To provide advanced graduate training in all aspects of computer science related to dealing with large
amounts of data.
There are two degree programs: M.S. and PhD. Within for course-only, project, and thesis based programs.
PhD in Computing: Data Management and Analysis
MS in Computing: Data Management and Analysis
The Data Management and Analysis Track within the Computing Degree Program will be administered by the Track Committee
Faculty (TCF). The TCF will elect each year a Chair from among its members. The Chair of the
TCF will oversee and coordinate all track administrative issues.
The current TCF consists of the following School of Computing faculty:
Hal Daume III
Juliana Freire
Ellen Riloff
Claudio Silva
Suresh Venkatasubramanian
Track Admissions
The TCF will work in conjunction with the School of Computing graduate admissions committee to review
track admissions. The means by which this will occur will be determined yearly between the TCF Chair,
the School of Computing Director, and the Director of Graduate Admissions.
Prerequisite Requirements
The nature and importance of information spans many fields. For this reason, students having a Bachelor's
degree in any science discipline will be considered for entry into the program.
Competency as determined by the TCF Chair in material spanning the following classes will be required:
Math 2250 Engineering Math (Linear algebra)
CS 3500 Software Practice
CS 4100 Advanced Algorithms and Data Structures
Students may be admitted to the program with probationary status contingent upon taking courses as
determined by the TCF Chair which eliminate prerequisite material deficiencies.
Program of Study: Ph.D.
Course work listed on the approved Program of Study form must comprise at least 50 semester hours of
graduate course work and dissertation research, exclusive of independent study. At least 14 semester hours
of dissertation research (CS 7970) and 24 semester hours of graduate course work must be included. Up
to 12 hours of graduate level course work already applied to other degrees may be used in the program of
study as approved by the TCF Chair.
Required Courses/Comprehensive Exam
Ph.D. students must demonstrate core knowledge in the area of information by passing three specified
courses, prior to the start of their fifth semester of study, with grades of B or better in each course and
an overall GPA in the specified courses of at least 3.5. This requirement constitutes the Comprehensive
Exam. The specific courses consist of the following:
CS 6150 Algorithms (3 hours)
CS 6350 Machine Learning (3 hours)
CS 6530 Database Systems (3 hours)
Students may place out of this requirement by substituting or transferring courses from other institutions
at the discretion of the TCF Chair.
Elective Courses
A student must take five elective courses (fifteen hours) which involve the areas related to information,
or are directly applicable to the student's dissertation research. Up to three courses (nine hours) may be
taken from other departments at the University of Utah. All elective courses on the Program of Study
must be taught at the graduate level. For those classes taken within the School of Computing, it is advised
that students take 6000 level courses and above when available/appropriate. All courses taken by a track
student to fulfill the elective requirements must be approved by the studentŐs committee and the TCF
Chair.
The following list contains some of the possible elective courses from the School of Computing which a
student may take to fulfill the elective requirements.
CS 6100 Foundations of Computer Science
CS 6210 Advanced Scientific Computing I
CS 6300 Artificial Intelligence
CS 6320 Computer Vision
CS 6340 Natural Language Processing
CS 6490 High Performance Parallel Computing
CS 6630 Scientific Visualization
CS xxxx Applications of NLP
CS xxxx Web Mining
CS xxxx Advanced Databases
CS xxxx Geometry
CS xxxx Data Mining
(Courses marked xxxx are currently listed as special topics courses but will be given a permanent number in the future.)
The following list contains some of the possible elective courses from outside the School which a student
may take to fulfill elective requirements:
MATH 5010 Introduction to Probability
MATH 5080 Statistical Inference I
MATH 5090 Statistical Inference II
MATH 5250 Matrix Analysis
MATH 6010 Linear Models
MATH 6020 Multilinear Models
MATH 7870 Methods of Optimization
ECE 5510 Random Processes
ECE 6520 Information Theory and Coding
ECE 6540 Estimation Theory
ECE 6551 Survey of Optimization Techniquies
IS 6481 Data Warehousing
IS 6482 Data Mining
BMI 6010 Foundations of Medical Informatics
BMI 6020 Foundations of Bioinformatics and Genetic Epidemiology
BMI 6105 Statistics for Biomedical Informatics
BMI 6300 Medical Decision-Makeing
Independent study courses (CS 6950 and CS 7950) cannot be included in the Program of Study for the
Ph.D. degree.
Students may place out of this requirement by substituting or transferring courses from other institutions
at the discretion of the TCF Chair.
One year of study must be spent in full-time residency at the University (i.e., the student must enroll for
a minimum of nine hours per semester for two consecutive semesters, summer optionally excluded). After
the residency requirement is fulfilled, registration for three semester hours of CS 7970 (Ph.D. Dissertation
Research) is considered a full load.
The Program of Study form should be filed with the School of Computing in the second semester of
study and with the Graduate School prior to taking the qualifying examination. The Program of Study
form must be submitted to the Graduate Records Office no later than the last day of the semester preceding
the semester of graduation.
Student Committee Requirement
Each student forms a supervisory committee whose members guide the student's research program. The
committee conducts the student's written qualifying examination, oral qualifying examination, and dissertation
defense. A Ph.D. supervisory committee consists of five faculty members. At least three faculty
members must be long-term instructional (LTI) faculty in the School of Computing, two of whom must
be from the TCF. At least one member must be from outside the School of Computing. Any School of
Computing long term instructional faculty member with advising privilege may serve as a supervisory
committee chair.
