Kyle Camarda, Ph.D.

Kyle Camarda's research focuses mainly on the use of high-performance computers to solve optimization problems in product design, process design and bioinformatics. In the search for new pharmaceuticals, polymers, or fuel additives, the traditional trial-and-error approach is being supplanted by a new technique which uses computers to suggest compounds which are promising before any synthesis or testing is performed. Using this method, called Computational Molecular Design, researchers in this group first aim to predict important properties of novel molecules. Once properties can be predicted, optimization problems are formulated and solved which result in candidate molecules which are likely to have all of the physical property values desired for the new product. Computational molecular design is being applied to the search for new pharmaceutical drug formulations, novel catalytic materials, polymer adhesives, and many other molecular systems. The group is also interested in applying novel optimization techniques, including Tabu search and genetic algorithms, to the flux analysis of metabolic networks, and in parallel computing applied to chemical engineering optimization problems.

A second line of research focuses on the use of new computing and networking technology to improve chemical engineering research and communications. Using the Access Grid Node at the Department of Chemical and Petroleum Engineering at the University of Kansas, researchers in this group use live video and audio conferencing to hold seminars, meetings and discussions over the internet. Camarda is also interested in integrating chemical engineering tools, such as process simulators, within Access Grid technology to allow for multi-site, multi-user design research.