Modeling and forecast of socio-technical systems in the data-science age.
Alessandro Vespignani, Northeastern University, Boston (MA, USA) and ISI Foundation, Torino (Italy)
In recent years the increasing availability of computer power and informatics tools has enabled the gathering of reliable data
quantifying the complexity of socio-technical systems. Data-driven computational models have emerged as appropriate tools to tackle the study of contagion and diffusion processes as diverse as epidemic outbreaks, information spreading and Internet packet routing. These models aim at providing a rationale for understanding the emerging tipping points and nonlinear properties that often underpin the most interesting characteristics of socio-technical systems. Here I review some of the recent progress in modelling contagion and epidemic processes that integrates the complex features and heterogeneities of
Alessandro Vespignani is Sternberg Distinguished Professor at Northeastern University in Boston, where he leads the Laboratory for the Modeling of Biological and Socio-technical Systems. He is fellow of the American Physical Society, member of the Academy of Europe, and fellow of the Institute for Quantitative Social Sciences at Harvard University. He is also serving in the board/leadership of a variety of journals and the Institute for Scientific Interchange Foundation. He is president elected of the Complex Systems Society. Vespignani is focusing his research activity in modeling diffusion phenomena in complex systems, including data-driven computational approaches to infectious diseases spread.
organized by Vittorio Loreto, Sapienza University of Rome (Italy)
Interconnected techno-social systems have an increasingly pervasive influence on our culture and everyday life. Technology plays a fundamental role in connecting people and circulating information, and affects more and more the way humans interact with each other. Everyday, a huge amount of information is exchanged by people through posts and comments on-line, tweets or emails, or phone calls as a natural aptitude of humans to share news, thoughts, feelings, or experiences. In addition, nowadays low-cost sensing technologies are being developed to allow citizens to directly assess the state of the environment; social networking tools allow effective data and opinion collection and real-time information sharing processes. The possibility to access to digital fingerprints of individuals is opening tremendous avenues for an unprecedented monitoring at a "microscopic level" of collective phenomena involving human beings. We are thus moving very fast towards a sort of a tomography of our societies, with a key contribution of people acting as data gathering "sensors". The panelists will discuss about the new challenges as well as the new opportunities that techno-social systems bring forward.
Future Control Challenges for Smart Grids.
organized by Sebastian Lehnhoff, OFFIS - Institute for Information Technology (Germany)
Future Smart Grids will be composed of large collections of autonomous components, e.g. PV systems, CHPs, or controllable consumers such as heat pumps or air conditioners. Sensors and actuators, aware of their environment, with the ability to communicate freely, will have to organize themselves in order to perform the actions and services that are required for a reliable and robust power supply. Monitoring and efficiently operating power networks with a high density of distributed renewable generation and controllable consumption is neither efficient nor robust or adaptive with centralized management. In order to achieve the necessary resolution and level of control, prospective smart energy networks need to be controlled by autonomous yet coordinated software agents acting on behalf of consumers and producers of electric energy. Self-organization provides a paradigm based on the urgent necessity to find methodologies for managing the complexity and controlling the behaviour of larg e scale distributed systems. However, in order to use such methods for controlling Smart Grids detailed analysis of key features as e.g. predictable synergetic behavior, avoidance of oscillations, or robustness against local failures are required. The panelists will discuss the issues of promotion self-organization in the industry as well as introducing domestic customers to autonomous control solutions.