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, students must be in good academic standing with their Department. The student must enroll in at least two quarters of Thesis Supervision (CS 298 or Informatics 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 Informatics 209S, CS 239S, CS 259S, CS 269S, and CS 279S 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 Informatics 209S, CS 239S, CS 259S, CS 269S, and CS 279S cannot be applied to the required "other graduate courses" units. The student must take a 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 (CS 260), Data Structures (CS 261), Analysis of Algorithms (CS 263); Architecture/CAD/Hardware: Introduction to Embedded and Ubiquitous Systems (CS 244/Informatics 244), Computer Systems Architectures (CS 250A), Computer Networks (CS 232), Introduction to Computer Design (CS 252); Software and Systems: Human-Computer Interaction (Informatics 231), Advanced Compiler Construction (CS 241), Principles of Data Management (CS 222), Software Engineering (Informatics 211), Distributed Computer Systems (CS 230).

Seven additional courses which are either ICS, CS, Informatics, or Statistics graduate courses, or CS and Informatics 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 (Informatics 132), Project in System Design (Informatics 117), Comprehensive Project in Software System Evolution (Informatics 118A-B), Advanced Project in Software Engineering (Informatics 119), Project in the Social and Organizational Impacts of Computing (Informatics 163), Language Processor Construction (CS 142B), Project in Operating System Organization (CS 143B), Logic Design Laboratory (CS 153), Computer Design Laboratory (CS 154B), Advanced Computer Networks (CS 133), Project in Algorithms and Data Structures (CS 165), Project in Artificial Intelligence (CS 175), Introduction to Expert Systems (CS 176).

Comprehensive Examination

Each student must pass a general comprehensive examination administered and evaluated by a committee assembled by the Bren School Associate Dean for Student Affairs.

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 Systems (CS 244/Informatics 244); five courses from the following: List A: Compilation and Compiler Design (CS 241), Software for Embedded Systems (CS 245), Validation and Testing of Embedded Systems (CS 246), Prototyping of Embedded Systems (CS 247), Computer Systems Architecture (CS 250A), Computer Networks (CS 232), Network and Distributed Systems Security (CS 203), Parallel Computing (CS 242), Introduction to Computer Design (CS 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 (CS 298 or Informatics 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 (CS 248A/Informatics 241), Software Engineering (Informatics 211), User Interfaces and Software Engineering (Informatics 235), Modern Microprocessors (CS 250B), Distributed Computer Systems (CS 230), Wireless and Mobile Networking (CS 236), High-Performance Architectures and Their Compilers (CS 243), Digital System Verification and Testing (CS 251), Design Description and Modeling (CS 253), Design Synthesis (CS 254), System Tools (CS 255), Combinational Algorithm for Design Synthesis (CS 258), Data Compression (CS 267), Graph Algorithms (CS 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 CS 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: CS 250A and CS 250B, CS 242, CS 243, CS 252, CS 253.

Embedded Software Focus: Informatics 211, Informatics 235, CS 243.

Distributed and Networked Embedded Systems Focus: select four of the following five courses: CS 250A, CS 230, CS 232 or CS 236, CS 242.

Micro-Electronic Embedded Systems Focus: CS 251, CS 253, CS 254, CS 255.

System Reliability and Fault Tolerance Focus: CS 250A, CS 251, CS 253.

Theoretical Foundations of Embedded Systems Focus: CS 230, CS 232, CS 258, CS 265.

Comprehensive Examination or Thesis

Each student must either: (1) pass a 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).

INTERNATIONAL M.S. CONCENTRATION IN EMBEDDED SYSTEMS

ICS now offers an international version of its M.S. degree program in Information and Computer Science (with a concentration in Embedded Systems). The program is taught by UCI faculty in Naples, Italy, and at UCI. It starts with one five-week summer session at UCI, nine months in Italy, and concludes with an additional five-week summer session at UCI. This allows students to gain experience with the culture and business practices in the European Union, an important edge in the global corporate world. The program is geared toward the needs of both international and U.S. students who wish to participate. All courses will be taught in English. Internships at U.S. and European companies may be possible during or after the completion of the program. For more information see http://ms-es.cib.na.cnr.it/ or e-mail the program directors at alexv@ics.uci.edu or nicolau@ics.uci.edu.

