Carnegie Mellon University

Joint PhD Program in Statistics & Machine Learning

The Joint Ph.D. Program in Statistics and Machine Learning is a program aimed at preparing students for academic careers in both CS and Statistics departments at top universities.
Students will be granted the joint degree if they meet TWO sets of program requirements corresponding to the TWO departments, namely the ML PhD Requirements and the Statistics PhD Requirements, as we present next.

ML Joint Program Requirements

  • Successfully complete the 5 ML Core courses, with an average GPA of 3.5. As of Fall 2018, Statistics courses other than 36-705 are not able to be counted as ML courses for Statistics students.
  • The Advanced Data Analysis (ADA) Project serves as the MLD Data Analysis requirement. (One Machine Learning Core or Affiliated faculty member must be on the committee). The presentation must be announced to the MLD community.
  • The Teaching Assistant requirement is satisfied within the Home Department

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

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Statistics Joint Program Requirements

For questions send email to:

MS degree along the way to the joint PhD

Students in the joint PhD program may earn a MS degree along the way to the joint PhD, but if they do they will have to decide if the degree will be from the Home Department or the Machine Learning Department. There is no joint MS degree and a student is not able to receive an MS from both departments. If choosing the ML MS degree, the student must comply with the requirements of the ML MS degree.