Communication, Computation, and Statistics

University of California, Berkeley

About the Program

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.

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Admissions

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 adviser), 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 adviser.

For further information regarding admission to graduate programs at UC Berkeley, please see the Graduate Division's Admissions website.

Designated Emphasis Requirements

Curriculum

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 204Probability for Applications4
STAT C205AProbability Theory4
STAT C205BProbability Theory4
STAT C206AAdvanced Topics in Probability and Stochastic Process3
STAT C206BAdvanced Topics in Probability and Stochastic Processes3
STAT 210ATheoretical Statistics4
STAT 210BTheoretical Statistics4
STAT 215AStatistical Models: Theory and Application4
STAT 215BStatistical Models: Theory and Application4
STAT 230ALinear Models4
STAT 232Experimental Design4
STAT 240Nonparametric and Robust Methods4
STAT C241AStatistical Learning Theory3
STAT C241BAdvanced Topics in Learning and Decision Making3
STAT 248Analysis of Time Series4
STAT 260Topics in Probability and Statistics3

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:

EL ENG 221ALinear System Theory4
EL ENG 222Nonlinear Systems--Analysis, Stability and Control3
EL ENG 223Stochastic Systems: Estimation and Control3
EL ENG 224ADigital Communications4
EL ENG 225ADigital Signal Processing3
EL ENG 225BDigital Image Processing3
EL ENG 225DAudio Signal Processing in Humans and Machines3
EL ENG 226ARandom Processes in Systems4
EL ENG 227ATCourse Not Available4
EL ENG 227BTConvex Optimization4
EL ENG 228AHigh Speed Communications Networks3
EL ENG 229AInformation Theory and Coding3
EL ENG 229BError Control Coding3
EL ENG C291Control and Optimization of Distributed Parameters Systems3
EL ENG C291EHybrid Systems and Intelligent Control3
COMPSCI 270Combinatorial Algorithms and Data Structures3
COMPSCI 271Randomness and Computation3
COMPSCI C280Computer Vision3
COMPSCI C281AStatistical Learning Theory3
COMPSCI C281BAdvanced Topics in Learning and Decision Making3
COMPSCI 288Natural Language Processing4
COMPSCI 289AIntroduction to Machine Learning4

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.

Faculty and Instructors

Faculty

Pieter Abbeel, Associate Professor. Artificial Intelligence (AI); Control, Intelligent Systems, and Robotics (CIR); Machine Learning.
Research Profile

David Aldous, Professor. Mathematical probability, applied probability, analysis of algorithms, phylogenetic trees, complex networks, random networks, entropy, spatial networks.
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Venkat Anantharam, Professor. Communications & Networking (COMNET); Artificial Intelligence (AI); Control, Intelligent Systems, and Robotics (CIR); Security (SEC); Signal Processing (SP).
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Peter L. Bartlett, Professor. Statistics, machine learning, statistical learning theory, adaptive control.
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Alexandre M. Bayen, Professor. Transportation, modelling and control of distributed parameters systems, large scale infrastructure systems, water distribution.
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John Canny, Professor. Computer science, activity-based computing, livenotes, mechatronic devices, flexonics.
Research Profile

Laurent El Ghaoui, Professor. Decision-making under uncertainty, convex optimization, robust solutions, semidefinite programming, exhaustive simulation.
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Noureddine El Karoui, Associate Professor. Applied statistics, theory and applications of random matrices, large dimensional covariance estimation and properties of covariance matrices, connections with mathematical finance.
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Adityanand Guntuboyina, Assistant Professor.

Michael I. Jordan, Professor. Computer science, artificial intelligence, bioinformatics, statistics, machine learning, electrical engineering, applied statistics, optimization.
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Daniel Klein, Professor. Artificial Intelligence (AI); Natural Language Processing, Computational Linguistics, Machine Learning.
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Robert C. Leachman, Professor. Logistics, manufacturing, semiconductors, scheduling, supply chain systems, dynamic production models, production planning and scheduling.
Research Profile

Edward A. Lee, Professor. Embedded Software, Real-Time Systems, Cyber-Physical Systems, Concurrency; Design, Modeling and Analysis (DMA); Programming Systems (PS);Signal Processing (SP).
Research Profile

Jitendra Malik, Professor. Artificial Intelligence (AI); Biosystems & Computational Biology (BIO); Control, Intelligent Systems, and Robotics (CIR); Graphics (GR); Human-Computer Interaction (HCI); Signal Processing (SP);.
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Kannan Ramchandran, Professor. Communications & Networking (COMNET); Signal Processing (SP); Control, Intelligent Systems, and Robotics (CIR).
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Benjamin Recht, Associate Professor. Control, Intelligent Systems, and Robotics (CIR); Signal Processing (SP); Machine Learning (ML); Optimization (OPT).

Stuart Russell, Professor. Artificial intelligence, computational biology, algorithms, machine learning, real-time decision-making, probabilistic reasoning.
Research Profile

Anant Sahai, Associate Professor. Communications & Networking (COMNET), Information Theory, Cognitive Radio and Spectrum Sharing; Control, Intelligent Systems, and Robotics (CIR), Distributed and Networked Control; Signal Processing (SP); Theory (THY), Information Theory.
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S. Shankar Sastry, Professor. Computer science, robotics, arial robots, cybersecurity, cyber defense, homeland defense, nonholonomic systems, control of hybrid systems, sensor networks, interactive visualization, robotic telesurgery, rapid prototyping.
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Alistair Sinclair, Professor. Theory (THY); Randomized algorithms; applied probability; statistical physics.
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Claire Tomlin, Professor. Control, Intelligent Systems, and Robotics (CIR); Biosystems & Computational Biology (BIO); Control theory; hybrid and embedded systems; biological cell networks.
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Martin Wainwright, Professor. Statistical machine learning, High-dimensional statistics, information theory, Optimization and algorithmss.
Research Profile

Bin Yu, Professor. Neuroscience, remote sensing, networks, statistical machine learning, high-dimensional inference, massive data problems, document summarization.
Research Profile

Avideh Zakhor, Professor. Signal Processing (SP); Artificial Intelligence (AI); Control, Intelligent Systems, and Robotics (CIR); Graphics (GR).
Research Profile

Emeritus Faculty

Peter J. Bickel, Professor Emeritus. Statistics, machine learning, semiparametric models, asymptotic theory, hidden Markov models, applications to molecular biology.
Research Profile

Jerome A. Feldman, Professor Emeritus. Artificial Intelligence (AI); Biosystems & Computational Biology (BIO); Security (SEC); cognitive science.
Research Profile

Nelson Morgan, Professor Emeritus. Signal Processing (SP).

John A. Rice, Professor Emeritus. Transportation, astronomy, statistics, functional data analysis, time series analysis.
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Pravin Varaiya, Professor Emeritus. Communications & Networking (COMNET); Control, Intelligent Systems, and Robotics (CIR); Energy (ENE); Control; Networks; Power systems; Transportation.

Contact Information

Graduate Group in Communication, Computation, and Statistics

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Director of Graduate Matters, EECS

Shirley Salanio

217 Cory Hall

Phone: 510-643-8347

shirley@eecs.berkeley.edu

Graduate Student Services Adviser, Computer Science

Audrey Sillers

367 Soda Hall

Phone: 510-642-9413

araya@eecs.berkeley.edu

Director of Student Services, School of Information

Siu Yung Wong

104 South Hall

Phone: 510-664-7092

siu@ischool.berkeley.edu

Graduate Student Services Adviser, Statistics

La Shana Polaris

373 Evans Hall

Phone: 510-642-5361

sao@stat.berkeley.edu

Graduate Student Services Officer for Students in Other Departments

de-ccs-staff@eecs.berkeley.edu

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