**When: Friday, February 8, 2019, 2:00 pm**

**Where: Informatics West, Room 232
**

**Speaker: Didier A. Vega-Oliveros
**

** **

Complex Networks’ Approaches for Analyzing Climate (and Other Spatiotemporal) Data

**Abstract: **Complex network theory has helped to identify valuable information in many domains, where systems are complex with non-trivial connections and properties. In this way, understanding how the network structure impacts the dynamics and also how to infer the structure from these dynamics is of paramount importance to the area. In another perspective, real-world time series reflect inherently nonlinear processes determining the underlying system’s structure and dynamics. A vast amount of time-series data come from many fields, including climate, car accidents, crimes, or neurosciences. In this talk, I will focus on how to analyze and represent spatiotemporal systems on networks, discussing some approaches like visibility graphs, time-series correlation networks, among others. Besides, this talk aims to show the great potentials of time series networks to tackling real-world contemporary scientific problems, and more important, identify and discuss some gaps and research challenges in the area.

**Biography: **Didier Vega-Oliveros received his PhD in Computer Science in 2017 from University of Sao Paulo, Brazil. He is a collaborative researcher at the National Institute for Space Research – INPE of Brazil, and recently, a post-doc visitor at Indiana University – Bloomington. His research deals with network sciences with data mining and its applications, in particular, developing algorithms applied to climate systems, social networks, and disasters risk reduction and management.