Letter from the Chair

Dear Prospective Graduate Student: 

The University of California at Berkeley has been at the forefront of research in Statistics and Probability since the founding of the original Statistical Laboratory by Jerzy Neyman in 1938. While maintaining our core strengths in probability and statistics, we have continued to grow and evolve: Our faculty contribute prominently to a broad array of fields in which probability and statistics are useful, in many cases revolutionizing practice. (See the department research pages and the websites of individual faculty, who work on applications such as AIDS, algebra, algebraic geometry, algorithms, animal movement, artificial intelligence, astronomy, astrophysics, biodemography, bioinformatics, biostatistics, causal inference, climate, clinical trials, combinatorial optimization, combinatorics, computational biology, computational phylogeny, computer vision, demography, earthquakes, ecology, elections, epidemiology, evolution, experimental design, finance, fMRI, forestry, game theory, genetics, genomics, geophysics, graphs, ..., and the rest of the alphabet.) As computational resources grow, as barriers between disciplines erode, as "Big Data" becomes the norm, and as more and more fields become data-driven, opportunities for probabilists and statisticians grow: Virtually every scientific field and every industry recognizes the need for and advantages of statistical approaches to their problems. This is the golden age of Statistics and Probability. 

The Ph.D. program in Statistics provides a broad background in probability theory and in applied and theoretical statistics. We also offer three "Designated Emphasis" (DE) tracks, the graduate school analog of a "minor": Communication and Computation, Computational and Genomic Biology, and Computational Science and Engineering.

The DE in Statistics with Communication and Computation provides a framework that unifies probability and statistics, information theory, control theory, signal processing, optimization theory, and artificial intelligence. This new discipline is crucial for research in modern information technology, especially in communication and data networks, multimedia transport and presentation, and large-scale, distributed data analysis in science, engineering and commerce. The department has close ties to the Simons Institute for the Theory of Computing and the Department of Electrical Engineering and Computer Science.

The DE in Statistics with Computational and Genomic Biology prepares students to add to the astonishing recent advances in genomics and molecular biology.  In addition to courses in probability and statistics, students in this DE take courses in Molecular and Cell Biology, Computer Science and Engineering, Bioengineering, Chemistry, Mathematics, or other areas affiliated with Computational and Genomic Biology. Students also receive mentoring and guidance from faculty in these affiliated departments. 

The DE in Computational Science and Engineering (CSE) reflects the fact that dramatic increases in computational power for mathematical modeling and simulation have made scientific computing crucial for the analysis of complex systems, such as computer chip manufacturing, battery modeling, turbine design, aircraft prototype testing, climate change and star formation, to name a few. "Big Data" is another compelling problem: radio telescopes, DNA sequencers, particle accelerators, sensor networks, social networks and the Internet all collect more data than humans can analyze and understand. Statistics, including machine learning and data visualization, are needed to extract useful information from the data. Solutions to these problems share many mathematical, statistical and computational techniques. The CSE program helps educate UC Berkeley students in these common techniques, enabling them to solve CSE problems across a wide range of disciplines through the development and promulgation of numerical and computational tools.

Even within the standard PhD track there are plenty of opportunities for expanding one's studies to encompass other areas. For example, probabilistic thinking is at the core of recent significant advances in a number of disciplines, and these are well-represented on the Berkeley campus both within and outside the Statistics department. Faculty in Electrical Engineering and Computer Science are working in fields such as randomized algorithms and queuing networks, and faculty in Mathematics are working on the boundary between partial differential equations and probability in mathematical physics and hydrodynamics. Several faculty have appointments in Demography, Political Science, or Sociology, and some do work with influence on public policy, from disaster preparedness to elections to healthcare. Students may take courses in many departments at an early stage as an integral part of the program, or have faculty from these departments in their dissertation committees. There are also special connections to the Simons Institute for the Theory of Computing, and to Biostatistics. Students have the resources of the School of Public Health at their disposal and may take courses offered by the School as part of their graduate education, to help foster research skills used in the analysis of data in the health, medical and biological sciences. 

In addition to studying at a world-class institution committed to achieving excellence across disciplines, Berkeley graduate students live and work in one of the most desirable places in the world--the San Francisco Bay Area--with its congenial climate, scenic views, proximity to nature, world-class food and coffee, and diverse cultural riches. I hope you choose to apply to study at our wonderful institution. 

Sincerely yours,


Philip B. Stark

Professor and Chair