Scientific Computing

Scientists and engineers rely more than ever on computer modeling and simulation to guide their experimental and design work. The infrastructure that supports this activity depends critically on the development of new numerical algorithms that are reliable, efficient, and scalable. "Large N" is the hallmark of modern, data-intensive scientific computing and it is a common thread that unifies departmental research in numerical linear algebra, optimization, and partial differential equations.

Faculty and Researchers

David Bindel works on simulating microelectromechanical systems, numerical linear algebra, finite element analysis, floating point computation and network tomography. His research involves software design, mathematical analysis and physical modeling.

Doug James works on geometric and physical algorithms for computer animation and interactive and scalable simulation, especially those for fast deformable models. Multi-sensory display of physical systems is a long-term challenge involving real-time algorithms to support graphical display, haptic force-feedback display, and auditory display of complex phenomena.

Charlie Van Loan works in numerical linear and multilinear algebra. A recurring theme in his current research is the development of efficient techniques for matrix problems that involve Kronecker products and multiple symmeties. He has written several texts including Matrix Computations (with Gene Golub), Introduction to Scientific Computing, and Computational Frameworks for the Fast Fourier Transform.

Applied Mathematics

The scientific computing group is also active in the Applied Mathematics Ph.D. program, which is part of Cornell's Center for Applied Mathematics. Prospective Ph.D. applicants interested in the mathematical aspects of scientific computing may wish to consider that graduate field as well.

Related Research

In addition to the core faculty mentioned above, we have several colleagues who work in related areas:

Kavita Bala performs research on scalable graphics for high-complexity scenes. Emphasis is on feature-based graphics, real-time global illumination, perceptually-based rendering, image-based rendering and texturing.

Steve Marschner focuses on high-quality rendering with an emphasis on accurate models for the appearance of everyday materials. Analytical and numerical calculations of light reflection and radiative transport are key elements of his research.

Ramin Zabih applies combinatorial and numerical algorithms to problems in computer vision and medical imaging.