathematics preparation must generally include mathematics equivalent to MATH 231 . Otherwise, the made-up deficiencies must be sufficient to assure that the applicant is able to proceed with advanced work directed toward the doctoral degree.
• A minimum grade point average of 3.0 on the basis of 4.0, in the highest degree granted. An applicant with a master’s degree in engineering or computer science having a GPA of less than 3.0, but at least equal to 2.75, may be admitted if substantial evidence can be submitted demonstrating that the applicant has the capacity to perform satisfactory doctoral work.
• All applicants are required to submit a brief (1 or 2 page) statement describing their professional goals and at least two letters of reference.
• The Graduate Record Examination (GRE) is required for all international and domestic applicants.
• International students require proof of English language proficiency. Complete information is available at the  UWM Center for International Education .
• Applicants with a relevant master’s degree who intend to complete an additional master’s in Computer Science at UWM should announce their plans at the time of admission, and not later than the start of their second year into the PhD program.

Reapplication

A student who receives a master’s degree at UWM must formally apply for admission to the Graduate School as a doctoral student before continuing studies that will be credited toward the Doctor of Philosophy in Computer Science.

The minimum degree requirement is 66 graduate credits beyond the bachelor’s degree. The minimum credit  distribution of coursework to be undertaken must be as follows depending on the option selected.

The 6-credit requirement in mathematics and/or quantitative methods may be met by satisfactorily completing certain courses specified by the Department or by taking the minor in mathematics. When such courses also count for either the major or the minor area, the remaining credits may be taken as approved electives.

The student must achieve a 3.0 GPA separately in each of the following areas: the major area, the minor area, and the quantitative methods area.

The minor is normally in another area offered in the College or in the physical sciences or mathematics or in management sciences. Consideration of any other area as a minor requires the prior approval of the Department.

A minimum of 26 credits, excluding doctoral thesis, must be at the 700 level or higher.

Major Professor as Advisor

The Graduate School requires that the student must have a major professor to advise, supervise, and approve the program of study before registering for courses. The incoming student will be assigned to an initial Program Advisor at the time of admission. Prior to the completion of 12 credits (9 credits for part-time students), the student must select a major professor who will be the student’s thesis advisor. The student, in consultation with the major professor, develops a proposed program of studies which is submitted for approval. For subsequent changes, the student must file a revised program of study for approval.

Foreign Language

There is no foreign language requirement for the degree.

The program residence requirement is satisfied either by completing 8 or more graduate credits in two consecutive semesters, exclusive of summer sessions, or by completing 6 or more graduate credits in each of three consecutive semesters, exclusive of summer sessions.

Qualifying Examination

Each student in the program must take and pass a Qualifying Examination to demonstrate that the student is qualified for doctoral-level work. The Qualifying Examination is a written exam and is structured in two parts: Part 1 and Part 2. The examination is offered twice a year during the regular academic year. 

Students entering with only a bachelor’s degree or with a master’s degree in an area unrelated to their major may take the Qualifying Examination for the first time after earning 12 credits of graduate work at UWM and must successfully pass the exam before earning 30 credits of graduate work at UWM.

Students admitted after completing an appropriate master’s degree must take this examination no later than the semester immediately after 18 credits of graduate work have been earned at UWM.

A student may take the Qualifying Examination twice. On the first attempt, the student must attempt both Part 1 and Part 2 of the examination.

• If the student passes both parts, then the student has passed the entire examination and will be permitted to proceed toward the Doctor of Philosophy degree.
• If the student fails both parts, then the student must take the entire exam again at its next offering.
• If a student passes only one of the two parts, then the student must take the examination again at its next offering, but may choose to take only the part of the examination that was not passed on the first attempt.
• If a passing grade is not obtained on the second attempt of the Qualifying Examination, the student will not be permitted to proceed toward the Doctor of Philosophy degree.

A student who fails the qualifying exam twice is subject to dismissal from the PhD in Computer Science program. A student may appeal the failure and dismissal within 30 days of being notified of the failure. If the student does not appeal or the appeal is not granted, the College will recommend to the Graduate School that the student be dismissed. A student who is dismissed from the PhD in Computer Science program because of failing the qualifying exam may not be enrolled in the PhD in Computer Science program for a complete calendar year. This does not preclude the student from being enrolled in any other degree program offered by the University. A student who wishes to re-enroll in the program after a calendar year has passed must apply as any other student would, including payment of fees. A student readmitted after having failed the qualifying exam twice must take the qualifying exam in the first semester of matriculation and this will count as the student’s first attempt at the exam. The student may appeal this requirement prior to the first scheduled day of classes. If the student fails the qualifying exam on this first attempt, the student is permitted the customary second attempt as described above. All appeals must be in writing and directed to the CEAS Associate Dean for Academic Affairs.

