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Clustering is an unsupervised machine learning method grouping data samples into clusters of similar objects. In practice, clustering has been used in numerous applications such as banking customers profiling, document retrieval, image…
The unprecedented volume of data from the Square Kilometre Array (SKA) telescopes will require the implementation of robust and solid strategies for efficient data processing and management. In this context, the SKA Regional Centre Network…
Scanning Transmission Electron Microscopy (STEM) coupled with Electron Energy Loss Spectroscopy (EELS) presents a powerful platform for detailed material characterization via rich imaging and spectroscopic data. Modern electron microscopes…
Clustering analysis has received considerable attention in spatial data mining for several years. With the rapid development of the geospatial information technologies, the size of spatial information data is growing exponentially which…
We present a new application of deep learning to infer the masses of galaxy clusters directly from images of the microwave sky. Effectively, this is a novel approach to determining the scaling relation between a cluster's Sunyaev-Zel'dovich…
The Swiss National Supercomputing Centre (CSCS) has a long-standing tradition of delivering top-tier high-performance computing systems, exemplified by the Piz Daint supercomputer. However, the increasing diversity of scientific needs has…
The advent of experimental science facilities-instruments and observatories, such as the Large Hadron Collider, the Laser Interferometer Gravitational Wave Observatory, and the upcoming Large Synoptic Survey Telescope-has brought about…
Computer Technology has Revolutionized Science. This has motivated scientists to develop mathematical model to simulate salient features of Physical universe. These models can approximate reality at many levels of scale such as atomic…
The SPECULOOS (Search for habitable Planets EClipsing ULtra-cOOl Stars) project aims to detect temperate terrestrial planets transiting nearby ultracool dwarfs, including late M-dwarf stars and brown dwarfs, which are well-suited for…
Image-guided robotic interventions involve the use of medical imaging in tandem with robotics. SlicerROS2 is a software module that combines 3D Slicer and robot operating system (ROS) in pursuit of a standard integration approach for…
High-Performance Computing (HPC) platforms enable scientific software to achieve breakthroughs in many research fields such as physics, biology, and chemistry, by employing Research Software Engineering (RSE) techniques. These include 1)…
The Smart Grid (SG) is a Cyber-Physical System (CPS) considered a critical infrastructure divided into cyber (software) and physical (hardware) counterparts that complement each other. It is responsible for timely power provision wrapped by…
The Slicer Combined with Array of Lenslets for Exoplanet Spectroscopy (SCALES) is a $2-5~\mu$m, high-contrast integral field spectrograph (IFS) currently being built for Keck Observatory. With both low ($R\lesssim250$) and medium…
Deep learning increasingly relies on massive data with substantial storage, annotation, and training costs. To reduce costs, coreset selection finds a representative subset of data to train models while ideally performing on par with the…
Scientific computing often requires the availability of a massive number of computers for performing large scale experiments. Traditionally, these needs have been addressed by using high-performance computing solutions and installed…
The design of Microprocessors Computer Architectures remains as a fundamental course in Computer Science and Computer Engineering. The technology and organization inside microprocessors have changed quite fast in the last twenty years. That…
IceCube is a one-gigaton instrument located at the geographic South Pole, designed to detect cosmic neutrinos, iden- tify the particle nature of dark matter, and study high-energy neutrinos themselves. Simulation of the IceCube detector and…
Sigma-profiles obtained from quantum-chemical calculations are key molecular descriptors for solvent selection, thermodynamic modeling, and data-driven molecular design. However, existing sigma-profile libraries are limited in size and…
HTCondor is a distributed job scheduler developed by the University of Wisconsin-Madison, which allows users to run their applications in other users' machines when they are not being used, thus providing a considerably increase in the…
Our work aims at using quantitative imaging tools to complement the limitation of noise encountered by high resolution fluorescence microscopy methods. Several cycles of fluorophore activation, imaging and deactivation produce a sequence of…