Summary
Seyed Sajjadinia is a Senior Data Scientist based in Trentino-Alto Adige with seven years of experience bridging engineering, biomechanics and industrial AI. He specializes in machine learning for time-series and operational modal analysis, building digital twins, surrogate models and interpretable AI while applying model-order-reduction and Bayesian filtering for structural monitoring. Comfortable across Python, Fortran and SQL, he combines numerical methods and signal processing with practical deployment—shipping automated modal analysis and anomaly-detection pipelines in industry. His PhD work blended graph neural networks and inverse finite element methods, reflecting a rare fluency in both deep learning and continuum mechanics. Colleagues rely on him for technical mentorship, mathematical development, and turning complex physics into production-ready data solutions.
7 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Free University of Bozen-Bolzano
Master's degree, Biomedical Engineering, Master's degree, Biomedical Engineering at Iran University of Science and Technology
English, Persian, Italian