cmu computer science phd application

Carnegie Mellon University School of Computer Science

Software Engineering Ph.D. Program

Software and societal systems department, build it better....

Software is becoming ever more important to our daily lives, as well as every sector of industry.  But as software systems increase in capability, they increase in complexity, resulting in delays, defects, and vulnerabilities.

Our Ph.D. program in Software Engineering seeks to educate the next generation of high-impact software engineering research, development, and educational leaders who will solve the problems associated with building large-scale and critical software systems.  Learn about our groundbreaking research , our world-leading faculty , and our alumni who are already making a big difference in the world.  We hope you will apply  to our Ph.D. program  so you can join us in learning to build software better!

Don't Forget!

Applications to the Ph.D. program in Software Engineering are accepted every year with a deadline in  December. This year the application window is open  September 6th, 2023 - December 13th, 2023.

Learn how to apply

• Why Software Engineering?
• What are your research strengths?
• What will my course of study look like?
• What are the prerequisites for admission?
• How is this program going to help my career?
• How do I apply?

Video Highlights

Our faculty are taking on some of the most exciting technical challenges modern software faces. Learn more about their work in these short research vignettes!

Program Highlight Videos

Featured Student

Featured Research

Featured Alumna

Language Technologies Institute

School of computer science.

Carnegie Mellon's School of Computer Science has a centralized online application process. The application period for the fall 2024 cycle is now closed. You can find more information on the School of Computer Science's master's admissions and doctoral admissions pages.

• SCS Graduate Admissions

Program Application Details

Ph.d. in language and information technology, dual-degree ph.d. in language and information technologies (portugal partnership), master of language technologies, master of science in intelligent information systems (miis), master of computational data science (mcds), master of science in artificial intelligence and innovation (msaii), undergraduate concentration in language technologies, lti phd/mlt graduate application support program.

This application support program aims to ensure that applicants to research graduate programs at LTI have someone to provide feedback on their application before submission. Historically, people from underrepresented backgrounds have lacked access to guidance from people familiar with the higher degree application process. In order to take steps towards an equitable application process, we invite applicants to the MLT and PhD programs to visit this page for application support through the School of Computer Science. LTI also holds informal information and Q&A sessions for MLT and PhD applicants. Current faculty and students will be present to answer any questions about the upcoming applications. Information about these sessions will be available when the application period is open.

Application Support

Machine Learning Department | CMU | Carnegie Mellon University

Welcoming our new faculty members.

The Machine Learning Department at Carnegie Mellon University welcomes five new faculty members to their core faculty, including Rayid Ghani, Yuanzhi Li, Andrej Risteski, Virginia Smith and Tianqi Chen.

Read article

Virtual Graduate Student Orientation

August 28, 2020.

We hope you can visit us for our Machine Learning Open House, which begins on March 18, 2020, with a 7:30 PM welcome reception.

We have moved our graduate student orientation to virtual attendance only. Please do not hesitate to contact us with any questions and concerns regarding our graduate student orientation session.

Faculty Openings

We started accepting applications on August 1, 2020

ML@CMU Has Launched

Bringing you the latest research in machine learning and related at Carnegie Mellon University.

Machine Learning Recent News

Machine Learning Open House For Accepted Ph.D. Students March 18 and 19, 2021

We hope you can visit us for our Machine Learning Open House, which begins on March 18, 2021, with a 7:30 PM welcome reception.

We have moved our open house to virtual attendance only. Please do not hesitate to contact us with any questions and concerns regarding our Ph.D. Open House.

Globally Known in AI & ML

In machine learning & ai u.s. news & world report 2018, world renowned faculty, for phd & master programs, what is machine learning, a message from manuela veloso - herbert a. simon university professor.

Machine Learning (ML) is a fascinating field of Artificial Intelligence (AI) research and practice where  we investigate how  computer agents can improve their perception, cognition, and action  with experience. Machine Learning is about machines improving from  data, knowledge, experience, and interaction. Machine Learning  utilizes a variety of techniques to intelligently handle large and complex amounts of  information build upon foundations  in many disciplines, including  statistics, knowledge representation, planning and control, databases, causal inference, computer systems, machine vision, and natural  language processing. AI agents with their core at Machine Learning aim at interacting with humans in a  variety of ways, including providing estimates on phenomena, making  recommendations for decisions, and being instructed and corrected. In our Machine Learning Department, we study and research the  theoretical foundations of the field of Machine Learning, as well as  on the contributions to the general intelligence of the field of  Artificial Intelligence. In addition to their theoretical education, all of our students, advised by faculty, get hands-on experience with  complex real datasets. Machine Learning can impact many applications relying on all sorts of  data, basically any data that is recorded in computers, such as health  data, scientific data, financial data, location data, weather data, energy data, etc.

As our society increasingly relies on digital data, Machine Learning is crucial for most of our current and future  applications.

Apply to a Machine Learning Program

• PhD in Machine Learning
• Joint PhD Program in Statistics & Machine Learning
• Joint PhD Program in Machine Learning & Public Policy
• Joint PhD Program in Neural Computation & Machine Learning
• Primary Master's in Machine Learning
• 5th-Year Master's in Machine Learning
• Secondary Master's in Machine Learning

Undergraduate

• Bachelor's of Science in Artificial Intelligence
• Machine Learning Minor
• Statistics & Machine Learning Major

Carnegie Mellon University School of Computer Science

Master's programs.

