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Stanford University
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Computational and Mathematical Engineering
School of Engineering
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  4. Computational And Mathematical Engineering
  5. PhD Minor

PhD Minor

PhD Minor
  • Institute for Computational and Mathematical Engr opens in a new tab
Program Minimum Units
21 Units
University Minimum Units
20 Units
Interests
Data and Information Sciences, Technology
Academic Areas
Engineering & Computer Science, Mathematics & Data Sciences

Overview

At the Institute for Computational & Mathematical Engineering (ICME), we design state-of-the-art mathematical and computational models, methods, and algorithms for engineering and science applications. The program collaborates closely with engineers and scientists in academia and industry to develop improved computational approaches and advance disciplinary fields. In particular, it leverages Stanford’s strength in engineering applications in the physical, biological, mathematical, and information sciences and has established connections with nearly 20 departments across five schools at Stanford.

The program identifies research areas that would benefit from a multidisciplinary approach in which computational mathematics is critical. This multidisciplinary intellectual environment is a core strength of ICME, with interaction among students and faculty with diverse backgrounds and expertise. Students and faculty are active in many research areas: aerodynamics and space applications, fluid dynamics, protein folding, data science, including machine learning and recommender systems, ocean dynamics, climate modeling, reservoir engineering, computer graphics, financial mathematics, and many more.

The program trains students and scholars from across Stanford in mathematical modeling, scientific computing, and advanced computational algorithms at the undergraduate and graduate levels. Courses typically provide strong theoretical foundations for solving real-world problems and numerical computations to facilitate the application of mathematical techniques and theories. Training offered includes matrix computations, computational probability and combinatorial optimization, optimization, stochastics, numerical solution of partial differential equations, parallel computer algorithms, and new computing paradigms.

Requirements

For a PhD minor in Computational and Mathematical Engineering (CME), a doctoral candidate must complete 21 units of approved graduate-level courses.

All courses must be taken for a letter grade and passed with a grade of B or better. Elective courses cannot be cross-listed with the student’s primary department. If a student is concurrently enrolled in a Master's program, there can be no overlap between the MA/MS courses and the PhD minor courses. Minor programs should be developed in close discussion between the student and the student’s primary PhD advisor.

PhD Minor Coursework

Core Courses

Complete all of the following course(s):
CME 302

Numerical Linear Algebra

3 Units
CME 306

Computational Methods of Applied Mathematics

3 Units
CME 307

Optimization

3 Units

Programming requirement

Complete at least 1 of the following courses:
CME 212

Programming for performance

3 Units
CME 213

Introduction to parallel computing using MPI, openMP, and CUDA

3 Units
CS 149

Parallel Computing

3-4 Units
CS 246

Mining Massive Data Sets

3-4 Units
CS 295

Software Engineering

3 Units
CS 315B

Parallel Computing Research Project

3 Units

Electives

Complete at least 3 courses and 9 units from the specialized depth electives list in the Computational and Mathematical Engineering PhD. To petition for a course that is not on this list to count toward the minor, please contact ICME student services.