Courses

The PI has developed a course in computational methods on biomolecular modeling [45]. The course covers mathematical, computational, and scientific applications of biomolecular modeling. The enrollment was about half computer science and engineering students and half students of physical sciences, including chemistry, physics, and biology, at both the graduate and senior undergraduate level. This class will be expanded to include more hands-on training for setting simulations for real applications. The collaborations described in this proposal will provide a wealth of possibilities for examples and lab exercises. Another example of the influence of a computational science approach to curriculum development is the core graduate course on scientific computing and numerical methods that I teach every other fall semester. It will include significant examples of applications where all numerical methods considered are used, along with challenges and opportunities for research in those areas. Computational science has influenced even a data structures course for juniors that I taught the past two fall semesters. Some of the students performed significant MD simulations using a novel approach, computing forces directly using topological information about the molecule. Others explored the use of haptic interfaces, and yet others tested new algorithms for kinetic data structures that may be useful in MD.

The PI's undergraduate course on data structures and applied algorithms has enabled the training of numerous undergraduate and graduate TAs, and has permitted a personalized approach to learning with emphasis on individual mentoring and projedct development. At the conclusion of the previous two offerings of this course, students presented their results orally, and submitted written papers that were published both electronically ³ and in written proceedings form by the department.