Research profile S.R.N. (Simon) Gazagnes.

S.R.N. (Simon) Gazagnes 

Simon graduated on 1 October 2021, Vast and fast data in the era of large astor physics and particle physics experiments.

Simon Gazagnes was a PhD candidate within the DSSC (2017 - 2021). He is supervised by Michael Wilkinson (BI), Leon Koopmans (Kapteyn) and Nasser Kalantar-Nayestanaki (KVI-CART) in the multidisciplinary project “[VF]ast Data”.

This project aims at developing and optimizing new algorithms to process the huge amount of data that are too large to process on a single node, or handle  data-acquisition having a data rate so high that it makes challenging the storage of all the information recorded. In the first case, finding the good scaling is mandatory to achieve an efficient processing, as processing one billion of 10 Megapixel images is considerably different from processing one thousand 10 Terapixel images. In the second case, methods able to detect and select only the desired information during the data acquisition need to be implemented.

These new methods for Vast and Fast data problems will be applied in two different fields, astrophysics and particle physics. In the Kapteyn Astronomical Institute, the Epoch of Reionization project aim at detecting the first signal from the reionization of the universe using the large radio telescope LOFAR. This instrument creates images-cubes (2 dimensions of space, one dimension of frequency) with a billion (or more) voxels of the sky, including different type of features, like compact and very diffuse structures, at vastly different scales. These large data  need to be processed through a multi-scale analysis to capture the smallest details of interest.
In the KVI-CART center, researchers are looking for new particles based on high energy collisions using a particle accelerator. The detection of these particles require a rapid-data acquisition method to detect and keep track of the rare events throughout the acquisition.

The proposed methods will use mathematical morphological tools developed in the JBI, and will be implemented on distributed CPU and GPU-based architecture.

Simon Gazagnes’s backgroung is on electrical engineering, signal and image processing, and astrophysics. He had a first experience in image processing in the MORPHEME team in Sophia Antipolis (France), developing a new method (SMLM-CEL0) to perform molecule localization related the photo-activated localization microscopy in biology. He then joined the STARBUST team in the Geneva Observatory to work on modelling and data analysis of galaxies spectra emitting ionizing photons.

Simon Gazagnes is interested in a wide range of fields, from the particle physics to the formation of the Universe, through neuroscience and biology. He aims at developing multi-disciplinary methods that could be used to meet the data processing challenges that these domains will face in the coming years.