Final approval of all supervisory committees is granted by the TCF Chair and the Dean of the Graduate
School. Students must form this committee by the end of the second semester of study, although a
committee may be revised later by petition to the Graduate Studies Committee.
Qualifying Examination/Dissertation Proposal
After passing the Comprehensive Examination, all Ph.D. students must pass a Qualifying Examination, as
specified by the Graduate School. The Qualifying Exam consists of a written part, to be conducted first,
and an oral part.
The written part of the Qualifying Examination will cover the candidate's general area of specialization
in sufficient depth to demonstrate his/her preparation for conducting Ph.D.-level research. Each member
of the studentŐs supervisory committee will contribute one or more questions to this exam. The supervisory
committee will provide a written evaluation of this part of the exam, including an indication of whether
or not the student will be allowed to proceed to the oral part of the Qualifying Examination.
The oral part comprises the dissertation proposal defense. At the supervisory committeeŐs option, it
may also include follow-up questions relating to the written part of the exam. A majority of the supervisory
committee should certify that the proposal is ready to be defended prior to conducting the oral part of the
Qualifying Exam. For guidelines on preparing proposals, consult Discussion on Ph.D. Thesis Proposals
in Computing Science, by H. C. Lauer. Copies are available from the Graduate Coordinator or from the
Thesis Editor. A copy of the dissertation proposal must be in the student's file.
Students should pass their Qualifying Examination by the end of their sixth semester of study, not
counting summer enrollment. The Qualifying Examination must be completed no less than one semester
prior to defense of the dissertation.
Dissertation Defense
The supervisory committee must give preliminary approval of the thesis or dissertation prior to the defense.
The defense can be scheduled after this approval. To schedule the defense, contact the Graduate
Coordinator. Students are strongly encouraged to schedule the defense during a regular colloquium slot.
The student must provide one copy of the thesis or dissertation to the chair of the supervisory committee
at least three weeks before the defense, and one copy to each of the other committee members at least
two weeks prior to the defense. A complete draft of the thesis or dissertation must be delivered to the
Graduate Coordinator one week prior to the announced time of defense. This copy will be made available
for public access. Students are encouraged to place an additional copy on the School of Computing web
pages at least one week prior to the announced time of defense.
After successfully defending the thesis or dissertation, the student must obtain approval from the Final
Reader (typically the supervisory committee chair), School Director and Dean of the Graduate School. A
draft of the final thesis or dissertation must then be presented to the Thesis Editor. Successful completion of
the defense must be reported to the Graduate School at least four weeks before the last day of examinations
in the final semester. Students should also read the document regarding copyright notices provided by the
School and declare their intentions regarding granting the School the right to photocopy the dissertation
before notifying the Graduate Coordinator of completion of the defense.
The student has one month after the defense to make any revisions prior to submitting the thesis
or dissertation to the Graduate School Thesis Editor. There will be at most two additional months to
complete any changes required by the Thesis Editor before final acceptance. If either of these deadlines
are not met, the candidate must redo the oral defense. The final thesis or dissertation must be filed one
week before the end of the semester of graduation.
Students are expected to offer each committee member a bound copy of the thesis or dissertation once
it is completed. Detailed policies and procedures concerning the thesis or dissertation are contained in
"A Handbook for Theses and Dissertations" published by the Graduate School. The Dissertation defense
should be held by the end of the seventh year of graduate study.
Program of Study: M.S.
A student may pursue an M.S. with a (1) course-only option, or (2) a project option. The minimum
number of credits for either option is 30 graduate level classes (this includes 5000 and 6000 level courses
as designated by departments). The individual option requirements are:
Course-only Option Requirements
Required courses (3):
CS 6150 Algorithms (3 hours)
CS 6350 Machine Learning (3 hours)
CS 6530 Database Systems (3 hours)
3 courses from the following list:
CS 6100 Foundations of Computer Science
CS 6210 Advanced Scientific Computing I
CS 6300 Artificial Intelligence
CS 6320 Computer Vision
CS 6340 Natural Language Processing
CS 6490 High Performance Parallel Computing
CS 6630 Scientific Visualization
CS xxxx Applications of NLP
CS xxxx Web Mining
CS xxxx Advanced Databases
CS xxxx Geometry
CS xxxx Data Mining
(Courses marked xxxx are currently listed as special topics courses but will be given a permanent number in the future.)
Elective courses chosen from any graduate level CS courses, including seminars and independent study
(a maximum of 3 hours of independent study is allowed). With approval of the supervisory committee, a
student may take two elective courses at the graduate level or higher from other departments, excluding
independent study, seminars and research credit. Thesis research hours are not counted toward degree.
Project Option Requirements
Required courses (3):
CS 6150 Algorithms (3 hours)
CS 6350 Machine Learning (3 hours)
CS 6530 Database Systems (3 hours)
2 courses from the following list:
CS 6100 Foundations of Computer Science
CS 6210 Advanced Scientific Computing I
CS 6300 Artificial Intelligence
CS 6320 Computer Vision
CS 6340 Natural Language Processing
CS 6490 High Performance Parallel Computing
CS 6630 Scientific Visualization
CS xxxx Applications of NLP
CS xxxx Web Mining
CS xxxx Advanced Databases
CS xxxx Geometry
CS xxxx Data Mining
(Courses marked xxxx are currently listed as special topics courses but will be given a permanent number in the future.)
Elective courses chosen from any graduate level CS courses, including seminars and independent study
(a maximum of 6 hours of independent study is allowed). With approval of the supervisory committee, a
student may take two elective courses at the graduate level or higher from other departments, excluding
independent study, seminars and research credit. Thesis research hours are not counted toward degree.