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Recent news reports stated that the National Security Agency has pursued new methods that have allowed the agency to monitor telephone and online communication, encrypted information that was thought to be virtually immune to eavesdropping. What steps can and should computer scientists take in response to this privacy threat? How will the recent revelations affect the future of cryptography—the field of encoding and decoding electronic communication and transmissions for the purposes of privacy, reliability and efficiency?
To address these questions, the Johns Hopkins University Information Security Institute will host an hour-long roundtable discussion, moderated by Anton Dahbura, interim executive director of the Information Security Institute, and Avi Rubin, the institute’s technical director. Other participants will include Johns Hopkins cyber-security experts Matthew Green, Stephen Checkoway and Giuseppe Ateniese.
The event will be streamed live at https://connect.johnshopkins.edu/jhuisicrypto/, and also will be posted online following the event.
NOTE: Seating at this public event will be limited. Members of the media who plan to cover the discussion are asked to RSVP to Phil Sneiderman, email@example.com.
Viktor Jirsa, Director of the Inserm Institut de Neurosciences des Systèmes at Aix-Marseille-Université and Director of Research at the Centre National de la Recherche Scientifique (CNRS) in Marseille, France, will present “Translational Medicine: From Bifurcations to Epilepsy Surgery.”
Abstract: Over the past decade we have demonstrated that constraining computational brain network models by structural information obtained from human brain imaging (anatomical MRI, diffusion tensor imaging (DTI)) allows patient specific predictions, beyond the explanatory power of neuroimaging alone. This fusion of an individual’s brain structure with mathematical modelling allows creating one model per patient, systematically assessing the modeled parameters that relate to individual functional differences. The functions of the brain model are governed by realistic neuroelectric and neurovascular processes and allow executing dynamic neuroelectric simulation; further modeling features include refined geometry in 3D physical space; detailed personalized brain connectivity (Connectome); large repertoire of mathematical representations of brain region models, and a complete set of physical forward solutions mimicking commonly used in non-invasive brain mapping including functional Magnetic Resonance Imaging (fMRI), Magnetoencephalography (MEG) Electro-encephalography (EEG) and StereoElectroEncephalography (SEEG). So far our large-scale brain modeling approach has been successfully applied to the modeling of the resting state dynamics of individual human brains, as well as aging and clinical questions in stroke and epilepsy. In this talk I will focus on the example of epilepsy and systematically demonstrate the individual steps towards the creation of a personalized epileptic patient brain model.
Those unable to attend on the Homewood campus may view a simulcast in Traylor 709 on the Johns Hopkins School of Medicine campus. The lecture will also be streamed through Panopto. Click here to view the webcast.