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
- ISSP 2020 - TOPICS IN INTELLIGENT SYSTEMS
- INFSCI 3005 - INTRODUCTION TO THE DOCTORAL PROGRAM
- ISSP 2030 - ADVANCED TOPICS IN INTELLIGENT SYSTEMS
Core
AND Choose two of the following:
- ISSP 2170 / CS 2750 - MACHINE LEARNING
- ISSP 2230 / CS 2731 - INTRO NATURAL LANGUAGE PROCESSING
- ISSP 2180 / CS 2770 - COMPUTER VISION
Theory
Applied or mathematical statistics. Choose one of the following:
- BIOST 2041 - INTRODUCTION TO STATISTICAL METHODS 1
- BIOST 2042 - INTRODUCTION TO STATISTICAL METHODS 2
- BIOINF 2118 - STATISTICAL FOUNDATIONS OF BIOMEDICAL INFORMATICS
- STAT 2131 - APPLIED STATISTICAL METHODS 1
- STAT 2132 - APPLIED STATISTICAL METHODS 2
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 elective courses, from the list below with the approval of the student’s academic advisor and Program Director. Contact the ISP Administrator after completing an advisor-approved elective course that falls outside of the ISSP course offerings, as a waiver may need to be submitted.
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
- ISSP 2020 - TOPICS IN INTELLIGENT SYSTEMS
- INFSCI 3005 - INTRODUCTION TO THE DOCTORAL PROGRAM
- ISSP 2030 - ADVANCED TOPICS IN INTELLIGENT SYSTEMS
Core
- ISSP 2083 / BIOINF 2032 - BIOMEDICAL INFORMATICS JOURNAL CLUB
- ISSP 2016 / BIOINF 2070 - FOUNDATIONS OF BIOMEDICAL INFORMATICS 1
- ISSP 2160 / CS 2710 - FOUNDATIONS OF ARTIFICIAL INTELLIGENCE
Then choose:
One of the following:
- ISSP 2170 / CS 2750 - MACHINE LEARNING
- ISSP 2230 / CS 2731 - INTRO NATURAL LANGUAGE PROCESSING
- ISSP 2180 / CS 2770 - COMPUTER VISION
AND choose one of the following:
- CS 1510 - ALGORITHM DESIGN
- CS 2150 - DESIGN & ANALYSIS OF ALGORITHMS
- CS 3150 - ADV TOPICS DESIGN & ANALYSIS OF ALGORITHMS
AND choose one of the following:
- BIOST 2041 - INTRODUCTION TO STATISTICAL METHODS 1
- BIOST 2042 - INTRODUCTION TO STATISTICAL METHODS 2
- BIOINF 2118 - STATISTICAL FOUNDATIONS OF BIOMEDICAL INFORMATICS
- STAT 2131 - APPLIED STATISTICAL METHODS 1
- STAT 2132 - APPLIED STATISTICAL METHODS 2
AND choose two of the following:
- ISSP 2017 / BIOINF 2071 - FOUNDATIONS OF BIOMEDICAL INFORMATICS 2
- ISSP 2240 / INFSCI 2130 - DECISION ANALYSIS AND DECISION SUPPORT SYSTEMS
- BIOINF 2121 - HUMAN-COMPUTER INTERACTION AND EVALUATION METHODS
- BIOINF 2117 - APPLIED MEDICAL INFORMATICS
- BIOINF 2016 - FOUNDATIONS OF TRANSLATIONAL INFORMATICS
- BIOINF 2124 - PRINCIPLES OF GLOBAL HEALTH INFORMATICS
Advanced Courses
Three ISSP advanced elective courses, from the list below with the approval of the student’s academic advisor and Program Director. Contact the ISP Administrator after completing an advisor-approved elective course that falls outside of the ISSP course offerings, as a waiver may need to be submitted.
TA
Students will register for three credits of the BIOINF 3998 - Doctoral Teaching Practicum. Special enrollment permission must be obtained from BMI training program coordinator.
For more degree requirements details, visit the Intelligent Systems course catalog.