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Joint Machine Learning PhD Degrees

Students interested in a Machine Learning- Joint PhD degree should first apply to the PhD program that best aligns with their research interests. (Machine Learning, Statistics, Neuroscience, Public Policy or Social & Decision Sciences)

The MLD requirements for graduation with a Joint-ML PhD degree are the same as those for the regular MLD PhD requirements (including the requirement for the PhD thesis committee composition), with only the following differences:

  • A Joint-ML PhD thesis will be a contribution to the combination of Machine Learning and the other field.
  • The single elective course, the speaking and writing skills requirements, and the Data Analysis requirement (10718) may be satisfied within the student’s home department.
  • A Joint-ML PhD student is still required to TA twice, but only one TA-ship has to be within MLD

A student in a Joint-ML PhD degree may earn a MS degree along the way, either from their home department or from MLD, but not from both.  To earn an MS in Research from MLD they must satisfy all the relevant requirements.

PhD in Statistics & Machine Learning

This PhD program differs from the Machine Learning PhD program in that it places significantly more emphasis on preparation in statistical theory and methodology. Similarly, this program differs from the Statistics PhD program in its emphasis on machine learning and computer science. The Joint PhD Program in Machine Learning and Statistics is aimed at preparing students for academic careers in both CS and Statistics departments at top universities or industry.

The student must be advised by a faculty from the home department along with a Core Faculty member from the joint department as a co-mentor. Joint Statistics-MLD faculty cannot serve both roles.  Both faculty must be identified at the time of admission to the joint program.

Note: MLD students are able to apply for this program after they have completed the courses and have a sponsoring faculty in Statistics make the case for admission.

Statistics Joint Program Requirements

Statistics PhD Online Application        Machine Learning PhD Online Application
For Statistics Dept. questions send email to: admissions@stat.cmu.edu
For Machine Learning Dept. questions send email to: ml-phd-admissions@cs.cmu.edu


PhD in Machine Learning & Public Policy

The Joint Ph.D. Program in Machine Learning and Public Policy is a program operated jointly by faculty in Machine Learning and the Heinz College (Schools of Public Policy, Information Systems, and Management). Students will gain the skills necessary to develop new state-of-the-art machine learning technologies and apply these successfully to real-world policy domains.

Public Policy Joint Program Requirements

Public Policy PhD Online Application           Machine Learning PhD Online Application

For Public Policy questions send email to: hnzadmit@andrew.cmu.edu
For Machine Learning Dept. questions send email to: ml-phd-admissions@cs.cmu.edu

PhD in Neural Computation & Machine Learning

This Joint PhD program trains students in the application of machine learning to neuroscience and neural inspired machine learning algorithms by combining core elements of the ML PhD program and the Program in Neural Computation (PNC) offered by the Neuroscience Institute (NI).

PNC Joint Program Requirements

Neural Computation PhD Online Application    Machine Learning PhD Online Application

For Neuroscience Dept. questions send email to: pnc-admissions@cnbc.cmu.edu
For Machine Learning Dept. questions send email to: ml-phd-admissions@cs.cmu.edu

PhD in Autonomous & Human Decision Making

This Joint PhD program trains students in both the technology of AI and human decision science, focusing on how and when AI can complement human decision making. Students will be trained in fundamentals of AI, autonomous decision making, fundamentals of human decision and behavioral science, cognitive models of decision making, and societal impact of AI technologies. This program is offered jointly by faculty in Machine Learning and Social and Decision Sciences.

Autonomous & Human Decision Making Joint Program Requirements

SDS PhD Online Application          Machine Learning PhD Online Application

For Social & Decision Science Dept. questions send mail to: John Miller
For Machine Learning Dept. questions send email to: ml-phd-admissions@cs.cmu.edu

 

To be considered...

In order to apply to a Joint ML PhD degree, a student must already be enrolled in one of the participating PhD programs in Machine Learning, Statistics, PNC, Heinz or SDS.

Before applying, a student must meet the following MLD requirements (in addition to any requirements from the other relevant Department) :

  • Take 10715, 36705, 10716 and earn at least a grade of A- in your first attempt to take each course. Letter grades are required. (Students who took courses before June 2023, will be Grandfathered in under the previous of B+ for the courses already taken.)
  • Identify a MLD Core Faculty member who agrees to serve as their MLD mentor.

Applications must be submitted by May 31st.

After completing the required courses apply by following the instructions below:

Please submit your online application by May 31st to include the following information:

  1. Statement of Purpose of why you would like to pursue the joint PhD degree.
  2. Your updated CV
  3. Your unofficial Carnegie Mellon Transcript, including your letter grades for 10715, 36705 & 10716.
  4. Your GRE & TOEFL (if applicable) from your original application to your current PhD program.
  5. Recommenders: (1) Ask your advisor to send a letter of recommendation with their agreement that the joint program would be a good thing for you to pursue and how it would benefit your research. (2) Ask your ML Core Faculty Mentor to send a letter of recommendation including why you would be a good fit for the joint program.
The online application opens January 15th and deadline is May 31st.

MLD Mentor

  • Provides ML expertise, advice and oversight to support the student’s research work.
  • Influences the student’s research direction to ensure that their PhD thesis makes sufficient contribution to machine learning to warranty a joint PhD in machine learning (a Joint ML PhD thesis will make a contribution to the combination of Machine Learning and the other field).  For this influence to be successful, a mentor must engage with the student early in their research explorations.
  • Meet with the student at least once per semester, preferably including the student’s home advisor, to discuss progress and plans. Student is responsible to schedule the meeting.
  • Maintains contact with the student’s home advisor.
  • Represents the student in MLD’s end-of-semester PhD student review.
  • A MLD mentor does not have a financial responsibility to the student, unless otherwise agreed in advance.