SCS offers a wide range of professional and academic master's programs across its seven departments. Admissions and requirements vary by program and are determined by the program's home department.

Links to all departments and master's programs appear below. Additionally, our Master's Programs Comparison Data includes statistics, facts and other information for each program.

If you're interested in applying, be sure to visit our Graduate Admissions Overview page or read our Frequently Asked Questions .

All Master's Programs by Department

Ray and stephanie lane computational biology department, master of science in automated science: biological experimentation.

The M.S. in Automated Science program is the first of its kind and provides training for students to play roles in the development of highly automated systems for doing science. It provides training in the principles and hands-on use of robotic laboratory equipment, the fundamental computational biological methods for constructing predictive models in biology and medicine, and the methods of active machine learning and AI for automatically and iteratively choosing experiments to achieve a given goal. The program is designed for a diverse applicant pool and will be especially valuable to students with undergraduate degrees in biology seeking to gain advanced computational skills for jobs in the laboratory automation industry. Opportunities also exist for successful graduates to transition to Ph.D. programs.

Master of Science in Computational Biology

The M.S. in Computational Biology program seeks to train the world's best computational biologists at the master's level. The curriculum provides both breadth and depth of training in computational biology, and is built on a solid foundation of biology, computer science, statistics and machine learning (data sciences). The program is designed for students with backgrounds in quantitative and/or life sciences. Students often participate in summer research internships in life sciences, industry or academic research laboratories. MSCB graduates are prepared for rewarding jobs in industry or to pursue their doctoral degrees at top universities.

Computer Science Department

Fifth year master's in computer science.

The Fifth Year Master's in Computer Science is a direct master's program for students receiving a bachelor of computer science from Carnegie Mellon. The purpose and goal of the program is to encourage our very brightest undergraduates to become involved with research that broadens their often hectic undergraduate experience.

Master of Science in Computer Science

The Master of Science in Computer Science (MSCS) program offers students with a bachelor's degree the opportunity to extend their training with advanced study in computer science. Applicants should possess basic analytic skills and a strong aptitude for mathematics, programming and logical reasoning. A bachelor's degree in computer science is not required, but some scientific, engineering or mathematical background is an important predictor of success.

Human-Computer Interaction Institute

Accelerated master of human-computer interaction.

The Accelerated Master of Human-Computer Interaction program provides CMU undergraduate HCI majors with an opportunity to complete a master's in human-computer interaction in an additional two semesters following graduation. Accepted students join the MHCI capstone in the spring semester of their senior year, graduate in May with their undergraduate degree, and then go right into being a graduate student in the summer while completing their capstone project with MHCI. The fall semester allows them to complete their electives for the master's portion of the program. Students should apply by Nov. 1 of their senior year.

Master of Educational Technology and Applied Learning Science (METALS)

This interdisciplinary program trains students to design, develop and evaluate evidenced-based programs for learning in traditional and nontraditional settings. Graduates will be prepared to take key positions in corporations, universities and schools as designers, developers and evaluators of educational technologies, as well as learning engineers, curriculum developers, learning technology policy-makers and even chief learning officers.

Master of Human-Computer Interaction

The Master of Human-Computer Interaction (MHCI) program is the first in the world dedicated to preparing professionals for careers related to human-computer interaction, user-experience design and user-centered research. The MHCI program integrates service and design thinking into a rigorous HCI curriculum that prepares our students to design and guide the future of human and technology interactions.

Master of Science in Product Management

This 12-month master's program, a joint effort with the university's Tepper School of Business, provides both the technical skills and business acumen students need to be successful in this high-demand area. A required internship and capstone project supply the practical skills students need to return to industry prepared for their new careers.

Language Technologies Institute

Master of computational data science.

The Master of Computational Data Science (MCDS) concentrates on applying the scientific method to very large data systems. The degree focuses on scientific experimental design, data collection, data modeling and analysis, problem solving, and human-computer interaction. These problem areas are addressed through a core computer science curriculum consisting of software engineering, machine learning, statistics, large scale distributed systems, storage systems, etc. The degree trains technologists to create new large scale data science systems.

Master of Science in Artificial Intelligence and Innovation

The Master of Science in Artificial Intelligence and Innovation (MSAII) equips you to identify potential artificial intelligence applications, and develop and deploy AI solutions to large practical problems. Students work in teams to implement AI systems that are responsive to market needs.

Master of Science in Intelligent Information Systems

The Master of Science in Intelligent Information Systems (MIIS) degree focuses on recognizing and extracting meaning from text, spoken language, video, and other forms of unstructured information. It provides deep exposure to content analysis and machine learning.

Master of Science in Language Technologies

The Master of Science in Language Technologies is a research-oriented degree in the areas of speech processing, language processing, information retrieval, machine translation and machine learning. Most MLT students are affiliated with an advisor's research project, in which they gain hands-on experience with advanced research and state-of-the-art software. An optional master's thesis project may also be chosen.

