Together with theory and experimentation, computational methods now constitute a third pillar of scientific inquiry. There's no denying the role that technology plays in sustaining scientific leadership and economic competitiveness. Advanced technologies now allow researchers to build and test models of complex phenomena and then manage and analyze almost unimaginably large volumes of data. Stellar explosions, climate shifts, the effects of gene flow on ecological communities, multi-scale earthquake-induced structural stresses, and nuclear fusion cannot be replicated, but they certainly can be simulated.

Computational engineering and science are key to developing models of behavior and modes of scientific discovery that enable significant and often cost-effective progress in solving the grand challenges of our time.

Lehigh researchers use computational modeling to help doctors improve cancer-radiation techniques to limit damage to healthy cells around tumors, and to allow people stricken with immobilizing diseases to control devices through thought recognition. Others seek to gauge the effect of earthquakes on interconnected infrastructure systems, or to understand the diffusion of aluminum and oxygen ions in the manufacture of advanced ceramics. Still others intend to improve the effectiveness of search engines on the Web.

Typical Graduate Programs

Graduate students interested in engineering surrounding the fields of data science and intelligent systems often pursue degrees such as: