Big data tools for physics and astronomy

Monday, 19 June 2017 - 09:00
Other Institutes

        : Sessions
    /     : Talks
        : Breaks
19 Jun 2017
AM
09:00 Watch this space: emerging trends and techniques that could transform physics and astronomy - Kyle Stuart Cranmer (New York University (US))   ()
09:45 Inter-experimental Machine Learning at the LHC - Dr Sergei Gleyzer (University of Florida (US))   ()
10:15 Large Scale Machine Learning in Astronomy - Gieseke Fabian   ()
11:05 GRID Processing of LOFAR spectroscopic and imaging surveys - Natalie Danezi (SurfSara)   ()
11:35 HPC Processing and Deep Learning Techniques for Classifying Radio Bursts - Joeri van Leeuwen   ()
PM
12:05 Collaborative machine learning for science with OpenML - Prof. Joaquin Vanschoren (TU Eindhoven)   ()
14:00 Amsterdam Data Science - Maarten de Rijke   ()
14:30 eScience - Wilco Hazeleger   ()
15:00 SurfSara - Maithili Kalamkar   ()
16:00 Determining the origin of the Galactic Center excess using convolutional neural networks - Mr Hendriks Luc   ()
16:15 Scaling up in complexity - Zahari Dimitrov Kassabov Zaharieva (University of Turin)   ()
16:30 Good fits of gamma-ray data with high-dimensional modelling - Dr Emma Storm (UvA)   ()
16:45 Generalizing LHC limits on Supersymmetry with Machine Learning - Mr Bob Stienen (IMAPP, Radboud University Nijmegen)   ()
17:00 Wrap-up and next steps - Juan Rojo (VU Amsterdam and Nikhef)   ()