Daniel Sussman recently joined CISE as faculty affiliate, bringing statistical expertise, extensive research experience, and a collaborative mindset to the interdisciplinary community. Sussman is an Assistant Professor in the Department of Mathematics and Statistics at Boston University. He started teaching in 2016.
His main research efforts have focused on statistical inference for network data. Sussman is currently exploring the impact of computational constraints on statistical risk and efficiency. His research seeks to develop a framework to describe and quantify trade-offs between fast computation and low statistical risk, which will allow practitioners to make informed decisions about the trade-off.
He has also been working jointly with neuroscientists on connectomics to collect network related data about the brain. Sussman uses network techniques to develop new methods to assess fundamental conjectures in neuroscience. His work also helps them perform statistical analysis on super high resolution images of neurons to understand their basic properties.
Sussman is a mentor, and is seeking collaboration with graduate students to research in statistics and networks. He attended Cornell University as an undergraduate, and received his Ph.D. in Applied Math and Statistics from Johns Hopkins University in 2014.