Abstract: A complex system is one in which its macroscopic properties emerge from the microscopic behavior of its components in such a way that they cannot be predicted from a fully detailed knowledge of them, resulting in the fact that the whole is more than the sum of its part. Leading scientific journals and research agencies have defined the challenge of understanding the structure and dynamics of complex systems as one of the major scientific endeavors of Science in the 21st Century. In this talk, I will introduce the audience to the basic problems that we face when we study a complex system. Through the specific example of modeling the large scale spreading of infectious diseases, we will see how the last 20 years have witnessed the development of tools that increasingly allow for a better understanding and characterization of complex natural, biological and socio-technical systems. We round off the talk by presenting current and future challenges, most notably, the application of Machine Learning techniques to tackle many open questions in complex systems science.

Short biography: Professor Yamir Moreno is the Director of the Institute for Biocomputation and Physics of Complex Systems (BIFI), University of Zaragoza, Spain. He is also a Deputy Director of the ISI Foundation in Italy and External Professor of the Complexity Science Hub Vienna, Austria. He is President of the Network Science Society (NSS) and served as President of the Complex Systems Society from 2015 to 2018. Yamir has published more than 200 scientific papers in international refereed journals and he serves as a reviewer for around 30 scientific journals and research agencies. His research works have collected more than 17550 (28650) citations, h=54(64) according to ISI WoK (Google Scholar). 

He is among the 1% most cited scientists in 2019 (The world’s most influential researchers).