DONALD BREN SCHOOL OF INFORMATION AND COMPUTER SCIENCES
GRADUATE PROGRAM
The University of California is the State's primary research institution, and the Donald Bren School of Information and Computer Sciences is the only independent computer science school on any UC campus. Established in December 2002 when the 35-year-old Department of Information and Computer Science was promoted to independent school status, ICS embodies the University's tradition of excellence as a world leader in information and computer sciences. ICS recently received a $20-million endowment from The Irvine Company Chairman Donald Bren to assist in recruiting and retaining distinguished faculty scholars. ICS began construction on a new, six-story research and administrative facility during the winter of 2004 with completion expected in 2007. Committed to increasing diversity in computing, ICS created the Ada Byron Research Center in 2003 to address research and outreach topics aimed at increasing the participation of women and other underrepresented populations in computer science and information technology.
Faculty and student-driven research in ICS is supported through a variety of grants, gifts, and contracts from public and private institutions such as the State of California, the U.S. Department of Education, various U.S. defense agencies, the National Science Foundation, the National Institutes of Health, NASA, and several companies, including Boeing, Conexant, HP, IBM, Intel, Microsoft, Raytheon, Sun, Toshiba, and Unisys. Since 2000, ICS has received more than $66 million in extramural funding, in addition to the recent $20-million endowment. Faculty within the School are active participants and leaders of numerous research institutes spanning computer science, including: the Institute for Genomics and Bioinformatics, Institute for Software Research, Center for Embedded Computer Systems, California Institute for Telecommunications and Information Technology, Center for Pervasive Communications and Computing, and the Ada Byron Research Center.
ICS offers M.S. and Ph.D. degrees in Information and Computer Science. Enrollments in the M.S. program are being limited to those students with an undergraduate degree in computer science or a closely related field.
Both M.S. and Ph.D. students may complete one of the following concentrations: Algorithms and Data Structures (Theory); Artificial Intelligence (AI); Informatics (INF); Informatics in Biology and Medicine (IBaM); Information Access and Management (IAM); Statistics (Stats); and Systems (SYS).
Three additional concentrations are available to M.S. students-Embedded Systems; Knowledge Discovery in Data; and Arts Computation Engineering (ACE). In addition, the School also offers a general M.S. degree that does not identify with any specific concentration.
The M.S. and Ph.D. degree program in Networked Systems is supervised by an interdepartmental faculty group. Information is available in the Interdisciplinary Studies section of the Catalogue.
ADMISSION
Applicants will be evaluated on the basis of their prior academic record. Applicants for the M.S. degree are expected to have a bachelor's degree in computer science or a related field. Those who do not have an undergraduate degree in computer science may take the Computer Science Advanced GRE test to demonstrate sufficient background in the field. Scores are reviewed on a case-by-case basis. Ph.D. applicants will be evaluated in their potential for creative research and teaching in Information and Computer Science.
Applicants are expected to have (1) skills in computer programming at least equivalent to those obtained in college-level courses in programming and language development; (2) skills in mathematics equivalent to those obtained in complete college-level courses in logic and set theory, analysis, linear algebra and modern algebra, or probability and statistics; (3) data structures, analysis of algorithms, automata theory, or formal languages; and (4) computer architectures.
All applicants are evaluated on the materials submitted: letters of recommendation, official GRE test scores, official college transcripts, and personal statement. For more information, contact the ICS graduate counselor at (949) 824-5156 or send e-mail to gcounsel@ics.uci.edu.
Financial Assistance
Financial assistance is available to Ph.D. students in the form of fellowships, teaching assistantships, and research assistantships. Although assistance varies, it is the School's goal to support all entering Ph.D. students, subject to availability of funds. International students who are not citizens of countries where English is either the primary or dominant language, as approved by Graduate Council, and who apply for teaching assistantships must take the Test of Spoken English (TSE) or the Speaking Proficiency English Assessment Kit (SPEAK) examination and earn a minimum score of 50 to be considered for an award.
Financial assistance may be available through teaching assistantships and corporate internships for ICS M.S. students.
Students with a Previously Earned Master's Degree
Credit for one or all required courses may be given at the time of admission to those students who have completed a master's degree in computer science or a closely related field. Course equivalency will be determined by the ICS Associate Dean for Graduate Studies following a written recommendation from a sponsoring research advisor. Research advisors can require that a student take additional courses when this is appropriate.
An additional M.S. degree will not be awarded if the student currently holds an M.S. degree in computer science or a related field from another university.
