The goals of our program are ambitious: we aim to provide a broad and deep understanding of mathematical issues in the information sciences.
The variety of topics covered in the courses that make up the degree program require expertise in a wide selection of subject disciplines; by utilizing the resources of several departments in teaching the courses, we hope to give the students the best possible introduction to mathematical and information sciences.
Curious where students go after graduating with a degree in Mathematical & Computational Science? Check out our students' post-graduation plans
The B.S. in Mathematical and Computational Science is an interdisciplinary undergraduate program designed as a major for students interested in the mathematical sciences, or in the use of mathematical ideas and analysis of problems in the social or management sciences. It provides a core of mathematics basic to all mathematical sciences and an introduction to the concepts and techniques of the following:
It also provides an opportunity for elective work in any of the mathematical science disciplines at Stanford.
Undeclared students looking for an introduction to MCS may take Data Science 101 (STATS 101) prior to taking any of the required Statistics core courses. If the MCS major is declared, STATS 101 may be used for elective credit toward the major.
The program utilizes the faculty and courses of the departments of Computer Science, Mathematics, Management Science and Engineering, and Statistics.
It prepares students for graduate study or employment in the mathematical and computational sciences or in those areas of applied mathematics which center around the use of computers and are concerned with the problems of the social and management sciences.
In 1971, four professors -- Rupert Miller from Statistics, Arthur Veinott, Jr. from Operations Research, John Herriot from Computer Science, and Paul Berg from Mathematics -- created an interdisciplinary group to meet the need of having an undergraduate program for students interested in applied math.