Zerara Mohammed

Zerara Mohammed is a Researcher and Project Unit Manager at HES-SO Geneva, specializing in Applied Mathematics and Data Science. Their work focuses on machine learning applications in spectroscopy, nanotechnology, and biomedical imaging. Key projects include combining deep learning with Raman spectroscopy for bacterial detection in infant formula milk and developing hyperspectral image classification methods funded by an international organization.

Education: Master's in Applied Mathematics - Data Science from Cergy Paris Université (in collaboration with PSL/Paris Dauphine University).

Research Interests: Machine learning algorithms for spectral analysis, miniaturized spectrometer design (Nature Communications 2024), computational chemistry (e.g., spin-crossover complexes), and applications in material science. Notable contributions include a 2023 IEEE review on miniaturized spectrometers and foundational work on logP prediction models in the 2000s.

Grants & Projects: Ongoing collaborations include a 2022-2023 project on Enterobacter sakazakii detection and hyperspectral anomaly detection research. Previously led studies on chemical pressure effects in metal complexes (Chimia 2002) and Rhea biochemical reaction database updates (Nucleic Acids Res. 2015).

Labs/Teams: Primary researcher in HES-SO teams for computational spectroscopy and nanotechnology projects. Collaborates internationally on biomedical sensor development and material science applications.