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Doctor of Philosophy in Intelligent Systems

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 thirty funded research projects, they support graduate students through collaborative research, personal mentoring, and external research funding.

Degree Requirements

Prerequisites: You are expected to have the undergraduate prerequisites needed to take the graduate courses required by the program. These may be required if not taken.

General Intelligent Systems Track Curriculum:

First-year students

  • ISSP 2020 – TOPICS IN INTELLIGENT SYSTEMS
  • INFSCI 3005 – INTRODUCTION TO THE DOCTORAL PROGRAM
  • ISSP 2030 – ADVANCED TOPICS IN INTELLGENT SYSTEMS

Core

  • ISSP 2160 – FOUNDTNS OF ARTIFICIAL INTELLGNC / CS 2710 – FOUNDTNS OF ARTIFICIAL INTELLGNC

AND Choose Two of the Following:

  • ISSP 2170 – MACHINE LEARNING / CS 2750 – MACHINE LEARNING
  • ISSP 2230 – INTRO NATURAL LANGUAGE PROCSSNG / CS 2731 – INTRO NATURAL LANGUAGE PROCSSNG
  • ISSP 2180 – COMPUTER VISION / 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:

  • CS 2110 – THEORY OF COMPUTATION
  • CS 2150 – DESIGN & ANALYSIS OF ALGORITHMS

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 Curriculum (ISP/MI)

This assumes that you already have training in a health care field; if this is not so, then the faculty will select a set of courses that teach you basic medical knowledge, and you 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 INTELLGENT SYSTEMS

Core

  • ISSP 2083 – BIOMDCL INFORMATICS JOURNAL CLUB / BIOINF 2032 – BIOMEDICAL INFORMATICS JOURNAL CLUB
  • ISSP 2015 – FOUNDATIONS OF CLINICAL AND PUBLIC HEALTH INFORMATICS / BIOINF 2011 – FOUNDATIONS OF CLINICAL AND PUBLIC HEALTH INFORMATICS
  • ISSP 2160 – FOUNDTNS OF ARTIFICIAL INTELLGNC / CS 2710 – FOUNDTNS OF ARTIFICIAL INTELLGNC

Then choose;

One of the following:

  • ISSP 2170 – MACHINE LEARNING / CS 2750 – MACHINE LEARNING
  • ISSP 2230 – INTRO NATURAL LANGUAGE PROCSSNG / CS 2731 – INTRO NATURAL LANGUAGE PROCSSNG
  • ISSP 2180 – COMPUTER VISION / CS 2770 – COMPUTER VISION

AND choose one of the following:

  • CS 1510 – ALGORITHM DESIGN
  • CS 2150 – DESIGN & ANALYSIS OF ALGORITHMS
  • CS 3150 – ADV TOPCS DSGN & ANALYS ALGORTHM

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 2070 – PROBABILISTIC METHODS / BIOINF 2101 – PROBABILISTIC METHODS
  • ISSP 2081 – FOUNDATIONS OF BIOINFORMATICS
  • ISSP 2240 – DECISION ANAL & DECISN SUPRT SYS / INFSCI 2130 – DECISION ANALYSIS AND DECISION SUPPORT SYSTEMS
  • BIOINF 2017 – CLINICAL RESEARCH INFORMATICS
  • BIOINF 2121 – HUMAN-COMPUTER INTERACTION AND EVALUATION METHODS
  • BIOINF 2117 – APPLIED CLINICAL INFORMATICS
  • BIOINF 2016 – FOUNDATIONS OF TRANSLATIONAL INFORMATICS
  • BIOINF 2124 – PRINCIPLES OF GLOBAL HEALTH INFORMATICS

Advanced courses

3 Graduate-level Courses (2000 or higher, 3 credits or more) ISSP lecture course that has your adviser’s approval as being relevant to your studies in the ISP are required.

Admissions Information

Letters of Recommendation

Identify and seek the recommendations of three individuals (e.g., professors, employers, information professionals) who are in a position to evaluate your academic performance or your potential as an information professional. At least one should be familiar with the field of intelligent systems.

Transcripts

Only scanned copies of official transcripts will be accepted and processed at the application stage.

Graduate Record Examination (GRE)

You are required to submit a recent score (within five years of the date of application) on the Graduate Record Examination as part of your admission credentials. Scores on all three sections (verbal, quantitative, and analytical) of the General Section should be submitted. There is no minimum score requirement.

Other Required Documentation

Please include the following with your online application:

  • CV; and
  • A concise statement of purpose that provides:
    • Your objective in pursuing a degree in intelligent systems.
    • Theoretical background in relevant areas.
    • Background in relevant tools and applications, particularly programming languages, including your level of proficiency.
    • Relevant practical experience, including industrial or commercial experience.

For International Applicants

Graduate students must possess sufficient knowledge of English to participate successfully in graduate study. International applicants must submit either the TOEFL or the IELTS (taken within two years of the date of application). A minimum score of 90 (with at least a score of 22 on each section) on the TOEFL or a minimum result of Band 7.0 (with at least a score of 6.5 on each section) on the IELTS is required.

Applicants to the Biomedical Informatics track of the Intelligent Systems Program must specifically indicate their interest in this track on their application to the Intelligent Systems Program. They must also submit an application to the Department of Biomedical Informatics in addition to submitting an application to the Intelligent Systems Program.

For more information, visit our Graduate Admissions FAQ.