Computational Science and Engineering
As communication needs and model equations for physical, biological, financial, or social systems have increased in complexity, computer simulation for such applications has evolved into a separate discipline devoted to the science and engineering of computational systems. This field, known as computational science and engineering (CSE) encompasses subdisciplines ranging from computational mathematics and algorithms to visualization and simulation of model equations to studies of communication systems, networking, and processing of digital information.
As a tool for science and engineering, computing has become an integral part of the interpretation of observations. The need for high-fidelity models in fields such as molecular biology, materials science, electrodynamics, and climate dynamics gives rise to model equations in which the number of degrees of freedom is so large that only a computational approach is viable. Computational techniques are also being increasingly used to predict observations or to provide model data where physical probes cannot be used due to cost, safety, or impossibility. Even for systems where no model equations exist, computational techniques are essential. For example, computational combinatorics and pattern recognition play a key role in understanding the human genome, by identifying correlations in the data.
CSE offers an ideal path to interdisciplinary research, where many computational techniques and developments can be transferred between disciplines. The successful scientist and engineer must understand the interplay between a computational system and the real-world phenomenon it models. DAS faculty conduct research in many exciting areas within CSE, both within our own research groups and through collaborations with our partners at Lawrence Berkeley, Lawrence Livermore, and Sandia National Laboratory, each of which house prominent research groups in CSE.