Bio: Prior to founding Maxeler, Oskar was Member of Technical Staff at the Computing Sciences Center at Bell Labs in Murray Hill, leading the effort in "Stream Computing". He joined Bell Labs after receiving a PhD from Stanford University. Besides driving Maximum Performance Computing (MPC) at Maxeler, Oskar is Consulting Professor in Geophysics at Stanford University and he is also affiliated with the Computing Department at Imperial College London, having received two Best Paper Awards, an Imperial College Research Excellence Award in 2007 and a Special Award from Com.sult in 2012 for "revolutionising the world of computers".

Abstract: Data volumes are sky-rocketing, and new sources and types of information are proliferating; we can now track and obtain data faster than ever before. Tools for modeling and understanding data are also abundant. But (big) data is only of value if you can extract insight from it . insights that lead you to decisions that can improve your processes, attract new clients, and be more nimble in your business. Today, deep and diverse technical expertise is required to use those tools and data to make sound business decisions. Users need extensive help to find data, people, analytic components, and solutions, to perform exploratory analysis, and to build analytic solutions for their business problems. Capturing information is not enough. We must make data and analytics consumable, lowering skill and expertise barriers to empower business users to leverage the tools of data science. We will do this by providing a rich and supportive environment, in which data-driven decision-making becomes a conversation with data in an intelligent and social context. The environment provides pre-built analytics, data sets, infrastructure and the necessary expertise, allowing business users to find, prepare, and visualize data easily, leveraging others. work, and to share and communicate not only findings but the whole process with others through familiar social tools.

Bio: Dr. Aya Soffer is Director of Big Data Analytics Research in IBM. In this role, Dr. Soffer leads the world-wide research strategy in Big Data and works with IBM.s product groups and customers to drive Research innovation in to the Market. Dr. Soffer leads IBM Research's Massive Scale Analytics Big Bet, an effort to develop new technologies to facilitate making smart decisions from information at very large scales. This is a world-wide effort across seven Research labs focusing on extracting insight from the vast amount of information gathered from heterogeneous sources and make it readily available to decision makers where and when they need it. In the Haifa Research Lab, Dr. Soffer is the Department Group Manager of the Big Data Analytics department that focuses on turning information into assets with emphasis on unstructured information including new forms of social media and and multimedia data. Many of these innovations are already included in IBM product and services offerings.

Dr. Soffer received her MS and PhD degrees in computer science from the University of Maryland at College Park in 1992 and 1995, respectively. Before joining IBM in 1999, she was a research scientist at Goddard space flight center, where she worked on digital libraries for earth science data. Dr. Soffer has published over 40 papers in referred journals and conferences and filed over 15 patents.