Jim Burke, Dima Drusvyatskiy, Thomas Rothvoss, Rekha Thomas
The program will depend on whether the focus is continuous or discrete optimization, as indicated.
| First Year | |||
|---|---|---|---|
| 554 | 555 | 556 | Linear Analysis (Continuous and discrete optimization) |
| 504 | 505 | 506 | Modern Algebra (Discrete optimization) |
| 514 | 516 | Optimization | |
Affiliated Faculty: Ioana Dimitriu (Math), Maryam Fazel (EE), Mehran Mesbahi (AA), and Hari Narayanan (Math)
Of the core courses, linear analysis is the one that should definitely be taken by all optimization students. Modern Algebra should be taken by students interested in discrete optimization. The choice of other core courses and which year to take them depends on the interests and career goals of the student. The choice of courses should be made in consultation with a prospective advisor.
All optimization students must develop proficiency in at least one programming language and should develop some expertise in numerical linear algebra. In addition, students should have some knowledge of data analysis and statistical inference.
We encourage all optimization students to take applied courses in Statistics, Applied Math, Engineering, and Computer Science.
Internships in industry or research labs are strongly encouraged.
For information about the research interests of the optimization faculty, visit their home pages:
