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Collaborative Modeling, Simulation, and Analytics with Splash
April 27, 2015 @ 6:30 pm
Peter J. Haas, IBM Almaden Research Center
*** Bring ID (e.g. Driver’s License) for eBay Security ***
6:30 Doors Open, Food & Networking
*** Please arrive by 7 PM due to Security ***
In the past few years, research around (big) data management has begun to intertwine with research around predictive modeling and simulation in novel and interesting ways. Driving this trend is an increasing recognition that information contained in real-world data must be combined with information from domain experts, as embodied in simulation models, in order to enable robust decision making under uncertainty. This convergence of data management and simulation is exemplified by the IBM Splash prototype framework for combining existing heterogeneous simulation models and datasets to create composite simulation models of complex systems. Such composite modeling across a broad range of disciplines, though highly challenging, is needed to support sound and robust decision making around complex issues such as population health and safety. Splash combines and extends technologies for simulation, information integration, and massive scale analytics. We give an overview of the Splash system, highlight some interesting technologies that we have developed in the course of the project, and point to some of the open questions in the new and evolving research area of collaborative modeling, simulation, and analytics.
Peter J. Haas is a Principal Research Staff Member at the IBM Almaden Research Center and a Consulting Professor of Management Science and Engineering at Stanford University. He is an IBM Master Inventor, ACM Fellow, and former President of the Institute for Operations Research and Management Science (INFORMS) Simulation Society. His work focuses on the interface between probability, statistics, and computer science, and has encompassed stochastic simulation methodology, machine learning, and technology for information management and analytics from DB2 through MapReduce and Spark. Awards include an ACM SIGMOD 10-year Best Paper Award, IBM Research Outstanding Technical Achievement Award, and INFORMS Simulation Society Outstanding Simulation Publication Award. He has served on a variety of editorial boards and program committees, and is the author of over 100 conference publications, journal articles, and books.
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