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Big data tools for physics and astronomy

Monday, June 19, 2017 - 9:00 AM
Other Institutes

        : Sessions
    /     : Talks
        : Breaks
Jun 19, 2017
AM
9:00 AM Watch this space: emerging trends and techniques that could transform physics and astronomy - Kyle Stuart Cranmer (New York University (US))  
9:45 AM Inter-experimental Machine Learning at the LHC - Dr Sergei Gleyzer (University of Florida (US))  
10:15 AM Large Scale Machine Learning in Astronomy - Gieseke Fabian  
11:05 AM GRID Processing of LOFAR spectroscopic and imaging surveys - Natalie Danezi (SurfSara)  
11:35 AM HPC Processing and Deep Learning Techniques for Classifying Radio Bursts - Joeri van Leeuwen  
PM
12:05 PM Collaborative machine learning for science with OpenML - Prof. Joaquin Vanschoren (TU Eindhoven)  
2:00 PM Amsterdam Data Science - Maarten de Rijke  
2:30 PM eScience - Wilco Hazeleger  
3:00 PM SurfSara - Maithili Kalamkar  
4:00 PM Determining the origin of the Galactic Center excess using convolutional neural networks - Mr Hendriks Luc  
4:15 PM Scaling up in complexity - Zahari Dimitrov Kassabov Zaharieva (University of Turin)  
4:30 PM Good fits of gamma-ray data with high-dimensional modelling - Dr Emma Storm (UvA)  
4:45 PM Generalizing LHC limits on Supersymmetry with Machine Learning - Mr Bob Stienen (IMAPP, Radboud University Nijmegen)  
5:00 PM Wrap-up and next steps - Juan Rojo (VU Amsterdam and Nikhef)  
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