The Dynamics of Information

<!--HTML--><link rel=\"stylesheet\" type=\"text/css\" href=\"http://cern.ch/cseminar/CDS/style.css\" /> <p> The dynamics of information within organizations is relevant to issues of productivity, innovation, and the sorting out of useful ideas from the general chatter of a community. How information spreads and is aggregated determines the speed with which individuals and organizations can act and plan their future activities. <p> This talk will describe mechanisms for automatically identifying communities of practice within organizations and for elucidating the spread of information spreads within those communities. In addition, a new method for forecasting uncertain events using small groups of people will be presented, along with empirical results that show its efficacy at making predictions in the real world. <h4>About the speaker</h4> <p> Bernardo Huberman is a Senior HP Fellow and Director of the Information Dynamics Lab at Hewlett Packard Laboratories. He received his Ph.D. in Physics from the University of Pennsylvania, and is currently a Consulting Professor in the Department of Applied Physics at Stanford University. He originally worked in condensed matter physics, ranging from superionic conductors to two-dimensional superfluids, and made contributions to the theory of critical phenomena in low dimensional systems. He was one of the discoverers of chaos in a number of physical systems, and also established a number of universal properties in nonlinear dynamical systems. His research into the dynamics of complex structures led to his discovery of ultradiffusion in hierarchical systems. <p> You may read more about him <a href="http://www.hpl.hp.com/research/idl/people/huberman/" target="_blank">here</a> <hr> <address> Organiser(s): <a href=\"http://consult.cern.ch/xwho/people/412742\">Miguel Angel Marquina</a> <BR><a target=\"_blank\" href=http://cern.ch/Computing.Seminars>Computing Seminars</a> / <a target=\"_blank\" href=\"http://cern.ch/it-dep\">IT Department</a> </address>