Doctoral Program Committee

The Doctoral Program Committee is proposed by the major professor in consultation with the student and the department. The Committee must include at least five graduate faculty (three from major area, one from minor area, and one from any area, including the major and minor areas). The last member may be a person from outside the University (such as another university, a research laboratory, or a relevant industrial partner), provided that person meets Graduate School requirements. The Committee may have more than five members, provided that the majority of the Committee members are from the student’s major field.

Doctoral Preliminary Examination

A student is admitted to candidacy only after successful completion of the doctoral preliminary examination conducted by the Doctoral Program Committee. This examination, which normally is oral, must be taken before the completion of 48 credits of graduate work toward the Doctor of Philosophy degree in Computer Science and should be taken within the first seven years in the program. Prior to the examination, the student must present a proposal for a doctoral dissertation project. The examination may cover both graduate course material and items related to the proposed dissertation project.

Dissertation and Dissertator Status

The student must carry out a creative effort in the major area under the supervision of the major professor and report the results in an acceptable dissertation. The effort of the student and the major professor to produce the dissertation is reflected in the PhD in Computer Science program requirement that the student complete at least 18 credits of doctoral thesis. 

After the student has successfully completed all degree requirements except the dissertation, the student may enter Dissertator Status. Achieving Dissertator Status requires successful completion of the Doctoral Preliminary Examination and prior approval of the student’s advisor, the Doctoral Program Committee, and the Computer Science GPR of a dissertation proposal that outlines the scope of the project, the research method, and the goals to be achieved. Any proposal that may involve a financial commitment by the University also must be approved by the Office of the Dean. After having achieved Dissertator Status, the student must continue to register for 3 credits of doctoral thesis per semester during the academic year until the dissertation is completed.

Dissertation Defense

The final examination, which is oral, consists of a defense of the dissertation project. The doctoral defense examination may only be taken after all coursework and other requirements have been completed. The student must have Dissertator Status at the time of the defense.

All degree requirements must be completed within ten years from the date of initial enrollment in the doctoral program.

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Admission Steps

Computer science - phd, admission requirements.

Terms and Deadlines

Degree and GPA Requirements

Prerequisites

Additional standards for non-native english speakers, additional standards for international applicants.

For the 2025-2026 academic year

See 2024-2025 requirements instead

Fall 2025 quarter (beginning in September)

Priority deadline: February 14, 2025

Final submission deadline: June 16, 2025

International submission deadline: May 5, 2025

Winter 2026 quarter (beginning in January)

Final submission deadline: November 4, 2025

International submission deadline: September 8, 2025

Spring 2026 quarter (beginning in March)

Final submission deadline: February 3, 2026

International submission deadline: December 8, 2025

Summer 2026 quarter (beginning in June)

Final submission deadline: May 4, 2026

International submission deadline: February 23, 2026

Priority deadline: Applications will be considered after the Priority deadline provided space is available.

Final submission deadline: Applicants cannot submit applications after the final submission deadline.

Degrees and GPA Requirements

Bachelors degree: All graduate applicants must hold an earned baccalaureate from a regionally accredited college or university or the recognized equivalent from an international institution.

University GPA requirement: The minimum grade point average for admission consideration for graduate study at the University of Denver must meet one of the following criteria:

A cumulative 2.5 on a 4.0 scale for the baccalaureate degree.

A cumulative 2.5 on a 4.0 scale for the last 60 semester credits or 90 quarter credits (approximately two years of work) for the baccalaureate degree.

An earned master’s degree or higher from a regionally accredited institution or the recognized equivalent from an international institution supersedes the minimum GPA requirement for the baccalaureate.

A cumulative GPA of 3.0 on a 4.0 scale for all graduate coursework completed for applicants who have not earned a master’s degree or higher.

Prerequisite courses for the PhD include: COMP 1671 Introduction to Computer Science I, COMP 1672 Introduction to Computer Science II, COMP 2673 Introduction to Computer Science III, COMP 2300 Discrete Structures in Computer Science, COMP 2370 Introduction to Algorithms & Data Structures, and COMP 2691 Introduction to Computer Organization (or equivalent).

Official scores from the Test of English as a Foreign Language (TOEFL), International English Language Testing System (IELTS), C1 Advanced or Duolingo English Test are required of all graduate applicants, regardless of citizenship status, whose native language is not English or who have been educated in countries where English is not the native language. Your TOEFL/IELTS/C1 Advanced/Duolingo English Test scores are valid for two years from the test date.

