Joint Ph.D. Programs

Carnegie Mellon University is a global leader in innovation, championing interdisciplinary inquiry and deeply collaborative problem-solving. Heinz College offers the following joint Public Policy Ph.D. programs, in cooperation with other departments on campus.

The Joint Ph.D. programs in Public Policy are tailored toward students who have both policy and core-disciplinary interests.

Joint Ph.D. students not only complete disciplinary training, but they also apply those theories and methods to matters of public interest (such as crime prediction and prevention, cybersecurity and privacy, education policies, or technological change in society).

These programs are rigorous and highly selective. Students who have strong disciplinary backgrounds—and who also wish to bring those disciplines to bear on public policy problems—are encouraged to apply.

Heinz College / Tepper School of Business

Acquire in-depth training in economics, quantitative methods, and substantive policy areas. Students interested in labor, education, and trade policies should strongly consider this program.

Key Heinz Faculty

Lee Branstetter
Karen Clay
Lowell Taylor
Brian Kovak

Examination requirements

Ph.D. in Economics & Public Policy students are not required to take courses at Tepper, but they are required to pass the following qualifying examinations:

Microeconomics
Macroeconomics
Econometrics
Public Economics

Microeconomics exam covers: Microeconomics I, Microeconomics II, Game Theory and Applications, and Economics of Contracts.

Macroeconomics exam covers Macroeconomics I, Dynamic Competitive Analysis, and Computational Methods for Economics.

NOTE: The Microeconomics and Macroeconomics qualifying exams are the same exams that all Tepper Economics PhD students take.

Econometrics requirement can be satisfied in two ways: They may take the Tepper qualifying examination in Econometrics, or they may take the Heinz quantitative requirements course sequence and take a qualifying examination based on that course sequence.

Students with appropriate preparation prior to their entry to the joint program may choose to take the qualifying exams prior to the third semester.

Course Requirements

The course requirements for the joint program combine those of the separate programs, with the following differences:

Students have the flexibility to take econometrics sequences at Tepper or Heinz, and can also take certain courses in econometrics/statistical methods within the Department of Statistics.
The Heinz research seminar requirement is reduced from a two-course requirement to a one-course requirement. Public Economics is typically taught in research seminar format.

Heinz College / School of Computer Science

The Joint Ph.D. Program in Machine Learning & Public Policy is a program for students to gain the skills necessary to develop new state-of-the-art machine learning technologies and apply these successfully to real-world policy issues. Students are expected both to make fundamental contributions to the science of machine learning as well as addressing core problems in one or more policy domains.

Key Heinz Faculty

Leman Akoglu
David Choi
George Chen
Rayid Ghani

Program Requirements

Students interested in the joint Ph.D. in Machine Learning & Public Policy must first gain admission to and enroll in either the Ph.D. in Public Policy and Management program or the Ph.D. in Information Systems and Management at Heinz College. Students should apply to the program most closely aligned with their main research interests. Students may apply to the joint program only after beginning their Ph.D studies at Heinz College. Get more details on Ph.D. admissions.

Heinz College Ph.D. students should express their interest early to their Heinz College advisor to plan appropriately for applying to the ML program.
Students must complete their Heinz College Ph.D. program requirements (PPM or ISM), as well as the Ph.D in Machine Learning requirements listed below:
- Completion of the five ML Core courses, with an average GPA of 3.5
- Completion of a Data Analysis Project, satisfied within the student's home department.
- Serve once as a Teaching Assistant for the Machine Learning Department

The Joint Ph.D. thesis committee must include one MLD Core or Affiliated Faculty, and the thesis proposal/defense must be announced to the MLD community.

Heinz College / Dietrich College of Humanities and Social Sciences

Heinz College and the Department of Statistics offer a joint Ph.D. in Statistics & Public Policy. This five-year program provides students with comprehensive preparation at the Ph.D. level in both statistics and public policy. The curriculum draws on existing courses in both Statistics and Heinz College, recognizing that selected courses can meet objectives of both programs.

Critical to the success of the joint program is the close collaboration among faculty members from Heinz College and Statistics. While students will have separate faculty advisors from both sides, their progress will be regularly assessed by a joint group of faculty.

Key Heinz Faculty

David Choi
Amelia Haviland
Daniel Nagin

Program Requirements

The Statistics & Public Policy curriculum is tailored to the individual student's interests and needs, but the general strategy is similar: to meld the two sets of Ph.D. requirements into a coherent and useful set of courses, with similar core items.

The dissertation research topic for students in the joint program should be relevant to both faculties, and the dissertation will be supervised jointly by members from both sides.

A sample schedule can be viewed on the Dietrich website.

There will only be a single thesis proposal and thesis defense. These will involve presentations to a joint group of faculty and students from the two separate programs, and the basic rules will resemble closely those used for Statistics proposals and dissertations.

Joint Ph.D. Programs