Analysis of large datasets are crucial in Particle Physics, just like in Nuclear Physics, Cosmology and other Physical Sciences, for interpreting results of ongoing (LHC) and future experiments.
Over the last few years, rapid progress in AI have enabled our smartphones, social networks, and search engines to understand our voice, recognize our faces, and identifiy objects in our photos with very good accuracy. These dramatic improvements are due in large part to the emergence of a new class of machine learning methods known as Deep Learning.
In order to promote an interdisciplinary/multidisciplinary approach, a half-day workshop on Big Data and Deep Learning Techniques was co-organized by the Institute of Nuclear and Particle Physics (INPP) and the Institute of Informatics and Telecommunications (IIT) at the National Centre for Scientific Research, Demokritos, with invited speakers from CERN.
Two presentations were given by researchers from SKEL Lab of IIT, the former was titled “Machine Learning for Complex Event Recognition” by Dr. N. Katzouris, while the latter “Complex Event Recognition at NCSR-D” by Mr. E. Alevizos.
Visit the event’s webpagehttps://indico.cern.ch/event/705941/