Plenary Key Notes:
Tim Bell, CERN
LHC COMPUTING: TOWARDS CLOUDS AND AGILE INFRASTRUCTURES
Mon, Sep. 1, 14:30 - 15:30
CERN is undergoing a major transformation in how computing services are delivered with the addition of a second data centre to help process over 35PB/year from the Large Hadron Collider.Within the constraints of fixed budget and manpower, agile computing techniques and common open source tools are being adopted to support over 11,000 physicists.
Tim Bell is responsible for the CERN IT Operating System and Infrastructure Group which supports Windows, Mac and Linux across the site along with virtualisation, printing, E-mail and web services. Prior to working at CERN, Tim worked for Deutsche Bank managing private banking infrastructure for Europe and with IBM as a Unix kernel developer and deploying large scale technical computing solutions. Tim is also an elected individual member of the OpenStack management board since 2012 and a member of the OpenStack user committee.
Prof. Frank Kirchner, Robotics Innovation Center, DFKI Bremen
ROBOTICS & ARTIFICIAL INTELLIGENCE
Wed, Sep. 3, 19:00 - 20:30
In recent years robotics has gained a lot of interest also in the area of artificial intelligence. While systems for a long time have been used as tools to implement classical AI approaches in the area of object recognition, environment representation, path and motion planning etc., researchers now begin to understand that the system (robot) itself is part of the question and has to be taken into account when teaching AI questions. This talk might survey the state of the art in robotics and outline ways to tackle the question of AI in the light of the systems as an integral part of the approach. Future milestones an key achievements will be discussed as a proposal to tackle the big question of AI.
Frank Kirchner studied Computer Science and Neurobiology at the University Bonn from 1989 until 1994, where he received his Diploma (Dipl. Inf.) in 1994 and graduated (Dr. rer. nat.) in Computer Science in 1999.
Prof. Richard Frackowiak, Department of Clinical Neuroscience, University of Lausanne
BRAIN PATHOLOGIES AND BIG DATA
Mon, Sep. 1, 16:00 - 17:00
We now know that a single gene mutation may present with multiple phenotypes, and vice versa, that a range of genetic abnormalities may cause a single phenotype. These observations lead to the conclusion that a deeper understanding is needed of the way changes at one spatial or temporal level of organisation (e.g., genetic, proteomic or metabolic) integrate and translate into others, eventually resulting in behaviour and cognition. The traditional approach to determining disease nosology- eliciting symptoms and signs, creating clusters of like individuals and defining diseases primarily on those criteria has not generated fundamental breakthroughs in understanding sequences of pathophysiology mechanisms that lead to the repertoire of psychiatric and neurological diseases.
It is time to radically overhaul our epistemological approach to such problems. We now know a great deal about brain structure and function. From genes, through functional protein expression, to cerebral networks and functionally specialised areas defined via physiological cell recording, microanatomy and imaging we have accumulated a mass of knowledge about the brain that so far defies easy interpretation. Advances in information technologies, from supercomputers to distributed and interactive databases, now provide a way to federate very large and diverse datasets and to integrate them via predictive data-led analyses.
Human functional and structural brain imaging with MRI continues to revolutionise tissue characterisation from development, through ageing and as a function of disease. Multi-modal and multi-sequence imaging approaches that measure different aspects of tissue integrity are leading to a rich mesoscopic-level characterisation of brain tissue properties. Novel image classification techniques that capitalise on advanced machine learning techniques and powerful computers are opening the road to individual brain analysis. Data-mining methods, often developed in other data-rich domains of science, especially particle and nuclear physics, are making it possible to identify causes of disease or its expression from patterns derived by exhaustive analysis of combinations of genetic, molecular, clinical, behavioural and other biological data. Imaging is generating data that links molecular and cellular levels of organisation to the systems that subtend, action, sensation, cognition and emotion. These ideas will be illustrated with reference to the human dementias.
Richard Frackowiak is head of the Department of Clinical Neurosciences at the Université de Lausanne (UNIL & CHUV) and a titular professor at the Ecole Polytechnique Fédérale de Lausanne. His interest is in human brain structure and function relationships in health and disease. He is highly cited with an h-index is 153 and has been awarded the Ipsen, Wilhelm Feldberg and Klaus Joachim Zulch prizes. Formerly Foundation Professor of Cognitive Neurology at University College London, Director of the Department of Cognitive Studies at the Ecole Normale Supérieure Paris, Wellcome Trust Principal Clinical Research Fellow, Dean-Director of the Institute of Neurology and Vice-Provost of UCL, he founded the Wellcome Department of Imaging Neuroscience (FIL) in 1994. MA and MD Cambridge, DSc London University, he holds an honorary doctorate from Liege University and an honorary professorship from UCL. He is a Fellow of the Academies of Medical Sciences of the UK, France, Belgium and the Academia Europaea and is a foreign associate of the Institute of Medicine USA and the Polish Academy of Sciences. He is past president of the British Neuroscience Association and the European Brain and Behaviour Society and editor-in-chief of NeuroImage.
Dr. Fabrizio Gagliardi, - Distinguished Research Director, Polytechnic University of Catalonia, Spain
Cloud computing in Europe for Science and industry. First experience and current trends.
Fri, Sep. 5, 10:50 - 11:50
The talk will discuss the current transformation in the computing landscape. The advent of Virtualization have made possible highly scalable and affordable distributed computing systems such as those offered by Cloud providers, public or private. This poses new challenges and problems to do with latency in accessing the data, SLAs, privacy and security issues. At the same time the explosion of data has generated the emergence of new computing paradigms such as MapReduce and Hadoop and the need for new computing storage hierarchies for HPC and distributed computing. The talk will review some practical experience drawn from the recently concluded FP7 project Venus-C and discuss current issues and trends.
Other current positions: