Berkeley EECS is the original Electrical Engineering and Computer Science department, paving the way for future visionaries and enabling massive progress in these areas. It is, without question, the best school for these disciplines in the entire world. There are many reasons to think seriously about UC Berkeley. It is one of the most distinguished institutions of higher learning, with a leading EECS department, a world-renowned faculty, a strong commitment to excellence in undergraduate education, and a beautiful campus situated opposite the Golden Gate Bridge near the San Francisco Bay. We are also a short distance from Silicon Valley, and a number of high-tech companies are also based in the Berkeley and Alameda areas. This close proximity to the latest technologies enlivens our curriculum, provides many research and summer job opportunities for our students, and makes this a very exciting place to study electrical engineering and computer sciences.

There is, and will continue to be, a high demand for EE and CS engineers. Due to the rapid pace of change, Berkeley’s academic program is flexible and emphasizes fundamentals. You will use up-to-date undergraduate computer and laboratory facilities. Distinguished teachers from the Berkeley campus will be your lecturers, advisors, and mentors. You can participate in undergraduate research projects. Engineers usually work in teams, so we also encourage our students to take courses to sharpen their communication skills. The impact of Berkeley research on the practical end of computer science has been significant. During the 1970s, theoretical research led by Professors R. A. Karp and S. A. Cook established fundamental concepts and limits of computational complexity. Former student Steve Wozniak co-founded Apple Computer with Steve Jobs. Berkeley faculty and students, led by Profs. R. Fabry and D. Ferrari, obtained source code and rights to the early Bell Labs UNIX operating system, and added networking features and virtual memory support for the DEC VAX. Berkeley UNIX on VAX became the standard for DARPA researchers of this period. The INGRES database system, developed by Professors M. Stonebraker and E. Wong, established the feasibility of implementing the relational data model on small computers. Berkeley INGRES was the first complete implementation of a relational database management system.

Innovation accelerated in the 1980s. Berkeley UNIX, including the Internet’s TCP/IP protocol suite, was publicly released as BSD 4.2. The work on computer-aided design broke new ground with demonstrations of design synthesis from logic specifications, producing chip designs that are “correct by construction.” Yet there also were many new activities and achievements.

The development of Reduced Instruction Set computers by David Patterson and Carlo Sequin, the Redundant Array of Inexpensive Disks project led by Randy Katz and David Patterson, and the INGRES relational database system led by Mike Stonebraker, Larry Rowe and Eugene Wong, can be directly connected to multi-billion dollar industries. In the area of system software, the impact of Berkeley Unix on minicomputers and subsequently on workstations and, through LINUX, on personal computers, is self-evident. Nor can we forget the role of Berkeley alumni in sparking the workstation and personal computer industry—pioneers such as Butler Lampson (Xerox PARC), Bill Joy (Sun), and Steve Wozniak (Apple). Numerical computations would not have been reliable had it not been for adoption of the IEEE 754 floating point standard, largely due to William Kahan, who received a Turing Award in 1989 for this work. In the area of programming languages and software engineering, Berkeley research has been noted for its flair for combining theory and practice.

UC Berkeley led the development of computational complexity theory with the foundational work of Richard Karp who showed the hardness of well-known algorithmic problems, such as finding the minimum cost tour for a traveling salesperson, could be related to NP-completeness—a concept proposed earlier by former Berkeley mathematics professor Stephen A. Cook. The resulting P vs. NP question has since been accepted as one of the ten most important open problems in mathematics, along with such classics as the Riemann Hypothesis. Berkeley computer scientists continue to lead the field of computational complexity, with work such as that on probabilistically checkable proofs and the hardness of approximation problems by Sanjeev Arora and Madhu Sudan in the early 1990s, and on quantum complexity theory by Ethan Bernstein and Umesh Vazirani a few years later. Two Turing Awards (Richard Karp, Manuel Blum) and four ACM Ph.D. Dissertation Awards (Eric Bach, Noam Nisan, Madhu Sudan, and Sanjeev Arora) are just a few of the honors garnered by the research in theoretical computer science at Berkeley.

Berkeley’s AI effort grew largely in the 1980s and 1990s, at a time when problems with this paradigm were becoming evident, and researchers at Berkeley played a major role in developing the new, more probabilistic and learning-oriented AI. This new synthesis brought traditional AI together with control theory, pattern recognition, neural networks, and statistical learning theory. Stuart Russell and Peter Norvig’s bestselling textbook has become the canonical exemplar of this synthesis, and research at Berkeley in fields such as vision, robotics and learning is bringing us ever closer to the dream of truly intelligent machines.