Image of the approximate predictive distribution given by variational inference at different stages of the algorithm.

THE DESIGNATED EMPHASIS IN COMMUNICATION, COMPUTATION AND STATISTICS

What is the DE?
Requirements for Admission | Petition for Admission | Coursework | Examination and Dissertation Requirements
Degree Conferral | Participating Faculty | Contacts


What is the DE in Communication, Computation and Statistics?

The Designated Emphasis (DE) in Communication, Computation and Statistics provides an academic structure for an interdisciplinary exchange of ideas. Many of the most significant developments in modern information technology---including communication and data networks, multimedia information processing, and large-scale, distributed data analysis in science, engineering and commerce---are no longer the province of a single academic field, but draw on ideas from diverse sources in computer science, electrical engineering and statistics. The DE in Communication, Computation and Statistics enables specialized, multi-disciplinary training and research opportunities in various emerging areas of information technology. Admitted students not only participate in a cutting-edge program and receive explicit recognition of specialization in the Designated Emphasis but are also well positioned to compete for the most desirable jobs in information technology, both in academia and in industry.

Requirements for Admission

To be admitted to the Designated Emphasis in Communication, Computation and Statistics, an applicant must already be accepted into a PhD program at the University of California, Berkeley. The candidate must also submit a petition for admission prior to taking the Qualifying Examination, after one year of study in his or her home department, and preferably in the second year of his or her graduate training. The petition for admission must be accompanied by a letter of recommendation from a sponsoring faculty member (e.g., the student's advisor), a personal statement, a Curriculum Vitae, and copies of transcripts. The petition for admission must be signed by the sponsoring faculty member before submission to the Graduate Student Services Advisor.

Coursework

One of the principal goals of the designated emphasis is to provide students with a broad education in communications, computation and statistics. Students are required to take at least two breadth courses outside of their home department. Students in EECS choose two courses from a list of courses in Statistics, students in Statistics choose two courses from a list of courses in EECS, and students in other departments choose one course from each of these two lists.

A student in EECS must choose two breadth courses from the following list, and a student in a department other than EECS or Statistics must choose one breadth courses from the following list:

Stat 204 (Probability for Applications)
Stat 205A (Probability Theory)
Stat 205B (Probability Theory)
Stat 206A (Stochastic Processes)
Stat 206B (Stochastic Processes)
Stat 210A (Theoretical Statistics)
Stat 210B (Theoretical Statistics)
Stat 215A (Statistical Models: Theory and Application)
Stat 215B (Statistical Models: Theory and Application)
Stat 230A (Linear Models)
Stat 232 (Experimental Design)
Stat 236 (Analysis of Discrete Observations)
Stat 238 (Bayesian Statistics)
Stat 240 (Nonparametric and Robust Methods)
Stat 241A (Statistical Learning Theory)
Stat 241B (Advanced Topics in Learning and Decision-Making)
Stat 248 (Analysis of Time Series)
Stat 260 (Topics in Probability and Statistics)

A student in Statistics must choose two breadth courses from the following list, and a student in a department other than EECS or Statistics must choose one breadth courses from the following list:

EE 221A (Linear System Theory)
EE 221B (Multivariable Feedback Systems)
EE 222 (Nonlinear Systems--Analysis, Stability and Control)
EE 223 (Stochastic Systems: Estimation and Control)
EE 224A (Digital Communication)
EE 225A (Digital Signal Processing)
EE 225B (Digital Image Processing)
EE 225D (Audio Signal Processing in Humans and Machines)
EE 226A (Random Processes in Systems )
EE 227A (Introduction to Convex Optimization)
EE 227B (Convex Optimization and Approximation)
EE 228A (High Speed Communications Networks)
EE 228B (Communication Networks )
EE 229 (Information Theory and Coding)
EE 291 (Communication Networks )
EE 291 (Control and Optimization of Distributed Parameters...)
CS 270 (Combinatorial Algorithms and Data Structures)
CS 271 (Randomness and Computation)
CS 280 (Computer Vision)
CS 281A (Statistical Learning Theory)
CS 281B (Advanced Topics in Learning and Decision-Making)
CS 288 (Statistical Natural Language Processing)
CS 289 (Knowledge Representation and Use in Computers)

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Examination and Dissertation Requirements

The Designated Emphasis will be satisfied in the qualifying examination by the designation of communication, computation and statistics as substantive areas of interrogation. The qualifying examination committee must include a member of the Designated Emphasis Group who may represent either the home department of the student or another discipline. The qualifying examination committee must include an Academic Senate member from outside the student's home department. Satisfactory performance on the qualifying examination for the doctorate will be judged independently from performance in the Designated Emphasis.

One member of the Designated Emphasis Group must serve on the dissertation committee and insure that the thesis contributes to the interdisciplinary study of communication, computation and statistics in a significant way. The dissertation committee must include an Academic Senate member from outside the student's home department.

Degree Conferral

Upon successful completion of the dissertation, the student's transcript and diploma will include the designation: "PhD in X with a Designated Emphasis in Communication, Computation and Statistics." This designation certifies that he or she has participated in, and successfully completed, a Designated Emphasis in addition to the departmental requirements for the PhD.

Participating Faculty

Pieter Abbeel - Electrical Engineering and Computer Sciences
David Aldous - Statistics
Venkat Anantharam - Electrical Engineering and Computer Sciences
Peter Bartlett - Electrical Engineering and Computer Sciences and Statistics
Alexandre Bayen - Civil and Environmental Engineering
Peter Bickel - Statistics
John Canny - Electrical Engineering and Computer Sciences
Laurent El Ghaoui - Electrical Engineering and Computer Sciences
Noureddine El Karoui - Statistics
Jerome Feldman - Electrical Engineering and Computer Sciences
Michael Gastpar - Electrical Engineering and Computer Sciences
Adityanand Guntuboyina - Statistics
Michael Jordan - Electrical Engineering and Computer Sciences and Statistics
Dan Klein - Electrical Engineering and Computer Sciences
Edward Lee - Electrical Engineering and Computer Sciences
Jitendra Malik - Electrical Engineering and Computer Sciences
Nelson Morgan - Electrical Engineering and Computer Sciences
Kannan Ramchandran - Electrical Engineering and Computer Sciences
John Rice - Statistics
Stuart Russell - Electrical Engineering and Computer Sciences
Anant Sahai - Electrical Engineering and Computer Sciences
Shankar Sastry - Electrical Engineering and Computer Sciences
Alistair Sinclair - Electrical Engineering and Computer Sciences
Claire Tomlin - Electrical Engineering and Computer Sciences
David Tse - Electrical Engineering and Computer Sciences
Pravin Varaiya - Electrical Engineering and Computer Sciences
Martin Wainwright - Electrical Engineering and Computer Sciences and Statistics
Bin Yu - Statistics
Avideh Zakhor - Electrical Engineering and Computer Sciences

Contacts

CS grad students should contact the CS Graduate Student Services Advisor:
Xuan Quach: Room 339 Soda Hall, xuquach@cs, (510) 642-9413.

EE grad students should contact the EE Graduate Student Services Advisor:
Shirley Salanio: Room 215 Cory Hall, shirley@eecs (510) 643-8347.

I School grad students should contact the I School Student Services Advisor:
Meg St. John: Room 111 South Hall, meg@ischool, (510) 642-1465.

Statistics grad students should contact the Statistics Graduate Student Services Advisor:
La Shana Porlaris: Room 373 Evans Hall, sao@stat, (510) 642-5361.

Students from other departments please contact us at: .

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Questions/Comments?
© 2004 EECS Department, University of California, Berkeley