Abstract: A fundamental challenge in neuroscience is to understand the algorithms that neural circuits have evolved to solve computational problems critical for survival. In this talk, I will describe how the olfactory circuit in the fruit fly brain has evolved simple yet effective algorithms to process and store odors. First, I will describe how fruit flies use a variant of a traditional computer science algorithm (called locality-sensitive hashing) to perform efficient similarity searches. Second, I will describe how this circuit uses a variant of a classic data structure (called a Bloom filter) to perform novelty detection for odors. In both cases, we show that tricks from biology can be translated to improve machine computation, while also raising new hypotheses about neural function. I will conclude by arguing that the search for "algorithms in nature" is not limited to only the brain and could include many other areas of biology, including plant biology.
Bio: Saket Navlakha is an assistant professor in the Integrative Biology Laboratory at the Salk Institute for Biological Studies. He received an A.A. from Simon's Rock College in 2002, a B.S. from Cornell University in 2005, and a Ph.D. in computer science from the University of Maryland College Park in 2010. He was then a post-doc in the Machine Learning Department at Carnegie Mellon University before starting his lab at the Salk Institute in 2014. His lab studies algorithms in nature, i.e., how collections of molecules, cells, and organisms process information and solve computational problems. In 2018, he was named a Pew Biomedical Scholar, and in 2019, he was awarded an NSF CAREER award.
Created by Mary McDavitt at Monday, February 04, 2019 at 5:35 PM.