Our group's research focuses on developing new software tools to better analyze large-scale biological, health, and medical data using diverse computational methods including machine learning (ML) and deep learning (DL) on high-performance computing (HPC) systems such as supercomputers and cloud computing.
Bioinformatics is an interdisciplinary field that develops methods and software tools for understanding biological data. As an interdisciplinary field of science, bioinformatics combines computer science, statistics, mathematics, and engineering to analyze and interpret biological data.
High-Performance Computing most generally refers to the practice of aggregating computing power in a way that delivers much higher performance than one could get out of a typical desktop computer or workstation in order to solve large problems in science, engineering, or business.
Computational science is the application of computational and numerical techniques to solve large and complex problems. Computational science takes advantage of the improvements in computer algorithms and mathematical techniques to do things that were previously too difficult or complex.