Our people are leaders in the fields of human genetics, sociology, mathematics, history, evolutionary biology, English literature and psychology, from the nations most prestigous institutions. About a third come from a computational modeling background who are interested in identifying and modeling knowledge generation and transmission processes. The remaining two thirds take the long view of science and scholarship and bring their expertise into meaningful conversations and research on topics that are of interest to them and to the Lab as a whole.
In the Limelight
Principal Software Engineer, University of Chicago
William earned a PhD in Electrical and Computer Engineering at the Illinois Institute of Technology in 1997, under the guidance of Joseph L. LoCicero and Henry Stark. His research topic was Constrained Optimization Algorithms for Image Processing, applied to Hologram design. In addition to working at several technology companies, he spent a large portion of his career as an independent consultant.
Assistant Professor of Statistical Science, Duke University
Rebecca C. Steorts is an Assistant Professor of Statistical Science at Duke University with affiliations in the information initiative at Duke (iid) and the Social Science Research Institute (SSRI). She received her B.S. in Mathematics in 2005 from Davidson College, her MS in Mathematical Sciences in 2007 from Clemson University, and her PhD in 2012 from the Department of Statistics at the University of Florida under the supervision of Malay Ghosh. She is currently a Visiting Assistant Professor in the Statistics Department at Carnegie Mellon University. Rebecca is a recipient of the Graduate Alumni Fellowship Award (2007-2010) from the University of Florida and the U.S. Census Bureau Dissertation Fellowship Award (2010-2011). In 2011, she was awarded the UF Innovation through Institutional Integration Program (I-Cubed) and NSF for development of an introductory Bayesian course for undergraduates. She has also been awarded Finalist for the 2012 Leonard J. Savage Thesis Award in Applied Methodology. She is interested in scalable computational methods for social science applications. Her current works focuses on recovering high dimensional objects from degraded data and determining how to recover the underlying structure. Methods used for this are entity resolution, small area estimation, locality sensitive hashing, and privacy-preserving record linkage as applied to medical studies, fmri studies, human rights violations, and estimation of poverty rates in hard to reach domains. Her research was on record linkage and sparse clustering was recently funded by the John Templeton Foundation, MetaKnowledge Network Grants Awarded, November 2014. Also, her work on privacy and record linkage was just funded by the National Science Foundation. She was recently named to MIT Technology Review's 35 Innovators Under 35 for 2015 as a humantarian in the field of software. Her work will be profiled in the Septmember/October issue of MIT Technology Review and she will be recognized at a special ceremony along with an invited talk at EmTech in November 2015.