About the School of Computational Science & Engineering
What is Computational Science & Engineering?
Computational Science and Engineering (CSE) is a discipline devoted to the systematic study, creation and application of computer-based models to understand and analyze natural and engineered systems. CSE is inherently interdisciplinary, with close ties to other disciplines such as computer science, mathematics, science, and engineering. It draws upon and integrates concepts and principles from these fields to define a new, cohesive body of knowledge centered on the representation and manipulation of computational models.
Subfields of the CSE discipline include high performance computing, data analytics and machine learning, visualization, modeling and simulation, and numerical and discrete algorithms.
Computation now is widely accepted, along with theory and experiment, as a crucial third mode of scientific research and engineering design. Computational modeling and data analytics are routinely used in virtually all fields of science and engineering, to analyze systems as large as the universe and as small as the tiniest molecules. They are essential to solving the most important and challenging problems facing the world today, such as the diagnosis and prognosis of disease, the creation of sustainable cities, and the development of new sources of clean, inexpensive energy.
In short, computational science and engineering has become indispensible in modern science and engineering.
About the School
The School of Computational Science and Engineering is devoted to the advancement and promotion of the CSE discipline. Our research focuses on making fundamental advances in the creation and application of new computational methods and techniques in order to enable breakthroughs in scientific discovery and engineering practice.
This research spans many computational areas. For example, research in high performance computing develops new ways to exploit the world’s most powerful supercomputers. Research in massive scale data and visual analytics and machine learning explores ways to extract useful information from the unprecedented volumes of data now appearing on the Internet and in many fields of science, engineering, and medicine. Modeling and simulation research explores new methods to exploit parallel and distributed computing platforms in order to solve challenging problems in areas such as medicine and transportation. Algorithm research builds a solid foundation spanning both continuous and discrete models. Our research is inherently interdisciplinary and includes interdepartmental collaborations and interactions that crisscross the Georgia Tech campus—and extend around the world.
Our degree programs strive to create a new type of scholar who is well versed in synthesizing principles from mathematics, science, engineering and computing to create innovative computational models and apply them to solve important real-world problems. The School of CSE played a leading role in creating Georgia Tech’s interdisciplinary master’s and doctoral degree programs in computational science and engineering, which include many other schools and departments across Georgia Tech. CSE also created the first distance-learning degree in the College of Computing with an option in the CSE master’s degree program.
A Message from the Chair of CSE
I believe that the School of CSE has firmly established itself as the country’s premier department focused on solving real-world challenges through advanced computational techniques, thanks to a world-class faculty and dedicated students,” says Bader. “My plan as school chair is to accelerate our impactful research and gain recognition for further successes by solving grand challenges that make this world a better place for all.
David A. Bader
Professor and Chair
School of Computational Science and Engineering