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 (CS 222), Machine Learning (CS 273A), Probabilistic Learning (CS 274A), Data Mining (CS 285), Descriptive Multivariate Statistics I (Informatics 207), 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 (CS 298 or Informatics 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 (CS 175), Information Retrieval, Filtering, and Classification (CS 221), Introduction to Artificial Intelligence (CS 271), Network-Based Reasoning/Constraint Networks (CS 275), Network-Based Reasoning/Belief Networks (CS 276), Neural Networks (CS 281), Representations and Algorithms for Molecular Biology (CS 284A).

Statistics Core Course List: 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 (Informatics 117), Human Computer Interaction (Informatics 231), Software Engineering (Informatics 211), Software Analysis and Testing (Informatics 215), Advanced User Interface Architectures (Informatics 235), Fundamentals of the Design and Analysis of Algorithms (CS 260), Data Structures (CS 261), Analysis of Algorithms (CS 263), Graph Algorithms (CS 265), Computational Geometry (CS 266).

Comprehensive Examination

All students not pursuing the thesis option must pass a comprehensive examination administered and evaluated by the KDD faculty.

M.S. CONCENTRATION IN ARTS COMPUTATION ENGINEERING (ACE)

Arts Computation Engineering (ACE) Building; (949) 824-2109
Simon Penny, Co-Director
Robert Nideffer, Co-Director

See pages 99 and 206 for additional information concerning ACE faculty affiliation.

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 (ICS 271-277), two ACE project internships (ICS 279), and one quarter of ACE thesis research (ICS 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 (CS 260), Data Structures (CS 261), Analysis of Algorithms (CS 263);

Architecture/CAD/Hardware: Embedded Computing Systems (CS 244/Informatics 244), Computer Systems Architectures (CS 250A), Internet (CS 232/EECS248A/Networked Systems 201), Introduction to Computer Design (CS 252);

Software Systems: Human-Computer Interaction (Informatics 231), Advanced Compiler Construction (CS 241), Data Management (CS 222), Software Engineering (Informatics 211), Distributed Computer Systems (CS 230).

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.

The Doctor of Philosophy program offers concentrations in two areas: Informatics (INF) and Informatics in Biology and Medicine (IBaM).

The program is research oriented and encourages students to work together with faculty to solve advanced problems in computer science. The program is designed for full-time study, and the normative time for completion of the Ph.D. is five years (four years for students who entered with a master's degree), with the exception of the Informatics concentration which has a normative time of six years. The maximum time permitted for either concentration is seven years. Students enrolled in the Ph.D. program must maintain satisfactory academic progress.

Teaching Requirements for the Ph.D. Program

All ICS doctoral students are required to participate in a minimum of two quarters of teaching activities before graduating. Teaching activities in summer or night school or service at other U.S. universities may be accepted in fulfillment of this requirement.

Timeline for the Ph.D. Program

All course requirements must be satisfied prior to the student's application for advancement to candidacy. The normative time for advancement to candidacy is three years (two years for students who entered with a master's degree), with the exception of the Informatics concentration which has a normative time of four years. Information on the selection of committees, advancement to candidacy, development of a doctoral dissertation, and final examination on the dissertation is available from the ICS Graduate Student Affairs Office.

CONCENTRATION IN INFORMATICS (INF)

Informatics is the interdisciplinary study of the design, application, use, and impact of information technology. It goes beyond technical design to focus on the relationship between information system design and use in real-world settings. These investigations lead to new forms of system architecture, new approaches to system design and development, new means of information system implementation and deployment, and new models of interaction between technology and social, cultural, and organizational settings.

In the Donald Bren School of Information and Computer Sciences, Informatics is concerned with software architecture, software development, design and analysis, programming languages, ubiquitous computing, information retrieval and management, human-computer interaction, computer-supported cooperative work, and other topics that lie at the relationship between information technology design and use in social and organizational settings. Effective design requires an ability to analyze things from many different perspectives, including computer science, information science, organizational science, social science, and cognitive science. Relevant courses in those disciplines are therefore an integral part of the program and give this concentration a unique interdisciplinary flavor—which is imperative as the computing and information technology fields play such a pervasive role in our daily lives.

Students must complete the Survey courses, Informatics Core courses, Informatics Breadth courses, and a focus track in General Informatics, Software, Interactive and Collaborative Technology, or Ubiquitous Computing. All courses must be passed with a grade of B or better.

Survey of Research and Research Methods: Research Methods in Informatics (Informatics 201) and two quarters of Seminar in Informatics (Informatics 209S).

Informatics Core Courses: three courses chosen from: Software Engineering (Informatics 211), Human-Computer Interaction (Informatics 231), Introduction to Ubiquitous Computing (Informatics 241), Social Analysis of Computing (Informatics 261).

Informatics Breadth: two four-unit graduate courses in ICS, CS, or Statistics, outside of Informatics.

Students must choose a track and complete the required courses:

General Informatics Track (GEN)
Electives: six four-unit graduate courses approved by the student's advisor and the Department Chair.

Software Track (SW)
Software electives: three courses from: Formal Specification and Modeling (Informatics 213), Software Analysis and Testing (Informatics 215), Software Processes (Informatics 217), Software Environments (Informatics 219), Software Architecture (Informatics 221), Applied Software Design (Informatics 223), Knowledge-Based User Interfaces (Informatics 233), Advanced User Interface Architecture (Informatics 235), Special Topics (Informatics 295 by Software faculty; no more than two 295s are permitted).

Software Breadth: three graduate courses outside of Software, drawn from a list maintained by the Software faculty.

Interactive and Collaborative Technology Track (ICT)
ICT electives (group 1): two courses chosen from: Computerization, Work, and Organizations (Informatics 263), Theories of Computerization and Information Systems (Informatics 265), Qualitative Research Methods in Information Systems (Informatics 203), Quantitative Research Methods in Information Systems (Informatics 205 or Social Science 201A and 201B).

ICT electives (group 2): two courses chosen from: Knowledge-Based User Interfaces (Informatics 233), Advanced User Interface Architectures (Informatics 235), Computer-Supported Cooperative Work (Informatics 251).

ICT Breadth: two four-unit graduate courses approved by the student's advisor. Students are encouraged, but not required, to take them outside of Informatics.

Ubiquitous Computing Track (UBICOMP)
Additional required courses: Ubiquitous Computing and Interaction (Informatics 242) and Introduction to Embedded and Ubiquitous Systems (Informatics 244).

UBICOMP Breadth: four four-unit graduate courses approved by the student's advisor. Students are encouraged, but not required, to take them outside of Informatics.

Research Project

Each student must find an Informatics faculty advisor and successfully complete a research project with that faculty member by the end of the second year. The research project should be done over at least two quarters of independent study or thesis supervision (Informatics 299 or 298) with that faculty.

Written Assessment

Each student must pass a written assessment. Students in the SW and ICT tracks must pass a written examination (also known as phase II exam) regularly administered by the Department. This examination is based on predetermined reading lists maintained by the SW and ICT faculty, respectively. Students in the UBICOMP and GEN tracks must describe the research project in a publication-quality report, which must be approved by three UBICOMP and Informatics faculty, respectively.

Candidacy Examination

Each student must pass the oral advancement to candidacy examination, which assesses the student's ability to conduct, present, and orally defend research work at the doctoral level. The candidacy committee will consist of five faculty members, the majority of whom must be members of the student's program, and the examination is conducted in accordance with UCI Senate regulations. The student must complete the course requirements, complete the research project, and pass the written assessment prior to advancing to candidacy. The oral candidacy examination consists of a research presentation by the student, followed by questions from the candidacy committee.

Students in the UBICOMP and GEN tracks, additionally to questions about the presented research will also be asked questions about a predetermined list of papers. In the case of UBICOMP, that list is maintained by the UBICOMP faculty; in the case of GEN, that list is to be determined by the student's committee.

Dissertation Topic Defense

The student must present a substantial written document representing the student's dissertation plan. This document must include the proposed dissertation abstract, a dissertation outline, a comprehensive survey of related work, and a detailed plan for completing the work. The dissertation plan is presented by the student to the dissertation committee, who must unanimously approve the student's proposal. The dissertation defense committee is formed in accordance with UCI Senate regulations.

Doctoral Dissertation and Final Examination

The student is required to complete a doctoral dissertation in accordance with Academic Senate regulations. In addition, the student must pass an oral thesis defense which consists of a public presentation of the student's research followed by an oral examination by the student's doctoral committee. The thesis must be approved unanimously by the committee.