Online Graduate Certificate in Machine Learning and Data Science Foundations

Organizations know how important data is, but they don’t always know what to do with the volume of data they have collected. That’s why CMU designed the online Graduate Certificate in Machine Learning and Data Science Foundations — to teach technically savvy professionals how to leverage AI and machine learning technology to harness the power of large scale data systems. This 12-month, 100% online program will prepare participants for the staggering amount of data generated by today’s rapidly changing world. 

Machine Learning Department

Fifth year master's in machine learning.

The Fifth Year Master's in Machine Learning allows Carnegie Mellon undergraduates to earn an MS degree in one additional year by taking some of the required ML courses as an undergraduate.

Master of Science in Machine Learning

The world's first and top-ranked machine learning program gives students the tools they need to solve real-world problems by using advanced machine learning techniques and developing their own learning algorithms. This program includes three semesters of courses, plus an internship in industry or research with our world-class, interdisciplinary faculty. It strengthens students' skills in computer science and statistics to provide exceptional training for future leaders in the field.

Robotics Institute

Master of science in computer vision.

Computer vision is the study of acquiring and interpreting visual imagery. As the technology matures, its applications in industry continue to expand exponentially in areas of great commercial value. The goals of the 16-month (three semesters plus summer) MSCV program are to provide a robust set of courses encompassing current and emerging state-of-the-art computer vision topics that prepare students for careers in this field, and to facilitate hands-on experience through real research and development projects addressing current applications.

Master of Science in Robotics

The robotics master of science program brings together areas of robotics research that would otherwise be spread across different departments or separate universities, preparing students to take a leading role in the research and development of future generations of integrated robotics technologies and systems.

Master's in Robotic Systems Development

The Master's in Robotic Systems Development (MRSD) is an advanced graduate degree with a combined technical/business focus for recent graduates/practicing professionals already engaged in, or wishing to enter, the robotics and automation field as practitioners in the commercial sector.

Software and Societal Systems

Master of science in information technology - privacy engineering.

The Master of Science in Information Technology - Privacy Engineering (MSIT-PE) is a 12- or 16-month program designed for computer scientists and engineers who wish to pursue careers as privacy engineers or technical privacy managers. Designed in close collaboration with industry and government, this program is intended for students who aspire to play a critical role in building privacy into future products, services and processes.

Master of Software Engineering

This program is designed for software professionals with at least two years of experience who want to learn best practices in managing large, diverse software development projects with a focus on software architecture and software project management. The MSE program emphasizes increased industry engagement in small groups with greater elective flexibility.

Master of Software Engineering - Embedded Systems

For entry-level software developers with less than two years of experience, the MSE-ES program focuses on software design for internet of things (IoT) and cyber-physical systems using microcontrollers with real-time actuators and sensors. The program includes a required summer internship and team project with professional mentors.

Master of Software Engineering - Scalable Systems

Designed for entry-level software developers with less than two years of experience, the MSE-SS program focuses on achieving business objectives through high-velocity, continuous integration for large-scale, data-intensive and intelligent systems. The program includes a required summer internship and team project with professional mentors.

Master of Software Engineering Online

This program is for software professionals with at least two years of experience who want to learn best practices in managing large, diverse software development projects with a focus on software architecture and software project management. The MSE Online program is part-time and culminates in a reflective practice thesis.

Our Master's Programs Comparison Data includes statistics, facts and other information for each program.

View our Master's Programs Comparison Data Sheet

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• M.S. in Computer Science

The M.S. in Computer Science offers students with a bachelor's degree the opportunity to improve their training with advanced study in computer science. 

We cater to students with basic analytic skills and a strong aptitude for mathematics, programming, and logical reasoning.  You don’t need a bachelor’s degree in computer science specifically for the program, but a technical undergraduate background will set you up for success.

Our program isn’t based on a fixed set of courses. Instead, you’ll construct your own course of study, in consultation with your advisor. The program requires only coursework; research is optional, though approximately a third of our students have some research involvement during the course of their studies, and there is a thesis option.

How long does the program take to complete?

Most students will complete the program in three semesters, but if you’re switching to computer science from another field, you may need an additional semester to fill gaps in your undergraduate training. The M.S. program is distinct from the Ph.D. program in computer science, and master's students will not usually continue into the Ph.D. program and will not receive preferential treatment if they apply.

Program Requirements

You must complete six broad requirements:

Pass* 96-108 units in qualifying master’s courses from the curriculum list in the MSCS Handbook . This is typically eight courses.

Pass up to 12 MSCS elective units.

Pass one course from the available Systems courses. (counts toward Qualifying unit)

Pass one course from the available Theoretical Foundations courses. (counts toward Qualifying unit)

Pass one course from the available Artificial Intelligence courses. (counts toward Qualifying unit)

Maintain a 3.0 QPA.

(* "Passing” is considered receiving a letter grade of C or higher.)

Some students may need to take additional courses that do not satisfy any program requirement, in order to satisfy pre-requisites for other courses. For example, most students will be expected to take 15-213/513 (Introduction to Computer Systems).

15-213/513 can be taken over the Internet during the summer, and new master’s students are encouraged to do so before they arrive. Students who completed their undergraduate work at CMU can apply up to two courses taken as an undergraduate toward requirements for the M.S., provided the two courses were not previously used to satisfy any requirement.