The minimum TOEFL/IELTS/C1 Advanced/Duolingo English Test score requirements for this degree program are:

Minimum TOEFL Score (Internet-based test): 80

Minimum IELTS Score: 6.5

Minimum C1 Advanced Score: 176

Minimum Duolingo English Test Score: 115

Additional Information:

Read the English Language Proficiency policy for more details.

Read the Required Tests for GTA Eligibility policy for more details.

Per Student & Exchange Visitor Program (SEVP) regulation, international applicants must meet all standards for admission before an I-20 or DS-2019 is issued, [per U.S. Federal Register: 8 CFR § 214.3(k)] or is academically eligible for admission and is admitted [per 22 C.F.R. §62]. Read the Additional Standards For International Applicants policy for more details.

Application Materials

Transcripts, letters of recommendation.

Required Essays and Statements

We require a scanned copy of your transcripts from every college or university you have attended. Scanned copies must be clearly legible and sized to print on standard 8½-by-11-inch paper. Transcripts that do not show degrees awarded must also be accompanied by a scanned copy of the diploma or degree certificate. If your academic transcripts were issued in a language other than English, both the original documents and certified English translations are required.

Transcripts and proof of degree documents for postsecondary degrees earned from institutions outside of the United States will be released to a third-party international credential evaluator to assess U.S. education system equivalencies. Beginning July 2023, a non-refundable fee for this service will be required before the application is processed.

Upon admission to the University of Denver, official transcripts will be required from each institution attended.

Three (3) letters of recommendation are required.  Letters should be submitted by recommenders through the online application.

Essays and Statements

Personal statement instructions.

A personal statement of at least 300 words is required. Your statement should include information concerning your life, education, experiences, interests and reason for applying to DU.

Résumé Instructions

The résumé (or C.V.) should include work experience, research, and/or volunteer work.

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Financial Aid Information

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Your submitted materials will be reviewed once all materials and application fees have been received.

Our program can only consider your application for admission if our Office of Graduate Education has received all your online materials and supplemental materials by our application deadline.

Application Fee: $65.00 Application Fee

International Degree Evaluation Fee: $50.00 Evaluation Fee for degrees (bachelor's or higher) earned from institutions outside the United States.

Applicants should complete their Free Application for Federal Student Aid (FAFSA) by February 15. Visit the Office of Financial Aid for additional information.

Professor Ihab Ilyas named Fellow of the Royal Society of Canada

Professor Ihab Ilyas of the Cheriton School of Computer Science has been named a 2024 Fellow of the Royal Society of Canada , the highest national recognition for researchers in the arts, humanities, social sciences, and sciences. He is among 104 distinguished individuals across Canada recognized this year for their exceptional scholarly, artistic, and scientific achievements.

“Congratulations to Ihab on becoming a Fellow of the Royal Society of Canada,” said Raouf Boutaba, University Professor and Director of the Cheriton School of Computer Science. “Over his career, he has made significant contributions in ranking, in machine learning for large-scale data linkage, and in generative AI systems for automatic data cleaning, as well as co-founding two successful start-up companies.”

Professor Ilyas’s many awards and recognitions include receiving the C.C. Gotlieb Computer Award in 2024, being named a Fellow of the Institute of Electrical and Electronics Engineers in 2021, a Fellow of the Association for Computing Machinery in 2020, and a Faculty Affiliate at the Vector Institute in 2020. Since 2018, he has held the Thomson Reuters–NSERC Industrial Research Chair in Data Cleaning , and from 2013 to 2016 held a Cheriton Faculty Fellowship . He has been awarded a Government of Ontario Early Researcher Award, an NSERC Discovery Accelerator Award, and a Google Faculty Research Award. Professor Ilyas co-founded two companies based on his research — Inductiv , a Waterloo-based start-up, now part of Apple, which uses AI for structured data cleaning, and Tamr , which specializes in large-scale data integration and cleaning. He has also served in prominent roles within the academic community, including on the Board of Trustees of the Very Large Data Bases Endowment in 2016 and as Vice Chair of the ACM Special Interest Group on Data Management in 2017. He is currently a Distinguished Engineer, Proactive Intelligence, at Apple Inc., on leave from the University of Waterloo.

Professor Ilyas’s research and contributions

Professor Ihab Ilyas has made outstanding contributions to data management, in particular on data integration, data cleaning, and rank-aware query processing. His research has made a significant impact on both academia and industry, leading to practical applications that address real-world challenges.

His key contributions include the following —

• Rank-aware query processing : Professor Ilyas pioneered the field of rank-aware query processing for accelerated retrieval of important information from large database systems.
• Handling uncertain and probabilistic data : He demonstrated how to deal with large uncertain and probabilistic data encountered in real-world applications.
• Automatic data cleaning using generative AI : He pioneered the field of automatic data cleaning using generative AI models at scale as an open-source platform and as a commercial product.
• Scalable data integration systems : He built data integration systems that scale to hundreds of thousands of heterogenous data sources, serving large enterprises.
• State-of-the-art knowledge graphs : Professor Ilyas designed and built a state-of-the-art knowledge graph platform that serves hundreds of millions of users in production.

