Intelligent Systems, PhD

The Intelligent Systems Program (ISP) is a multidisciplinary graduate program at the University of Pittsburgh dedicated to applied artificial intelligence (AI). Many of Pitt’s acclaimed schools are represented through our associated faculty, including the School of Medicine, the School of Law, the School of Education, the Swanson School of Engineering, and the Kenneth P. Dietrich School of Arts and Sciences.

What Do We Offer?

  • Broadly interdisciplinary approach: We offer a strong, well-balanced foundation in the fundamentals of AI and many opportunities for advanced research and training in many disciplines, including computer science, biomedical informatics, cognitive psychology, information science, education, law, and more.
  • Focused, customized curricula: Building on the core curriculum, you design your own personalized curricula that prepares you for interdisciplinary research in your areas of interest.
  • Collaborative atmosphere: Faculty members and students present their research in regular program seminars, exposing you to a broad range of research topics and methods and affording you the opportunity to present your own research.
  • Highly motivated faculty: Pitt’s widely published ISP faculty are leaders in their fields. Drawing on the strengths of diverse sectors of the university, and participating in over 30 funded research projects, they support graduate students through collaborative research, personal mentoring, and external research funding.

Degree Requirements

Students are expected to have the pre-requisites needed to take the courses necessary to obtain the PhD degree in ISP. These may be required if not already taken.

General Intelligent Systems Track

First-year students


AND Choose two of the following:


Applied or mathematical statistics.  Choose one of the following:

Theory of computation, algorithms. Choose one of the following:

One additional course required. Any of the theory courses listed above are acceptable.

Advanced courses

Four ISSP advanced lecture courses, numbered 2000 or higher and approved by the PhD adviser.

Biomedical Informatics Track (ISP/MI)

This assumes that a student already has training in a health care field; if this is not so, then the faculty will select a set of courses that teach the student basic medical knowledge, and the student may take these courses as electives.

First-year students


Then choose:

One of the following:

AND choose one of the following:

AND choose one of the following:

AND choose two of the following:

Advanced Courses

Three (3) advanced lecture courses, numbered 2000 or higher, relevant to ISP and approved by the academic adviser.


TA any biomedical informatics (BIOINF) course that is cross listed as an ISSP course.

For more degree requirements details, visit the Intelligent Systems course catalog.

Admissions Requirements