Algorithms for Large-scale Biophysical Data Analysis
In the last few years, new opportunities for discovery through data analysis, modeling and simulation have emerged in the biological and biomedical sciences, as well as in traditional physical and social sciences. Biological researchers, in particular, are being confronted by an explosion of data from genome sequencing, gene expression arrays, mass spectroscopy, protein interaction studies, high-resolution imaging, multi-electrode arrays and a host of other new experimental technologies. The speaker will describe several research problems at the interface of mathematics, computational science and laboratory experiment where close collaboration between theorists and practitioners will be essential in making progress, with a particular focus on neuroscience and structural biology.
About the speaker
Prof. Leslie Greengard received his PhD in Computer Science from Yale University in 1987. He has been on the faculty of the Courant Institute of Mathematical Sciences at New York University since 1989, and was the director of the Institute from 2006 to 2011. He is currently Silver Professor of Mathematics and Computer Science. He is also founding director of the Simons Center for Data Analysis.
Prof. Greengard’s research focuses on integral equation methods for electromagnetics, acoustics, elasticity, plasma physics and fluid dynamics. His research group is developing fast solvers for each of these applications in complex geometry, and extending “analysis-based fast solvers” to kernel-based methods in statistical inference.
Prof. Greengard received numerous awards including the John von Neumann Lecture Prize, the Wilbur Cross Medal, and the Leroy P. Steele Prize for Seminal Contribution to Research, etc. He is a Member of the US National Academy of Sciences and the US National Academy of Engineering.