Just a picture of Rhodes Hall.

  


Welcome to CAM!

The Center for Applied Mathematics (CAM) administers the graduate Field of Applied Mathematics. Graduate education is a vital function at Cornell University. From the student's point of view, the Applied Mathematics graduate program offers not only the opportunity to work at a major university, but flexibility and accommodation to individual needs and interests. Applied Mathematics is one of the most diverse graduate fields; the range of possibilities of graduate research encompasses the areas of specialization of all the faculty members in the field, who currently number more than eighty. As a Cornell graduate student in applied mathematics, you will find a culture of respect and trust and a collegial atmosphere in which to study and that encourages you to excel. To apply to our program, see details here.

Some CAM student work interests:

Coupled cell neural models for locomotion
My research involves modeling the neuronal networks in the rodent spinal cord that are responsible for generating the basic rhythmic patterns of walking, such as left-right limb alternation. The approach I use is to model the neurons and their synaptic connections as coupled cells of ODEs. Working with neurobiologists in the Harris-Warrick lab group, I'm working to develop models that accurately describe the biophysical properties of the real neurons and the architecture of the real network in the spinal cord. Analysis of these models should give insight into what features of the models' dynamics are due to the intrinsic properties of individual neurons and which ones arise from the network connectivity. To perform the analysis, we're developing new software and algorithms for numerical simulation and bifurcation analysis of coupled cell systems with multiple time scales.

  - Erik Sherwood

Neural models and multiple time scales
My research involves developing and analyzing models of neurons from a multiple time scale point of view. The models are ordinary differential equations, to which we apply the tools of geometric singular perturbation theory. The application is to neurons involved with breathing. By splitting the system into fast and slow subsystems and looking at bifurcations in these subsystems, we can gain insight into mechanisms underlying changes in firing patterns. I also hope to develop parameter optimization algorithms which take advantage of the fast-slow structure.

  - Joe Tien
About Us | Site Map | Contact Us | ©2005 Center for Applied Mathematics