Dany Katamba Mpoyi
Postdoctoral Researcher @Politecnico di Bari
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WORK HISTORY
Postdoctoral Researcher @Politecnico di Bari
Contributed to R&D on design and testing methodologies for materials and vehicle components, emphasizingenergy eciency, CO2 reduction, and lightweight structure.• Performed mechanical characterization (static, fatigue, and impact tests) on chassis materials, collecting high-frequency experimental data and conducting numerical analysis (linear static and dynamic FEM simulations) tomodel the frame behavior under operational stresses.• Correlated experimental and numerical results to validate material models and identify critical structuralareas for potential lightweight remodeling.• Developed AI-based predictive frameworks using machine learning to model material behavior, support data-driven decisions, and optimize resistance/weight ratios in vehicle parts.• Contributed to the preparation of a scientific report.
EDUCATION
Institut Supérieur des Techniques Appliquées (ISTA/Kinshasa)
Bachelor's degree, Electromechanical Engineering
Institut Supérieur des Techniques Appliquées (ISTA/Kinshasa)
Master's degree, Mechanical Engineering
Politecnico di Bari
PhD in, Aerospace engineering and sciences
Politecnico di Bari
Doctor of Philosophy - PhD student, Aeronautical/Aerospace Engineering
ABOUT DANY KATAMBA MPOYI
I am a Mechanical Engineer with a PhD in Aerospace Engineering, specializing in signal processing, industrial condition monitoring, and artificial intelligence applied to mechanical systems and materials and structures.My academic journey is grounded in advanced research on acoustic emission analysis and non-destructive testing (NDT), while my professional experience includes three years at Bralima (Heineken Group), where I contributed to large-scale industrial projects such as the installation of a new packaging line and cross-functional technical fieldwork.I am deeply passionate about applying data science to solve real-world problems in engineering, manufacturing, and predictive maintenance. My work bridges academic rigor and industry relevance, particularly in areas like deep learning for signal and vibration analysis, damage detection, failure analysis, and smart diagnostics.I am a member of the Instrumentation and Measurement Society (IMS) and Istituto di Robotica e Macchine Intelligenti (I-RIM), and I\'m currently expanding my expertise in AI-powered decision systems, production intelligence, and mechanical data modeling.🧠 **Core Skills**: Signal & Acoustic Data Processing | Machine Learning | Deep Learning | Transfer Learning | NDT | Failure & Damage Analysis | Mechanical Systems | Python (scikit-learn, XGBoost, PyTorch, TensorFlow.)|Matlab | LabVIEW| Solidworks, Abaqus CAE **Languages**: French | English | Italian | Lingala | Congo Swahili Open to collaborations or roles in industrial data science, smart manufacturing, predictive maintenance, and AI-driven engineering systems.For more informations :
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