Prof. Daniels is an associate professor of computer science, with the majority of his research focused on algorithms for “big data” – essentially, sublinear-time algorithms for problems such as search or sequence alignment, trying to leverage the manifold structure of high-dimensional data. He did a postdoc in mathematics at MIT and a Ph.D in computer science at Tufts University, focused on problems in computational biology ranging from protein structure prediction to biological sequence analysis. More recently, he has also been interested in applying “manifold mapping” ideas to problems in astronomy, cybersecurity, and machine learning.