Course Substitutions
A student who has taken relevant graduate courses at UCI or another university may petition to have a specific course certified as equivalent to one which satisfies ICS requirements. The petition should describe the course and can be approved either by a committee composed of the student's faculty advisor, the ICS Associate Dean for Graduate Studies and a faculty member who is in the concentration area in which the course is taught, or by the ICS Graduate Policy Committee. Only two courses can be substituted.
The Master of Science program offers concentrations in the same areas as the Ph.D. concentrations described under the Doctor of Philosophy heading below. For each of these concentrations, the course requirements for the M.S. are determined by the concentration track and are identical to those of the Ph.D., although completion plans differ.
In addition, the Master of Science program offers a general M.S. in ICS, a concentration in Embedded Systems, a concentration in Knowledge Discovery in Data, and a concentration in Arts Computation Engineering.
Detailed course requirements for the M.S. and Ph.D. degrees are listed in the following pages under each concentration area. M.S. students may select one of two options: thesis plan or comprehensive examination plan, as described below. The normative time for completion of the M.S. program is two years. All study must be completed within four calendar years from the date of admission.
Plan I: Thesis Plan. The thesis option is available for graduate students who may wish to continue on to a Ph.D. program or those who wish to concentrate on a specific problem. To qualify for this option, the student must be in good academic standing with the Department. The student must enroll in at least two quarters of Thesis Supervision (ICS 298) that will substitute for two required courses as specified under the concentration area or specialization of choice. All required courses must be completed with a grade of B or better, and the student must write a research or thesis project. A committee of three faculty members (voting members of the Academic Senate) will guide the student and give final approval of the thesis. The committee will consist of an advisor (ICS faculty member) who is willing to supervise the thesis project, and two other faculty members (one of which must be from ICS) who are willing to serve on the committee as readers of the thesis. An oral presentation of the thesis to the committee will be required. Seminar courses such as 229, 239, 259, 269, and 279 cannot be applied to the required "other graduate courses" units.
Plan II: Comprehensive Examination Plan. The student completes the required units as specified under the concentration area. Each course must be completed with a grade of B or better. Seminar courses such as 229, 239, 249, 259, 269, and 279 cannot be applied to the required "other graduate courses" units. The student must take a written comprehensive examination given by ICS faculty. The examination covers the core requirements and is given twice a year (fall and spring quarters).
ICS GENERAL M.S. DEGREE PROGRAM
The ICS general M.S. degree program is designed for students who do not wish to specialize in any specific area. Students can explore many of the advanced fields in computer science. These areas include: embedded systems, networking, databases, computational geometry, neural networks, data mining, machine learning, graph algorithms, VLSI, parallel architectures, user interfaces, bioinformatics, graphics and visualization, security and cryptography, HCI/CSCW, software engineering, data structures, and ubiquitous computing.
Required Courses
The following courses must be completed with a grade of B or better. Five courses, including at least one from each of the following three categories: Theory: Fundamentals of the Design and Analysis of Algorithms (ICS 260), Data Structures (ICS 261), Analysis of Algorithms (ICS 263); Architecture/CAD/Hardware: Embedded Systems Concepts (ICS 212), Computer Systems Architectures (ICS 241A), Computer Networks (ICS 243A), Introduction to Computer Design (ICS 252); Software and Systems: Human-Computer Interaction (ICS 205), Advanced Compiler Construction (ICS 211), Principles of Data Management (ICS 214A), Software Engineering (ICS 221), Distributed Computer Systems (ICS 242).
Seven additional courses which are either ICS graduate courses or ICS undergraduate project courses. At most two undergraduate project courses can count toward this requirement. (A course taken as an undergraduate student cannot count toward this requirement.) The undergraduate project courses are: Project in Human-Computer Interaction (ICS 105), Project in System Design (ICS 125), Comprehensive Project in Software System Evolution (ICS 126A-B), Advanced Project in Software Engineering (ICS 127), Project in the Social and Organizational Impacts of Computing (ICS 135), Language Processor Construction (ICS 145A), Project in Operating System Organization (ICS 145B), Logic Design Laboratory (ICS 155A), Computer Design Laboratory (ICS 155B), Advanced Computer Networks (ICS 156), Project in Algorithms and Data Structures (ICS 165), Project in Artificial Intelligence (ICS 175A), Introduction to Expert Systems (ICS 175B).
Comprehensive Examination
Each student must pass a general written comprehensive examination administered and evaluated by a committee assembled by the Associate Dean for Graduate Studies.
