As the world becomes increasingly connected both virtually and physically, aspects of human societies behave more and more like evolved natural systems such as microbial communities and the brain network. Exploration of similarities and differences between them could offer novel insights and understanding that benefit mankind. Both data-driven modelling in the AI community and hypothesis-driven modelling in statistical physics can play important and complementary roles in tackling the hugely complex dynamics and behavior exhibited by these systems. The workshop aims at showcasing some of the successful research outcomes in this rapidly expanding interdisciplinary field, and promoting exchange of ideas and methodologies particularly among the young researchers.

Topics:

• Social network dynamics (epidemiology, crowdsourcing, opinion dynamics)
• Statistical mechanics in Data Science (algorithmic phase transitions, spin glasses, compressive sensing)
• Systems Biology (statistical laws in microbiomes, biological networks)
• Systems Neuroscience (connectomics, avalanche dynamics, grid cells)