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This archived information is dated to the 2009-10 academic year only and may no longer be current.

For currently applicable policies and information, see the current Stanford Bulletin.

Computer Science

In this section:

Computer Sciences Course Catalog Numbering System

Bachelor of Science in Computer Science

Master of Science in Computer Science

Doctor of Philosophy in Computer Science

Ph.D. Minor in Computer Science

Teaching and Research Assistantships in Computer Science

Overseas Studies Courses in Computer Science

Up one level:

School of Engineering

Emeriti: (Professors) Tom Binford, Edward Feigenbaum, Richard Fikes, Donald E. Knuth,* John McCarthy, Edward J. McCluskey, William F. Miller, Nils J. Nilsson, Vaughan Pratt,* Jeffrey D. Ullman, Gio Wiederhold*

Chair: Jennifer Widom

Associate Chair for Education: Mehran Sahami

Professors: Alex Aiken, Dan Boneh, David Cheriton, William J. Dally, David Dill, Hector Garcia-Molina, Leonidas J. Guibas, Patrick Hanrahan, John Hennessy, Mark A. Horowitz, Oussama Khatib, Daphne Koller, Monica Lam, Jean-Claude Latombe, Marc Levoy, Zohar Manna, Teresa Meng, John Mitchell, Kunle Olukotun, Yoav Shoham, Sebastian Thrun, Jennifer Widom, Terry Winograd

Associate Professors: Serafim Batzoglou, Dawson Engler, Ronald P. Fedkiw, Michael Genesereth, Christoforos Kozyrakis, Christopher Manning, David Mazieres, Nick McKeown, Andrew Ng, Serge A. Plotkin, Balaji Prabhakar, Mendel Rosenblum

Assistant Professors: Gill Bejerano, Jeffrey Heer, Sachin Katti, Scott Klemmer, Vladlen Koltun, Jure Leskovec, Philip Levis, Fei-Fei Li, Tim Roughgarden

Professors (Research): John Ousterhout, John K. Salisbury

Professor (Teaching): Eric S. Roberts

Associate Professor (Teaching): Mehran Sahami

Courtesy Professors: Russ Altman, Martin Fischer, Bernd Girod, Michael Levitt, Clifford J. Nass, Roy Pea, Fouad A. Tobagi

Courtesy Associate Professors: Ashish Goel, Dan Jurafsky, Vijay Pande, Benjamin Van Roy

Courtesy Assistant Professors: Paulo Blikstein, Atul Butte, Ramesh Johari, Ge Wang

Lecturers: Gerald Cain, Nicholas J. Parlante, Robert Plummer, Patrick Young, Julie Zelenski

Consulting Professors: Gary Bradski, Kathleen Fisher, Prabhakar Raghavan

Consulting Associate Professor: Federico Barbagli, Pei Cao

Consulting Assistant Professors: Kurt Akeley

Visiting Professor: Martin Abadi

* Recalled to active duty.

Mail Code: 94305-9025

Phone: (650) 723-2273

Web Site: http:// www.cs.stanford.edu

Courses offered by the Department of Computer Science are listed under the subject code CS on the Stanford Bulletin's ExploreCourses web site.

The Department of Computer Science (CS) operates and supports computing facilities for departmental education, research, and administration needs. All CS students have access to the departmental student machine for general use (mail, news, etc.), as well as computer labs with public workstations located in the Gates Building. In addition, most students have access to systems located in their research areas.

Each research group in Computer Science has systems specific to its research needs. These systems include workstations (PCs, Macs), multi-CPU computer clusters, and local mail and file servers. Servers and workstations running Linux or various versions of Windows are commonplace. Support for course work and instruction is provided on systems available through Information Technology Services (ITS) and the School of Engineering (SoE).

Mission of the Undergraduate Program in Computer Science

The mission of the undergraduate program in Computer Science is to develop students' breadth of knowledge across the subject areas of computer sciences, including their ability to apply the defining processes of computer science theory, abstraction, design, and implementation to solve problems in the discipline. Students take a set of core courses. After learning the essential programming techniques and the mathematical foundations of computer science, students take courses in areas such as programming techniques, automata and complexity theory, systems programming, computer architecture, analysis of algorithms, artificial intelligence, and applications. The program prepares students for careers in government, law, and the corporate sector, and for graduate study.

Learning Outcomes

The department expects undergraduate majors in the program to be able to demonstrate the following learning outcomes. These learning outcomes are used in evaluating students and the department's undergraduate program. Students are expected to be able:

  1. to apply the knowledge of mathematics, science, and engineering.
  2. to design and conduct experiments, as well to analyze and interpret data.
  3. to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability.
  4. to function on multidisciplinary teams.
  5. to identify, formulate, and solve engineering problems.
  6. to understand professional and ethical responsibility.
  7. to communicate effectively.
  8. to understand the impact of engineering solutions in a global, economic, environmental, and societal context.
  9. to demonstrate a working knowledge of contemporary issues.
  10. to apply the techniques, skills, and modern engineering tools necessary for engineering practice.
  11. to transition from engineering concepts and theory to real engineering application.

Graduate Programs in Computer Science

The University's basic requirements for the M.S. and Ph.D. degrees are discussed in the "Graduate Degrees" section of this bulletin.

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