M.S. CONCENTRATION IN EMBEDDED SYSTEMS
The goal of the M.S. concentration in Embedded Systems is to prepare ICS students for the challenges in exploiting technologies that are driving computing-based systems into new and emerging application domains. The ever-increasing integration of communications, multimedia, computing and relentless digitization of data continues to expand the scope and the complexity of embedded systems. To appreciate these advances, and to productively contribute to future advances of these systems, a critical appreciation of the underlying scientific principles is a must. The goal of this program is to develop a comprehensive understanding of the hardware and software technologies used in embedded systems. Students will develop an understanding of the technology capabilities and limitations and the methods to evaluate design trade-offs between different technology choices.
Required Courses
The following courses must be completed with a grade of B or better: all students must complete Introduction to Embedded and Ubiquitous Computing Systems (ICS 212); five courses from the following: List A: Compilation and Compiler Design (ICS 211), Software for Embedded Systems (ICS 213), Validation and Testing of Embedded Systems (ICS 216), Prototyping of Embedded Systems (ICS 217), Computer Systems Architecture (ICS 241A), Computer Networks (ICS 243A), Network and Distributed Systems Security (ICS 243G), Parallel Computing (ICS 244), Introduction to Computer Design (ICS 252), and Advanced System Software (EECS 211).
Six additional courses chosen in one of the following two ways: (1) for students pursuing the M.S. thesis option, two four-unit courses in Thesis Supervision (ICS 298) plus four graduate courses taken from List A or the following List B; or (2) for all other students, six graduate courses taken from List A or the following List B: Introduction to Ubiquitous Computing (ICS 203A), Software Engineering (ICS 221), User Interfaces and Software Engineering (ICS 227), Modern Microprocessors (ICS 241B), Distributed Computer Systems (ICS 242), Wireless and Mobile Networking (ICS 243E), High-Performance Architectures and Their Compilers (ICS 245), Digital System Verification and Testing (ICS 251), Design Description and Modeling (ICS 253), VLSI System Design (ICS 254), Design Synthesis (ICS 256), System Tools (ICS 257), Combinational Algorithm for Design Synthesis (ICS 258), Data Compression (ICS 267), Graph Algorithms (ICS 265), Real-Time Computer Systems (Engineering EECS 223). M.S. students who do not have an undergraduate degree in Computer Science or equivalent must also take ICS 260.
Suggested Electives. Students may focus their studies in specific domains within embedded systems by completing groups of electives as shown below.
Embedded System Architectures Focus: ICS 241A and ICS 241B, ICS 244, ICS 245, ICS 252, ICS 253.
Embedded Software Focus: ICS 221, ICS 227, ICS 245.
Distributed and Networked Embedded Systems Focus: select four of the following five courses: ICS 241A, ICS 242, ICS 243A or ICS 243E, ICS 244.
Micro-Electronic Embedded Systems Focus: ICS 251, ICS 253, ICS 254, ICS 256, ICS 257.
System Reliability and Fault Tolerance Focus: ICS 241A, ICS 251, ICS 253.
Theoretical Foundations of Embedded Systems Focus: ICS 242, ICS 243A, ICS 258, ICS 265.
Comprehensive Examination or Thesis
Each student must either: (1) pass a written comprehensive examination administered by the Embedded Systems faculty; or (2) submit a thesis for approval by a three-person committee consisting of an advisor (who is an ICS Embedded Systems full-time faculty member) and two other full-time faculty members (one of which must be from ICS).
M.S. CONCENTRATION IN KNOWLEDGE DISCOVERY IN DATA
The goal of the M.S. concentration in Knowledge Discovery and Data is to educate students in both the fundamental principles of computational methods for modeling data, as well as to provide a broad foundation in emerging methods for knowledge discovery and data mining. Technological advances in digital data collection, memory capacity, and computational power, have revolutionized our view of data analysis in the past 10 years. The volumes of data being collected in science, business, medicine, and government are truly vast in nature. Across all of these areas, there is a rapidly increasing demand for better theories and tools to provide users with improved understanding of their data and to leverage their data for decision support.
Knowledge discovery in databases (KDD) is an emerging discipline within computer science, focused on the principles of how patterns and structure can be inferred from large data sets. It is an area of significant academic interest and research opportunity. For example, a Special Interest Group in Knowledge Discovery in Databases (SIGKDD) was recently started by the Association for Computing Machinery (ACM) to promote both research and professional activities in this area; a new journal called Data Mining and Knowledge Discovery was started in 1997; and the field sponsors an annual international conference with over 500 attendees. In addition, the National Science Foundation has recently begun a large interdisciplinary research program in Knowledge and Distributed Intelligence (KDI), based in part on recent research and interest in KDD. Industry participation is also very active with broad demand for graduates in this area, across a wide variety of companies engaged in leveraging scientific and business data for strategic purposes.
