Computational Analysis and Applications Research Group (CARG

Objectives The group is performing research in the following areas: Merging physical and machine learning models: signal processing, probabilistic machine learning and deep learning models. Improving computational efficiency of algorithms: hardware and software accelerators Biomedical, tracking, acceleration of software testing and other applicatio... ns of machine learning and data analysis Learning in combined phyisical and machine learning models normally relies on computational approximate methods and therefore the term: computational analysis. History This research group evolved from Computer Architecture research group (original CARG). Computer architecture research group was formed in 2008 and focused on the following topics: computer architectures, signal processing architectures, hardware and software accelerators, GPU architectures and programming and algorithmic modifications for more efficient implementation in hardware. In recent years our research has gone in several different directions and therefore we decided to change the name of our group to Computational Analysis and Acceleration Research Group (new CARG).Read More