You can see a detailed description of the program's requirements and curriculum in our  MSCS Handbook .

How to Apply

For questions specific to the Master of Science in Computer Science (MSCS) please email: [email protected]

• Bachelor's Programs
• Fifth Year Master's
• Accelerated MBA Program
• Master's - How to Apply
• Master's Programs Contacts
• Other SCS Master's Programs
• Doctoral Programs
• Student Resources

Ph.D. Program Admissions

Application information.

The application window for a Fall 2024 start is now closed. The application reopens in Fall 2024 with information for a 2025 start. 

Graduate programs within the Carnegie Mellon University School of Computer Science (SCS) utilize a common online application form. The SCS online application should be completed and submitted electronically as instructed by the deadline.

To apply for admission, read our application instructions carefully and make certain that you have met all requirements when you submit your online application.

Application Process

The HCII strives toward fairness and equity in its admissions process. To this end, we review all applications with a sensitive awareness to the applicant’s personal experiences, background, and potential to add to the rich and dynamic culture of the department. We recognize the value of individual circumstances and consider the unique educational contexts and life experiences of all students. In reviewing materials, we consider diverse forms of evidence that applicants are likely to be successful at research based on their preparatory experiences, as described in the applicant’s statement of purpose, CV, and letters of recommendation from research mentors. This evidence might come in the form of publications or research presentations to which the applicant contributed, portfolios of work, open-source contributions, installations, etc.

It is your responsibility to make certain that your application is complete by the stated deadlines. Unfortunately, given the tight deadlines of our process, we cannot accept late applications and do not consider applicants outside of the stated application period.

Application Requirements

Statement of purpose.

Prepare a Statement of Purpose providing a concise one- or two-page statement. While the format and content is ultimately up to you, consider including information relevant to the following:

• Your primary interests within HCI. Discuss your research interests, and any relevant experiences you have had that have informed and inspired those interests. Student interests tend to evolve as they are immersed in the environment of the HCII. The description provided here is not intended as a definitive statement of what you will do in your Ph.D., but is rather used to direct your application to most likely advisors and also to assess your ability to describe and motivate your research interests. You might consider including a discussion of the potential societal impact of the work (both positive and negative), as such considerations are core to how we think about our work and research at the HCII. You might find it useful to relate your work to existing research areas and projects in the HCI Institute, which are listed on the HCII research summary page. That said, the HCII is a large and dynamic place, and we know that they do not represent the entirity of work or interests of the many people in the department. Anyone with research interests related to HCI (broadly defined) are explicitly welcome.
• State your personal and/or professional objectives in pursuing a Ph.D., and why you are applying to Carnegie Mellon, and the HCII, specifically.
• Describe your background in fields related to your objective. List here any relevant industrial or commercial experience. Please note that we welcome students from diverse educational, cultural, and geographic backgrounds with a variety of strengths — strong technical skills, strong social science skills, strong design skills, and combinations of the above.
• The HCII values students who exhibit persistence and resilience in the face of challenge and adversity, demonstrate a commitment to ethics, and show concern for others and for their community. Describe how your background and your experiences attest to these personal attributes.  

CV / Resume

Attach your current CV (resume), including a summary of research experience and a list of publications, presentations, and conferences/meetings attended.

Publications

Attach copies of up to three (3) publications (preferably in English) that you may have. Please note that having prior publications is not a prerequisite for application.

If appropriate to your background, you may include a link to your portfolio or other online representation of your (e.g., GitHub profile page).

Transcripts

Submit transcripts from all undergraduate and graduate institutions attended, even if no degree was granted. You must upload your transcript in either PDF, JPG, or PNG format. Any other format will not be accepted.

Letters of Recommendation

Submit three letters of recommendation online. Recommenders should know you relatively well and be able to evaluate the quality of previous work. At least two should be from faculty or recent employers.  Recommenders should include information about how long and in what capacity they have known you, give specific and concrete examples of your work, and provide an assessment of relevant traits or accomplishments, such as your persistence and resilience in the face of a challenge, intellectual independence and originality, and commitment to ethics and social impact in your work. Letters are submitted electronically, using the online application. Letters are due at the time of the final deadline.

TOEFL, if required

Take the Test of English as a Foreign Language (TOEFL) and upload your scores directly to your online application. If you are not able to take the TOEFL exam, you may substitute the IELTS or Duolingo English proficiency test. It is a university requirement that all students whose native language is not English take one of these exams. This is true even if the student has an undergraduate or masters degree from an English-speaking college.

Application Fee

Application to the HCII Ph.D. program is usually accompanied by a non-refundable application fee. Many applicants will qualify for a waiver based on either membership in one of many predefined organizations or because of financial need. If you qualify, we invite you to please ask for an SCS Graduate Application Fee Waiver . (The application fee waiver is handled separately from admissions decisions.)

Tuition and Financial Aid

It is anticipated that students accepted into the HCII Ph.D. program will be awarded a graduate fellowship for the academic year covering full tuition and a living allowance. These fellowships renew for the duration of the program as long as the student maintains good standing. There is no separate financial aid form to be completed. Students are encouraged to apply for support from outside Carnegie Mellon (fellowships, foreign government grants, etc.). As an incentive to seek funding from other sources, a supplement is often provided to the stipend of any student who obtains outside support.

