Associate Research Professor; Assistant Professor in Applied Math
Tamás Budavári’s primary interest is in cosmology, large-scale structure, and galaxy evolution. He has been focusing on various statistical and computational challenges in astronomy as modern detector technology is rapidly changing the way science is done. Large projects he has worked on, including the Sloan Digital Sky Survey, pioneered much of the new methodology. Work done with next-generation telescopes will require new ways of doing science. New hardware architectures, new algorithms and new statistical methods will be needed to analyze the observations of the upcoming surveys, such as the Large Synoptic Survey Telescope.
AS.171.628 Practical Scientific Analysis of Big Data
In accord with the goals of JHU's Institute for Data Intensive Engineering and Science (IDIES), this new course for Spring 2012 is focusing on modern data analytics. Graduate students learn to work with scientific databases and implement parallel computation on GPUs using CUDA. New data processing approaches are introduced to tackle frequent challenges of massive data.
AS.171.633 Graphics Processor Programming in CUDA
In conjunction with the Practical Scientific Analysis of Big Data class, this semester a short graduate course is also offered, which covers parallel computing on modern general-purpose graphics processors. Students learn to design and implement scientific algorithms in C for CUDA, the Compute Unified Device Architecture.