Grégory Hammad is a research scientist and data practitioner with about a decade of experience turning petabyte-scale physics and medical imaging datasets into actionable insights, honed during a PhD and postdoctoral work on CMS at CERN and subsequent roles in data science. He builds robust analysis pipelines, statistical models and ML algorithms—often inventing bespoke background estimation and neural-network techniques—to extract rare signals from noisy collision data. His background spans C++ toolkits for particle physics, medical image processing stacks (SPM, FreeSurfer, FSL) and production data workflows, reflecting an ability to move models from research into operational systems. Based in Liège, he now focuses on Big Data analysis beyond academia, blending deep domain expertise in experimental physics with practical software engineering for high-throughput environments. An understated strength is his experience optimizing resource-constrained monitoring systems (memory/CPU profiling) for large-scale scientific instruments, which informs pragmatic, performance-aware solutions.
10 years of coding experience
12 years of employment as a software developer
CPGE, PCSI, CPGE, PCSI at Lycée Jacques Decour
Engineer’s Degree, Physics and modelling, Engineer’s Degree, Physics and modelling at Université de Strasbourg
CPGE, PC, CPGE, PC at Lycée Condorcet
Doctor of Philosophy (Ph.D.), Elementary Particle Physics, Doctor of Philosophy (Ph.D.), Elementary Particle Physics at Université libre de Bruxelles
BAC, S, BAC, S at Lycée Paul Lapie
Master’s Degree, Subatomic and astroparticle physics, Master’s Degree, Subatomic and astroparticle physics at University of Strasbourg
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Grégory Hammad - Research Scientist at CyclotronResearchCentre