Final Checklist

Remember that all items must be uploaded directly to your online application. Have you included the following?

• Application Fee (or a waiver)
• Publications (up to 3)
• Portfolio (optional)
• Transcripts from all schools attended
• TOEFL scores, if required

About Carnegie Mellon

Carnegie Mellon University does not discriminate. Carnegie Mellon University is required not to discriminate in admission, employment, or administration of its programs or activities on the basis of race, color, national origin, sex or handicap in violation of Title VI of the Civil Rights Act of 1964, Title IX of the Educational Amendments of 1972 and Section 504 of the Rehabilitation Act of 1973 or other federal, state, or local laws or executive orders.

In addition, Carnegie Mellon University does not discriminate in admission, employment, or administration of its programs on the basis of religion, creed, ancestry, belief, age, veteran status, sexual orientation or gender identity. Carnegie Mellon does not discriminate in violation of federal, state, or local laws or executive orders.

Inquiries concerning application of these statements should be directed to the Provost, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, telephone 412-268-6684 or the Vice President for Campus Affairs, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, telephone 412-268-2056. Carnegie Mellon University publishes an annual campus security report describing the university’s security, alcohol and drug, and sexual assault policies and containing statistics about the number and type of crimes committed on the campus during the preceding three years. You can obtain a copy by contacting the Carnegie Mellon Police Department at 412-268-2323. The security report is also available online.

Obtain general information about Carnegie Mellon University by calling 412-268-2000. For consumer information about Carnegie Mellon, visit the HUB.

Ph.D. Program

Current Students

Emphasis Areas

Frequently Asked Questions

Program Requirements

Resources for Current Students

Outgoing Students & Postdocs

Ph.D. in Human-Computer Interaction Carnegie Mellon University 5000 Forbes Avenue Pittsburgh, PA 15213-3891

Leah Buffington Ph.D. Program Coordinator Phone: 412-268-5037 Email us

Machine Learning & Data Science Foundations

Online Graduate Certificate

Be a Game Changer

Harness the power of big data with skills in machine learning and data science, your pathway to the ai workforce.

Organizations know how important data is, but they don’t always know what to do with the volume of data they have collected. That’s why Carnegie Mellon University designed the online Graduate Certificate in Machine Learning & Data Science Foundations; to teach technically-savvy professionals how to leverage AI and machine learning technology for harnessing the power of large scale data systems.   

Computer-Science Based Data Analytics

When you enroll in this program, you will learn foundational skills in computer programming, machine learning, and data science that will allow you to leverage data science in various industries including business, education, environment, defense, policy and health care. This unique combination of expertise will give you the ability to turn raw data into usable information that you can apply within your organization.  

Throughout the coursework, you will:

• Practice mathematical and computational concepts used in machine learning, including probability, linear algebra, multivariate differential calculus, algorithm analysis, and dynamic programming.
• Learn how to approach and solve large-scale data science problems.
• Acquire foundational skills in solution design, analytic algorithms, interactive analysis, and visualization techniques for data analysis.

An online Graduate Certificate in Machine Learning & Data Science from Carnegie Mellon will expand your possibilities and prepare you for the staggering amount of data generated by today’s rapidly changing world. 

A Powerful Certificate. Conveniently Offered. 

The online Graduate Certificate in Machine Learning & Data Science Foundations is offered 100% online to help computer science professionals conveniently fit the program into their busy day-to-day lives. In addition to a flexible, convenient format, you will experience the same rigorous coursework for which Carnegie Mellon University’s graduate programs are known. 

For Today’s Problem Solvers

This leading certificate program is best suited for:

• Industry Professionals looking to deliver value to companies by acquiring in-demand data science, AI, and machine learning skills. After completing the program, participants will acquire the technical know-how to build machine learning models as well as the ability to analyze trends.
• Recent computer science degree graduates seeking to expand their skill set and become even more marketable in a growing field. Over the past few years, data sets have grown tremendously. Today’s top companies need data science professionals who can leverage machine learning technology.   

At a Glance

Start Date May 2024

Application Deadlines Rolling Admissions

We are still accepting applications for a limited number of remaining spots to start in Summer 2024. Apply today to secure your space in the program.

Program Length 12 months

Program Format 100% online

Live-Online Schedule 1x per week for 90 minutes in the evening

Taught By School of Computer Science

Request Info

Questions? There are two ways to contact us. Call 412-501-2686 or send an email to  [email protected]  with your inquiries .

Program Name Change

To better reflect the emphasis on machine learning in the curriculum, the name of this certificate has been updated from Computational Data Science Foundations to Machine Learning & Data Science Foundations.

Although the name has changed, the course content, faculty, online experience, admissions requirements, and everything else has remained the same. Questions about the name change? Please contact us.

Looking for information about CMU's on-campus Master of Computational Data Science degree? Visit the program's website to learn more.  Admissions consultations with our team will only cover the online certificate program.

A National Leader in Computer Science

Carnegie Mellon University is world renowned for its technology and computer science programs. Our courses are taught by leading researchers in the fields of Machine Learning, Language Technologies, and Human-Computer Interaction. 

Number One  in the nation for our artificial intelligence programs.

