The IEEE International Conference on Data Science and Advanced Analytics (DSAA) aims to be the flagship annual meeting spanning the interdisciplinary field of Data Science. DSAA focuses on the science of data science, as well as the implications of the science for applications to industry, government, and society. From the science side, DSAA spans all of the component fields of data science, including statistics, probabilistic and mathematical modeling, machine learning, data mining and knowledge discovery, complexity science, network science, business analytics, data management, infrastructure and storage, retrieval and search, security, privacy and ethics. From the applications side, DSAA aims both to show researchers important problems and issues that are revealed by real applications, and to show practitioners and users how the science can be applied to realize value. DSAA is intended to reflect the interdisciplinary nature of data science and analytics, as an alternative to the highly specialized disciplinary conferences.

October 1-4, 2018

Torino, Italy

Source: dsaa2018.isi.it

Neuroscience is a highly interdisciplinary field focused on uncovering the dynamics of brain and, more in general, the complex functions and structures of neural systems. These topics constitute paradigmatic examples of complex systems, and can be studied by using different frameworks, spanning from nonlinear dynamics to complex networks. In addition, the increasing availability of data coming from tools like fMRI, EEG, and others, has strongly supported new investigations. At the same time, although these topics are maybe among mostly investigated in science, a lot must yet be discovered. Remarkably, neural systems have had a great impact also in parallel fields, e.g. artificial intelligence, leading to propose new algorithms and computational techniques. For instance, neural networks and their evolution to the modern deep learning represent one of the most successful cases. It is worth to highlight that some of these tools (e.g. Deep Learning) are now widely used for investigating (biological) neural systems, e.g. for analyzing brain waves. As result, a big interdisciplinary community composed of neuroscientists, physicists, mathematicians, computer scientists, and many others, nowadays collaborates on the same projects and interacts trying to obtain new insights in this complex and exciting field. The proposed satellite will be focused on theoretical neuroscience, and its extensions to AI/Deep Learning, in order to attract the interest of researchers working in a highly interdisciplinary contexts, often overlapping, with the aim to trigger discussions and sharing novel ideas on the field. In particular, we aim to have a specific focus on the synopsis of current research into complex networks in human neuroscience, supported by data coming from fMRI/EEG/etc, on the complexity emerging in artificial neural networks, and on the potential synergy between the two fields.

Source: www.braincomputing-satellite.com