Skip to Content

Search: {{$root.lsaSearchQuery.q}}, Page {{$root.page}}

Statistics Department Seminar Series: Abhra Sarkar, Ph.D., Post-Doctoral Associate, Department of Statistical Science, Duke University

Novel Statistical Frameworks for Analysis of Structured Sequential Data
Friday, January 13, 2017
11:30 AM-1:00 PM
411 West Hall Map
Abstract:

We are developing a broad array of novel statistical frameworks for analyzing complex sequential categorical data sets. Our research is primarily motivated by a collaboration with neuroscientists trying to understand the neurological, genetic and evolutionary basis of human communication using bird and rodent models. The data sets comprise structured sequences of syllables or ‘songs’ produced by animals from different genotypes under different experimental conditions. The primary goals are to elucidate the roles of different genotypes and experimental conditions on animal vocalization behaviors and also to learn complex serial dependency structures and systematic patterns in the vocalizations. We are developing novel statistical methods based on first and higher order Markovian dynamics that help answer these important scientific queries. The methods have appealing theoretical properties and practical advantages and are of very broad utility, with applications not limited to analysis of animal vocalization experiments. Our research also paves the way to advanced automated methods for many other sophisticated dynamical systems that can accommodate more general data types.
Building: West Hall
Website:
Event Type: Workshop / Seminar
Tags: seminar
Source: Happening @ Michigan from Department of Statistics, Department of Statistics Seminar Series