Number One  in the nation  for our programming language courses.

Number Four  in the nation for the caliber of our computer science programs.

Privacy Engineering Program

Software and societal systems department, who should apply, how to apply, statement of purpose..

Type a concise one- or two-page statement in this format: Part I: Briefly state your objective in pursuing the MSIT Privacy Engineering professional graduate degree. Tell us if you have a particular reason for applying to this degree. Part II: Describe your background in fields particularly relevant to your objective. List here any relevant academic, industrial or commercial experience. Part III: Include any additional information you wish to supply to the Admissions Committee.

Transcripts

We will request transcripts from you only if you are offered admission into our program; please do not send them otherwise .  After receiving your offer, you may submit transcripts from all undergraduate and graduate institutions attended, even if no degree was granted. Transcripts should be in an official sealed envelope. The transcript may be mailed with your application or sent directly from the institution to the admissions coordinator address below.

Submit your current resume, including a summary of research and industrial experience and a list of publications (if any). Include copies of any peer-reviewed research publications (in English only) that you may have.

GRE scores are optional, but applicants who have taken the GRE are encouraged to submit their scores.

Send your scores to the School of Computer Science, Carnegie Mellon University; Institute Code: 2074, Department Code: 0402.

English Language Aptitude Test Scores

TOEFL/IELTS Duolingo - If your native language (language spoken from birth) is not English, an official copy of an English proficiency score report is required.  The English proficiency requirement cannot be waived for any reason . We strongly encourage applicants to take either the TOEFL or the IELTS.  In cases where these are not available it is acceptable to take the Duolingo test.  We discourage the use of the "TOEFL IPT Plus for China" since speaking is not scored. If you have previously taken the TOEFL or IELTS, your scores will be accepted if they are less than two years old. Your English language test score should indicate proficiency (A Duolingo score of 120 is equivalent to a TOEFL iBT score of 97-10). Send your scores directly to Carnegie Mellon University - School of Computer Science; Institutional Code: 4256; Departmental Code: 78.

Three Letters of Recommendation

The admissions committee prefers, but does not require, letters from both academia and industry. People who recommend you should know you relatively well and should be able to discuss the quality of your work.

Application Fee

The application fee is $80 if you apply by the early deadline (November 29, 2023; $100 after that. 

Application Info

Applications for part-time students open September 6, 2023

Application Deadline is January 28th 2023

Applicants apply here.

For any questions regarding applications to the Privacy Engineering program, please contact us via the link below.

• Incoming Student Info
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Tuition and fees

Frequently asked questions, how competitive is the selection process.

The MSIT Privacy Engineering program is very selective. We are looking for students with strong backgrounds in computer science or related fields, good communication skills, and a passion for privacy engineering.

What are the minimum TOEFL, IELTS, GRE, and GPA scores for your program?

English language competency is strongly correlated to academic and professional success. Thus the degree program has a minimum English competency score requirement. A successful applicant will normally have a total TOEFL iBT score of at least 100 (with no sub-score less than 22) or an IELTS score of at least 7.5.  A Duolingo score of 120 is equivalent to a TOEFL iBT score of 97-102. The degree program does not have a minimum GRE or GPA requirement. However, admitted students generally have GRE scores above the 90th percentile on the quantitative exam and above the 50th percentile on the verbal exam.

Do I have to take the TOEFL?

TOEFL/IELTS - If you are an international applicant and your native language (language spoken from birth) is not English, an official copy of your score report is required. The TOEFL/IELTS requirement cannot be waived for any reason. As you may be aware, the English proficiency testing situation worldwide continues to change rapidly. We currently strongly discourage the use of the "TOEFL iBT Plus for China", since speaking is not scored. Applicants currently in mainland China are encouraged to take the IELTS test. Your application will NOT be considered COMPLETE without the TOEFL or one of the other English proficiency tests mentioned.

What makes a good personal essay for my application?

We are looking for strong evidence that you can do well in our degree program. For example, a description of your research project experience, your involvement in the project, and the impact of the research is good evidence. A description of a large software project, your involvement in the project, and the impact of the project is good evidence. A historical essay that starts with your first use of computers at age five is not good evidence. Please write the essay yourself. Get help of course, but it should be substantially your own words.

What makes for a good letter of recommendation?

The strongest letters come from respected advisors and managers who know your work and who write favorably about your work. A letter from a professor who taught you in a class provides fine but not great evidence. These people simply know your abilities less well than a research advisor or a manager.

Are research publications required for my application?

No, publications are not required, but they are perhaps the best evidence that you can do high quality research. Not all admitted students will have them.

Is work experience required for my application?

No, work experience is not required. However, we value some types of work experience highly, particularly if the experience is close to the type of work our graduates perform. We also value summer internships and undergraduate research experiences.

Is scholarship funding available?

We are working on lining up some scholarships for the MSIT-PE program and expect to have more information available soon.  Get your application in by the deadline in order to be eligible.  Students are also encouraged to apply for scholarships from outside organizations.  For example, US citizens may be eligible for the  SMART Scholarship for Service Program .  The ACSA (Applied Computer Security Associates) offers scholarships for women studying information security.  Female applicants are eligible for this scholarship and the deadline for this is February 1.  For more information see  SWSIS .

