Center for Computational Mathematics
Image and Signal Processing
At CCM, we develop new computational and statistical methods, and accompanying software, for the analysis of large, complex data sets, especially those that arise from high-throughput scientific experiments.
In applications ranging from neuroscience to microscopy to astronomy, we use novel mathematical approaches to create efficient, automated methods of analysis. In this area, we currently focus on 1) developing and benchmarking codes for identifying neural firing events in electrophysiological recordings (spike sorting) and calcium imaging; 2) algorithms to determine the 3-D structure of proteins and protein complexes from electron microscopy data (cryo-EM); and 3) high-dimensional statistical analysis of microbial interactions in the ocean from genetic sequencing and time-series data.
Spike Sorting at CCM
Recording from electrodes is key to neuroscience research, but the raw data require spike sorting – a computational technique for determining exactly when distinct neurons fire. Our lab develops ways to compare the accuracy of the many spike sorters available.