Required Courses
The following courses must be completed with a grade of B or better: Principles of Data Management (ICS 214A), Machine Learning (ICS 273A), Probabilistic Learning (ICS 274A), Data Mining (ICS 278), Descriptive Multivariate Statistics I (ICS 238A), and any two courses from the Artificial Intelligence Core Course List and any two courses from the Statistics Core Course List.
For students pursuing the M.S. thesis option, two four-unit courses in Thesis Supervision (ICS 298) plus any one course from the General Computer Science Course List completed with a grade of B or better.
For students not pursuing the thesis option, the following additional courses must be completed with a grade of B or better: any two courses from the General Computer Science List and one elective. For the elective, a non-ICS course can only be taken with the approval of a KDD faculty member.
Artificial Intelligence Core Course List: Project in Artificial Intelligence (ICS 175A), Information Retrieval, Filtering, and Classification (ICS 207), Introduction to Artificial Intelligence (ICS 270A), Network-Based Reasoning/Constraint Networks (ICS 275A), Network-Based Reasoning/Belief Networks (ICS 275B), Neural Networks (ICS 276A), Representations and Algorithms for Molecular Biology (ICS 277A).
Statistics Core Course List: Descriptive Multivariate Statistics II (ICS 238B), Discrete Mathematics and Probability (Psychology 203A), Introduction to Mathematical Statistics (Psychology 203B), Experimental Design (Psychology 203C), Theory of Mathematical Statistics (Mathematics 201A), Probability (Mathematics 270A-B-C).
General Computer Science Course List: Project in System Design (ICS 125), Human Computer Interaction (ICS 205), Software Engineering (ICS 221), Software Analysis and Testing (ICS 224), Advanced User Interface Architectures (ICS 227), Fundamentals of the Design and Analysis of Algorithms (ICS 260), Data Structures (ICS 261), Analysis of Algorithms (ICS 263), Graph Algorithms (ICS 265), Computational Geometry (ICS 266).
Comprehensive Examination
All students not pursuing the thesis option must pass a written comprehensive examination administered and evaluated by the KDD faculty.
M.S. CONCENTRATION IN ARTS COMPUTATION ENGINEERING (ACE)
As digital technologies infiltrate increasingly diverse aspects of cultural practice, and human culture at large is influenced by the presence of digital technologies, there is a profound need for a new type of professional in the entertainment industry, in education, and in the arts, who can help to construct, manage, and monitor these changes. Such a professional must be technically skilled, artistically skilled, and theoretically skilled, all at an equally high and rigorous level. The goal of the M.S. concentration in Arts Computation Engineering is to provide students with a broad-based and interdisciplinary training at the intersection of digital technology and cultural and artistic practices. The ACE program is coordinated across the Donald Bren School of Information and Computer Sciences, The Henry Samueli School of Engineering, and the Claire Trevor School of the Arts, and places equal emphasis on technical, artistic, and critical proficiency. Strongly practical in composition, it provides students with the opportunity to explore in detail topics such as telematic performance, immersive and augmented environments, embodied interaction, and the cultural impact of new technologies.
Graduation is by publicly presented thesis project and written thesis, in addition to completion of course work.
Required Courses
The ACE concentrations in all three fields consist of a two-year curriculum. The following courses are required:
ACE Core: five ACE interdisciplinary theory seminars (Informatics 270), four ACE studio/labs (Informatics 271-277), two ACE project internships (Informatics 279), and one quarter of ACE thesis research (Informatics 278).
(NOTE: A total of 48 units of Core courses must be completed. Any of the ACE core category courses may be reduced by one and replaced with a different ACE core course or an elective, in consultation with the student's advisor.)
Electives: a minimum of four ICS electives including one from each of the following three categories, passed with a grade of B or better:
Theory: Fundamentals of the Design and Analysis of Algorithms (ICS 260), Data Structures (ICS 261), Analysis of Algorithms (ICS 263);
Architecture/CAD/Hardware: Embedded Computing Systems (ICS 212), Computer Systems Architectures (ICS 241A), Computer Networks (ICS 243A), Introduction to Computer Design (ICS 252);
Software Systems: Human-Computer Interaction (ICS 205), Advanced Compiler Construction (ICS 211), Data Management (ICS 214A), Software Engineering (ICS 221), Distributed Computer Systems (ICS 242).
Two additional breadth electives: that may be chosen by students in consultation with an advisor, and/or may be assigned by the ACE program committee in consultation with the student. These courses will compensate for lacunae in the student's background and may include upper-division undergraduate courses when appropriate and approved in advance by the candidate's advisor.
A program faculty member from the School of ICS will advise on elective selection and may be on the thesis committee.