Can I continue to the Ph.D. degree after graduating from the MSIT Privacy Engineering program?

There is no Privacy Ph.D. degree and the MSIT-PE is a professional master’s degree program designed to prepare students who intend to work as privacy professionals in industry or government.  This being said successfully completing the degree with good grades could give a Ph.D. application in any program a big boost in several ways. Your MSIT-PE GPA would likely be viewed positively  in the evaluation of an application. In addition, performing research as part of the degree (e.g., course project, capstone project) could also increase your chances of success. Finally, admission into the MSIT-PE program is very selective. There are no guarantees, of course. Students interested in pursuing a Ph.D. at Carnegie Mellon should instead consider directly applying to a PhD Program such as the PhD programs in  Societal Computing ,  Engineering and Public Policy ,  Human Computer Interaction ,  Computer Science ,  Electrical and Computer Engineering , or  Public Policy and Management .

Can I take courses in other parts of CMU (Heinz School of Public Policy, Tepper School of Business, etc.)?

Yes, a number of courses in other parts of the university are available to MSIT-PE students as general electives.

Do we have a comprehensive exam or graduation exam?

There are no comprehensive exams in the MSIT-PE program. The student integrates their academic experience with practical application via the capstone project.

Where do I find out more about graduate education at Carnegie Mellon University?

Visit the  Carnegie Mellon University Graduate Education website .

Doctoral Degree in Computer Science

Carnegie Mellon's Ph.D. in Computer Science is, above all, a research degree. When the faculty award a Ph.D., they certify that the student has a broad foundation and awareness of core concepts in computer science, has advanced the field by performing significant original research and has reported that work in a scholarly fashion.

When you begin our Ph.D. program, you’ll take the Introductory Course for Doctoral Students — an intense two week program that orients you to the department, introduces you to research and education topics our faculty are interested in, helps you find a faculty advisor and familiarizes you with Carnegie Mellon’s resources. Next, you’ll gain a broad understanding of fundamental research issues in major areas of computer science through coursework and original research. Finally, you’ll write and orally defend a thesis that guarantees you understand the area well enough to advance the state of knowledge in the field.

During the first two years of the program, you’ll gain the foundation of knowledge that will allow you to become an expert researcher in computer science, primarily by

Mastering a body of graduate material, achieved by passing 96 university units worth of graduate courses (equivalent to eight full-time courses).

Learning how to organize and begin to carry out original research, achieved by participating in directed research.

You will also serve as a teaching assistant, hone your writing and speaking skills and maintain your programming prowess. You’ll also receive periodic evaluation of your progress, and must make satisfactory progress to continue in the program.

Time Commitment:

As a Ph.D. student in computer science at CMU, you'll spend roughly five years acquiring a body of technical knowledge that includes a familiarity with the breadth of the field, as well as a deep understanding of your research area. From your second month in the program, you'll work closely with your faculty advisor, who is charged with guiding your education and monitoring your progress through the program. You'll take courses, teach and perform directed research — all to ensure that you leave Carnegie Mellon as an expert in your field. For a complete breakdown of our program requirements, read our Ph.D. Handbook .

Financial Information:

The Computer Science Department offers all Ph.D. students full financial support while they are in good academic standing in their respective programs. To learn more about Ph.D. funding, visit the SCS  Doctoral Programs  webpage.

Graduate Tuition: https://www.cmu.edu/sfs/tuition/graduate/scs.html

Student Fees: https://www.cmu.edu/sfs/tuition/fees/index.html

Carnegie Mellon Graduate Student Financial Aid: https://www.cmu.edu/sfs/financial-aid/graduate/index.html

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Electrical and Computer Engineering undergraduate program

The Department of Electrical and Computer Engineering's  (ECE) undergraduate program is broad and flexible, structured to provide students with limited constraints consistent with a rich, comprehensive view of the profession. The undergraduate curriculum comprises mathematics, computer science, statistics, and more and accommodates students with diverse backgrounds, interests, and skills by enabling multiple paths to success. Students can configure their program to meet their objectives, preparing them for careers in technology, industry, or graduate school, or as a launching pad for careers in business, law, medicine, or public service. Students may choose to pursue additional majors or minors to enhance their experiences gained in electrical and computer engineering.

Graduates of the program go on to work at companies like Accenture, Amazon, Apple, Capital One, Google, and Microsoft and pursue graduate degrees at academic institutions such as CMU, Stanford University, Cambridge University, and the University of Michigan.

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Degree programs

• Bachelor of Science in Electrical and Computer Engineering  (BS in ECE) The BS in ECE is a broad and highly flexible degree program, enabling students to explore a wide variety of areas within the field. Graduates of the program are able to identify, formulate, and solve complex engineering problems and apply engineering design to produce solutions for specified needs.
• Integrated Master’s/Bachelor’s in Electrical and Computer Engineering  (IMB) The IMB program allows students who excel academically to earn both a bachelor’s and master’s degree without needing to apply separately. Designed to provide extensive knowledge and technical proficiency, this program enhances students’ preparedness for careers in the industry. Typically completed in eight to ten academic semesters at CMU, this comprehensive experience ensures graduates are well-equipped for their professional endeavors.

