{"347741":{"#nid":"347741","#data":{"type":"event","title":"Ph.D. Thesis Proposal by Ilias Fountalis","body":[{"value":"\u003Cp\u003EPh.D. THESIS PROPOSAL\u003Cbr \/\u003E\u003Cbr \/\u003ETITLE: \u003Cstrong\u003EFrom spatio-temporal data to functional weighted networks: methods and\u003C\/strong\u003E\u003Cstrong\u003E\u0026nbsp;\u003C\/strong\u003E\u003Cbr \/\u003E\u003Cstrong\u003Eapplications in climate science, neuroscience and ecology.\u003C\/strong\u003E\u003Cbr \/\u003E\u003Cbr \/\u003E\u003Cstrong\u003EIlias Fountalis\u003C\/strong\u003E\u003Cbr \/\u003ESchool of Computer Science\u003Cbr \/\u003ECollege of Computing\u003Cbr \/\u003EGeorgia Institute of Technology\u003Cbr \/\u003E\u003Cbr \/\u003EDate: Wednesday,\u0026nbsp;December 3, 2014\u003Cbr \/\u003ETime: 11:00 AM - 1:00 PM\u003Cbr \/\u003ELocation: KACB 3100\u003Cbr \/\u003E\u003Cbr \/\u003ECommittee:\u003Cbr \/\u003E----------\u003Cbr \/\u003E\u003Cbr \/\u003EProf. Constantine Dovrolis, School of Computer Science, GeorgiaTech\u0026nbsp;\u003Cbr \/\u003E(Advisor)\u003Cbr \/\u003EProf. Mostafa H. Ammar, School of Computer Science, GeorgiaTech\u003Cbr \/\u003EProf. Annalisa Bracco, Earth and Atmospheric Sciences Department,\u0026nbsp;\u003Cbr \/\u003EGeorgiaTech\u003Cbr \/\u003EAssistant Prof. Bistra Dilkina, \u0026nbsp;School of Computational Science and\u0026nbsp;\u003Cbr \/\u003EEngineering, GeorgiaTech\u003Cbr \/\u003EAssociate Prof. Shella Keilholz, Wallace H. Coulter Department of\u0026nbsp;\u003Cbr \/\u003EBiomedical Engineering, GeorgiaTech and Emory University School of Medicine\u003Cbr \/\u003EProf. Athanasios Nenes, Earth and Atmospheric Sciences Department,\u0026nbsp;\u003Cbr \/\u003EGeorgiaTech\u003Cbr \/\u003E\u003Cbr \/\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003Cbr \/\u003E----------\u003Cbr \/\u003EThere is an abundance of spatio-temporal data\u0026nbsp;today\u0026nbsp;from diverse complex\u0026nbsp;\u003Cbr \/\u003Esystems such as the Earth\u0027s climate, the human brain, or the mobility\u0026nbsp;\u003Cbr \/\u003Epatterns of migratory species. By analyzing such data, scientists are\u0026nbsp;\u003Cbr \/\u003Eable to discover the key modules of the corresponding system, and to\u0026nbsp;\u003Cbr \/\u003Einvestigate their dynamics and inter-dependencies.\u003Cbr \/\u003E\u003Cbr \/\u003ESpatio-temporal data are typically embedded in a two- or\u0026nbsp;\u003Cbr \/\u003Ethree-dimensional grid, and the dynamics of each grid cell are\u0026nbsp;\u003Cbr \/\u003Erepresented by a time-series. Common computational analysis methods for\u0026nbsp;\u003Cbr \/\u003Esuch data include standard time series analysis, spatial clustering, and\u0026nbsp;\u003Cbr \/\u003Eprincipal\/independent component analysis. These techniques, although\u0026nbsp;\u003Cbr \/\u003Evaluable in specific contexts, are not able to directly identify the\u0026nbsp;\u003Cbr \/\u003Elatent functional components of the system and how these components\u0026nbsp;\u003Cbr \/\u003Einteract with each other. This objective can be met more naturally with\u0026nbsp;\u003Cbr \/\u003Ea framework that is based on network analysis.\u003Cbr \/\u003E\u003Cbr \/\u003EThe emerging field of network analysis incorporates a broad range of\u0026nbsp;\u003Cbr \/\u003Emodels, metrics and algorithms to study complex nonlinear dynamical\u0026nbsp;\u003Cbr \/\u003Esystems; its main premise is that the underlying topology or network\u0026nbsp;\u003Cbr \/\u003Estructure of a system has a strong impact on its dynamics and evolution.\u003Cbr \/\u003E\u003Cbr \/\u003EWe propose a novel network-based analysis framework for the study of\u0026nbsp;\u003Cbr \/\u003Espatio-temporal data. First, we cluster grid-cells into \u0022areas\u0022, defined\u0026nbsp;\u003Cbr \/\u003Eas spatially coherent regions that are highly homogeneous in terms of\u0026nbsp;\u003Cbr \/\u003Edynamics. The proposed algorithm identifies a parsimonious set of latent\u0026nbsp;\u003Cbr \/\u003Efunctional components, and it relies on a single parameter that is set\u0026nbsp;\u003Cbr \/\u003Ebased on a target statistical significance level. In a second step, we\u0026nbsp;\u003Cbr \/\u003Eidentify edges between areas. The strength of the edge between two areas\u0026nbsp;\u003Cbr \/\u003Eis given by the covariance of their cumulative anomaly time series. Each\u0026nbsp;\u003Cbr \/\u003Eedge is also characterized by the lag at which the cross-correlation\u0026nbsp;\u003Cbr \/\u003Ebetween the two areas is maximum, in absolute sense.\u003Cbr \/\u003E\u003Cbr \/\u003EThe proposed framework has been applied successfully in Climate Science\u0026nbsp;\u003Cbr \/\u003Eto evaluate state-of-the-art climate models and to assess their\u0026nbsp;\u003Cbr \/\u003Eperformance. Further, we have investigated future projections of these\u0026nbsp;\u003Cbr \/\u003Emodels\u0027 trajectories under increased greenhouse gas emission scenarios.\u0026nbsp;\u003Cbr \/\u003EWe are going to also apply the proposed method on functional MRI data to\u0026nbsp;\u003Cbr \/\u003Econstruct dynamic functional brain networks. Finally, we will apply the\u0026nbsp;\u003Cbr \/\u003Eproposed framework in the context of Ecology, to investigate bird\u0026nbsp;\u003Cbr \/\u003Emigration patterns.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"From spatio-temporal data to functional weighted networks: methods and  applications in climate science, neuroscience and ecology."}],"uid":"28077","created_gmt":"2014-11-20 10:55:53","changed_gmt":"2016-10-08 02:10:26","author":"Danielle Ramirez","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2014-12-03T10:00:00-05:00","event_time_end":"2014-12-03T12:00:00-05:00","event_time_end_last":"2014-12-03T12:00:00-05:00","gmt_time_start":"2014-12-03 15:00:00","gmt_time_end":"2014-12-03 17:00:00","gmt_time_end_last":"2014-12-03 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"221981","name":"Graduate Studies"}],"categories":[],"keywords":[{"id":"1808","name":"graduate students"},{"id":"102851","name":"Phd proposal"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}