Alex Ghaitanellis is a Data Science Lead with eight years of experience bridging rigorous fluid mechanics research and practical ML-driven product development, currently based in Singapore. Trained as a process engineer with a PhD in fluid mechanics, he developed specialized SPH models for multi-phase sediment transport and translated those simulation insights into ML applications such as CNN-based post-processing for experimental PIV images. He has moved between industry, academia and startup ecosystems—EDF R&D, NUS, Entrepreneur First and roles at Musiio, Yara and discovermarket—building a rare combination of domain modeling, product-minded data science and investor-facing communication. At discovermarket he now leads data science and sustainable risk management, applying physics-informed thinking to commercial analytics and proposition design. Notably, his background in Lagrangian particle methods and self-taught ML enables him to tackle complex physical systems with both first-principles models and modern data-driven tools.
7 years of coding experience
4 years of employment as a software developer
Engineer’s Degree, Energy, Thermodynamics, Fluid Mechanics, Engineer’s Degree, Energy, Thermodynamics, Fluid Mechanics at Université de Technologie de Compiègne
Certificate course, Artificial Intelligence: Implications for Business Strategy, Certificate course, Artificial Intelligence: Implications for Business Strategy at MIT Sloan School of Management
Master’s Degree, Fluid mechanics, Master’s Degree, Fluid mechanics at Université Paris Sud (Paris XI)
Doctor of Philosophy (Ph.D.), Fluid mechanics - Numerical simulations - Sediment transport, Doctor of Philosophy (Ph.D.), Fluid mechanics - Numerical simulations - Sediment transport at Université Paris-Est
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