In his early work, Professor Ilyas made fundamental contributions to developing efficient techniques for evaluating rank-aware queries over large databases. Rank-aware querying is important in modern applications involving multi-objective optimization. Some examples include finding the top 10 products that satisfy user preferences or showing the most relevant videos or images similar to an example image. Retrieving the most relevant information to users from traditional database systems is an expensive and a complex process. Professor Ilyas pioneered the integration of rank-aware querying into database technologies to enable effective and efficient retrieval from large data sets. He developed algorithms and techniques that substantially improved how database systems handle ranking and user-preferences in processing queries.

His Rank-Join algorithm is the state-of-the-art approach to produce query answers ranked on user preference. He has introduced RankSQL, the first end-to-end rank-aware query engine based on novel ranked relational algebra semantics. He extended this work to ranking over uncertain data and provided the first meaningful semantics for the interplay between uncertainty and score-based ranking. He has also addressed uncertainty in the ranking function itself. His publications defined a new line of research and have provided great insight and several practical semantics of how to produce the most probable top-k records with respect to user preferences. His related work on high-dimensional spatial indexing has been implemented in PostgresSQL, the world’s most advanced and used open-source relational database engine.

Professor Ilyas is a world leader on data quality, focusing on scalable automatic error detection, cleaning and imputation of dirty structured data. Dirty, incomplete, and inconsistent datasets are common in big data and data science and are major impediments to progress in data analytics in which insights are drawn from data. The problem has been identified as the main hurdle for data science and costs the world’s economy billions of dollars annually.

Professor Ilyas pioneered the area of data cleaning by automatically discovering complex integrity constraints from raw data sets and incorporating this domain knowledge into state-of-the-art machine learning and generative AI models. He addressed multiple technical challenges, among them lack of training data, translating traditional integrity constraints into model features, bridging the gap between logical and probabilistic data cleaning, and handling the sparsity and scale challenges in running machine learning on big relational data. The work presents data errors as a noisy channel with a probabilistic model to generate original clean data, and a probabilistic realization model that pollutes that data. Several key results on mining the constraints and on the learnability of these machine learning models parameters using only the observed dirty data helped create pragmatic and scalable solutions. Key insights also include how violations of business rules and integrity constraints can be incorporated into these machine learning models, which allowed decades of logical cleaning research to be incorporated in modern and scalable techniques. In a series of papers, Professor Ilyas, his team and collaborators developed highly novel solutions, demonstrating their efficacy and applicability in building usable systems adopted by large enterprises.

This work produced a rich open-source prototype system called HoloClean and led to Inductiv, a start-up that was acquired by Apple. Inductiv’s technology has been incorporated into multiple data processing pipelines at Apple that power key analytics and user experience enhancing tools. In addition to their industry impact, the top four publications on HoloClean have significantly catalyzed scientific follow-on work.

Professor Ilyas has also made important contributions in large-scale data integration. Information about the same real-world entity — for example, a product, a major event, or a song — come from a variety of heterogenous sources in both structured and unstructured forms. These sources might present contradictory aspects and be in different formats and schemas. Matching these large number of sources to a common representation and resolving and repairing conflicting information are at the heart of the data integration challenge. Professor Ilyas’s fundamental contributions in data integration were commercialized in Tamr, another start-up that has been used by Fortune 500 companies.

Professor Ilyas recently led a major data integration effort at Apple, building the state-of-the-art knowledge graph platform known as Saga. His work integrated data from a variety of external and internal sources to build the source of truth for all world major entities. The integrated knowledge platform runs in production powering products and user experience enhancing tools used by hundreds of millions of users.

Fellows of the Royal Society of Canada at the Cheriton School of Computer Science

Professor Ilyas is the tenth faculty member at the Cheriton School of Computer Science to be named a Fellow of the Royal Society of Canada. Previous recipients of Royal Society of Canada Fellowships are N. Asokan, Raouf Boutaba, Richard Cleve, J. Alan George, Srinivasan Keshav, Ming Li, J. Ian Munro, M. Tamer Özsu, and Douglas Stinson.

Royal Society of Canada

Founded in 1882, the RSC comprises the Academy of Arts and Humanities, Academy of Social Sciences, Academy of Science and the RSC College. The RSC recognizes excellence, advises the government and society, and promotes a culture of knowledge and innovation within Canada and with other academies around the world.

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