**Meeting Times:** Mondays and Wednesdays, 3:00-4:15

**Location:** ES&T L1125

**Instructor:** Edmond Chow

**E-mail:**

**Office Hours:** By appointment

This course will cover many of the major computational methods used
in science and engineering for numerical simulation, inverse problems,
and machine learning. Students will deepen their understanding of
these methods through programming and experimentation. Examples
will be given in Matlab.

**Topics**

- Finite element method
- Fast multipole method
- Bayesian estimation theory
- Gaussian processes and kernel methods
- Numerical optimization
- Electronic structure calculations
- Brownian dynamics simulation

Graduate-level Numerical Linear Algebra (CSE/MATH 6643 and/or CSE/MATH 6644).
Experience with Matlab.

**Grading**

60% Assignments

30% Final project (in-class presentation, final report)

10% Class participation

**Textbook**

There is no textbook for this course. References for resources
will be given in class.