Computational Science and Engineering (CSE) is a discipline devoted to the study and advancement of computational methods and data analysis techniques to analyze and understand natural and engineered systems. CSE is inherently interdisciplinary, and integrates concepts and principles from computer science, mathematics, science, and engineering to define a new, cohesive body of knowledge that is rapidly changing. It solves real-world problems in science, engineering, health, and social domains, by using high-performance computing, modeling and simulation, and large-scale Big Data analytics. Our research enables breakthroughs in scientific discovery and engineering practice.
CSE research at Georgia Tech spans many areas. For example, research in High Performance Computing improves the efficiency, reliability and speed of algorithms, software, tools and applications running on a variety of architectures. Artificial Intelligence and Machine learning research explores the construction and study of learning models and algorithms that make data-driven predictions or decisions. Data Science and Visual Analytics research develops new methods that transform large and complex data sets into value, and visualization techniques to interactively query and analyze enormous data sets ranging from terabytes to petabytes. Scientific Computing and Simulation develops mathematical models and uses simulation and learning as a means to understand natural and engineered systems, often leveraging the above areas. Research in Computational Bioscience and Biomedicine encompasses bioinformatics, genomics, systems biology, biomedical system modeling, and data-driven approaches to public health management.
The School of CSE is a diverse, interdisciplinary innovation ecosystem composed of award-winning faculty, researchers, and students. We are creating future leaders who keep pace with and solve the most challenging problems in science, engineering, health, and social domains.
Read the CSE Annual Report for more information.