CONCENTRATION IN INFORMATICS IN BIOLOGY AND MEDICINE (IBAM)

Biology and medicine have become data-intensive information sciences. Massive data acquisition technologies, such as genome sequencing, high-throughput drug screening, and DNA arrays, generate biological information in quantities that overwhelm conventional approaches. Cost-effective health care and quality medical decision-making require integrating large amounts of up-to-date information and knowledge. Biological systems have also inspired computer science advances with new concepts, including genetic algorithms, artificial neural networks, computer

viruses and synthetic immune systems, DNA computing, artificial life, and hybrid VLSI-DNA gene chips. New computational opportunities such as these create a critical need for theoretical and algorithmic advances in storing, retrieving, networking, processing, analyzing, and visualizing biomedical information.

Informatics in Biology and Medicine is an interdisciplinary concentration at the interface between computer sciences, biological sciences, and medicine. It addresses problems that are specific to the information technologies in biology, medicine, and health care. Research topics include gene finding, protein structure and function prediction, structural and functional genomics, proteomics, electronic patient record systems, medical decision support systems, guideline-based health care, medical information access, and human-computer interfaces for medical applications. To make advances in these areas, society needs people with knowledge and skills that bridge those taught in conventional biological, medical, and computer science curricula. This area provides for such an interdisciplinary computer science education.

Background: Students should have already taken at least one undergraduate course in basic biology, or must make up that deficit during their first year with one of these courses: From Organisms to Ecosystems (Biological Sciences 94), Biochemistry (Biological Sciences 98), Molecular Biology (Biological Sciences 99), Developmental Biology (Biological Sciences D104), Human Physiology (Biological Sciences E109).

Required Courses

The following courses must be completed with a grade of B or better: Seminar in Research in ICS (ICS 200); one course in Theory selected from: Fundamentals of the Design and Analysis of Algorithms (CS 260), Data Structures (CS 261), or Analysis of Algorithms (CS 263); one course in Architecture/CAD/Hardware selected from: Introduction to Embedded and Ubiquitous Systems (CS 244/Informatics 244), Computer Systems Architectures and Languages (CS 250A), Computer Networks (CS 232), or Introduction to Computer Design (CS 252); one course in Software and Systems selected from: Human-Computer Interaction (Informatics 231), Compiler Construction (CS 241), Principles of Data Management (CS 222), Software Engineering (Informatics 211), or Distributed Computer Systems (CS230); Introduction to Medical Informatics (CS 208); Representations and Algorithms for Molecular Biology (CS 284A); at least three quarters of Seminar in Informatics in Biology and Medicine (CS 289S); four courses from: Human-Computer Interaction (Informatics 231), Knowledge-Based User Interfaces (Informatics 233), Information Retrieval, Filtering, and Classification (CS 221), Advanced Topics in Data Management (CS 224), Advanced User Interface Architectures (Informatics 235), Computerization, Work, and Organizations (Informatics 263), Computational Geometry (CS 266), Machine Learning (CS 273A), Probabilistic Learning: Theory and Algorithms (CS 274A), Network-Based Reasoning/ Belief Networks (CS 276), Neural Networks (CS 281), Cognitive and Computational Neuroscience (CS 283), Probabilistic Modeling of Biological Data (CS 284B), Data Mining (CS 285), special topics taught by one of the faculty in this area (CS 280; only one 280 course counts toward the advanced topics requirement) (for M.S. students pursuing the thesis option, two of the four courses must be substituted with two four-unit courses in Thesis Supervision, CS 298 or Informatics 298); two courses from: Systems, Anatomy, and Physiology I (Engineering 210A), Environmental Health Sciences III: Biostatistics and Epidemiology (Environmental Analysis and Design E226), Decision Analysis (Management 283), Molecular Evolutionary Methods (Ecology and Evolutionary Biology 251), Problems in Genomic Analysis (Biological Chemistry 204), Structure and Biosynthesis of Nucleic Acids (Molecular Biology and Biochemistry 203), Structure and Biosynthesis of Proteins (Molecular Biology and Biochemistry 204), Macromolecular Structure, Function, and Interaction (Molecular Biology and Biochemistry 240), Cellular and Molecular Neuroscience (Physiology and Biophysics 202); upon petition, an undergraduate course may be substituted for one of the above interdisciplinary graduate-level courses.

Additional Requirements for the Ph.D. Degree

Each student must write a survey paper and a research paper of publishable quality and pass a comprehensive examination prior to advancing to candidacy.