- Strong preparation in mathematics: Linear Algebra, Numerical Linear Algebra, Vector Calculus.
- Strong preparation in probability and statistics: Basic Probability Theory, Graphical Probabilistic Models (Bayesian networks).
- Strong programming background and experience in C++, JAVA, Lisp, MATLAB, Mathematica, or R/SPlus as well as knowledge of advanced data structures.
- Experience with optimization algorithms: Linear and quadratic programming, convex optimization, gradient descent search and the conjugate-gradient method, Newton's method, etc.
- Other useful background includes image processing, computer graphics, computational geometry, geographic information systems, database systems.

Prospective students interested in a research assistantship should email me a letter that describes their background, experience, and research goals. Please also include a list of the courses you have taken (and grades received) and a resume. Attach copies of any papers that you have published in English.