Student experience

The ECE Department is committed to developing well-rounded students both in and out of the classroom. Students are encouraged to participate not only in engineering-specific events but also in campus and city-wide activities. With over 400 student-run organizations , Carnegie Mellon University offers opportunities for students of all backgrounds and interests.

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Health & Biomedicine

How does learning something new not overwrite what we know?

Researchers from Carnegie Mellon University and University of Pittsburgh examine what happens in the brain when it’s presented with learning a new task, but also asked to recall a familiar one.

Faculty from Carnegie Mellon University will collaborate with West Virginia University and University of Pittsburgh on a National Science Foundation Regional Innovation Engines program.

CMU partners to reimagine energy in the region

News & Events

2024 NSF CAREER Awards

The National Science Foundation (NSF) has awarded Giulia Fanti, Guannan Qu, and Akshitha Sriraman, all assistant professors of electrical and computer engineering, the NSF Faculty Early Career Development (CAREER) Award.

Zhang receives NSF CAREER Award

Xu Zhang received an NSF career grant for his work on device fabrication and system-level applications of atomically thin 2D materials.

Artificial Intelligence

PennDOT Secretary meets Carnegie Mellon transportation experts

PennDOT Secretary Michael Carroll visited CMU facilities at Mill 19 to meet transportation researchers and learn about collaboration opportunities.

New center to investigate quantum computing

A new National Science Foundation Industry-University Cooperative Research Center at CMU will create an ecosystem that advances quantum computing and information technologies.

Detecting brain tsunamis

Researchers from Carnegie Mellon University, the University of Pittsburgh, and the University of Cincinnati have combined their expertise in engineering and medicine to create a noninvasive method for detecting worsening brain injuries before they happen. This advancement could reshape neurocritical care.

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College of Engineering dean, professor, and alumnus inducted in the National Academy of Engineering.

Faculty and alumnus inducted into the National Academy of Engineering

Relationships are key to the research and the researchers

Zeynep Ozkaya’s work in Jana Kainerstorfer’s biophotonicslab has helped her to better understand the signal processing principles she is learning in her electrical engineering courses.

USDOT Deputy Secretary meets CMU transportation researchers

Carnegie Mellon is working closely with the USDOT to transform the U.S. transportation system through research that focuses on safety, economic growth, climate and sustainability, and equity.

Cybersecurity

Carnegie Mellon’s hacking team wins 7th DEF CON Capture-the-Flag title

The winningest team in DEF CON’s Capture-the-Flag (CTF) competition history, CMU’s Plaid Parliament of Pwning defended its title, earning its seventh victory in the past 11 years.

Exchanging campuses, making global connections

Through the Global Campus Exchange program, engineering students have the opportunity to experience what it is like to be enrolled at another CMU location.

The CMU community is familiar with Spring Carnival, but what goes on behind the scenes to make it all happen? The students in Spring Carnival Committee’s Electrical Subcommittee play a major role in making it all connect.

Spring Carnival runs on connections

Energy & Environment

Forbes includes six CMU alumni in 30 Under 30 in Energy

Six alumni were listed in Forbes 30 Under 30 in Energy for their groundbreaking startup companies.

Cyberphysical Systems

Carnegie Mellon awarded $20M for transportation research

Congresswoman Summer Lee and U.S. Department of Transportation (USDOT) announce that CMU will lead consortium that will receive $20 million to create Safety21, a University Transportation Center.

Reimagining datacenters

Akshitha Sriraman is rethinking datacenter computing across hardware and software systems to enable efficient, sustainable, and equitable large-scale web systems.

MSE students win big with doctoral research at 3MT championship

MSE Ph.D. students earned first place overall, the People’s Choice Award, and the Alumni Choice Award at the Carnegie Mellon Three Minute Thesis (3MT) Competition.

Improving air quality in Africa

CMU-Africa, CMU-Pittsburgh, and global collaborators create an air quality testing center in Ghana with new funding from the Clean Air Fund.

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Admissions Open in Computer Science

Phd program in computer sciencesemester 1/2024, apply now – april 22, 2024 ..

International Program Type 1.1: For Master’s degree holder. Duration of Study : 3 years (6 semesters) Type 2.2: For Bachelor’s degree holder. Duration of Study : 4 years (8 semesters) . Apply and More Information Type1.1 >> https://admission.grad.cmu.ac.th/admissions/indexeng.php?p=107&id=10686 Type2.2 >> https://admission.grad.cmu.ac.th/admissions/indexeng.php?p=107&id=10687

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U.S. News & World Report ranks UC Berkeley computer science graduate program No. 1

UC Berkeley’s computer science graduate program was ranked first in the nation for the second year in a row by U.S. News & World Report , according to 2024 rankings  released April 8.

Berkeley’s program in the Department of Electrical Engineering and Computer Sciences shared the top spot with computer science programs at the Massachusetts Institute of Technology, Stanford University and Carnegie Mellon University. 

Several other Berkeley graduate programs in business, public health, public affairs and more were listed in the top 20 for their disciplines. These rankings are based on a survey of academics at peer institutions, according to U.S. News .

Berkeley’s Department of Electrical Engineering and Computer Sciences is shared by the College of Computing, Data Science, and Society and the College of Engineering. Learn more about Berkeley’s computer science graduate program.