Data Quality Assessment for Industrial Data

Dynamic system monitoring using HMM, BAFO and Monte Carlo

Code and processed data accompanying the MSc thesis Integrating Dynamical Systems and Machine Learning for Modeling and Predicting Decay Across Wood Treatments, conducted at DTU in collaboration with the Danish Technological Institute.

Machine learning project to predict final steel temperature in industrial production processes.

Process Engineering simulation tools for industrial efficiency, mass-balance calculations, and system purity optimization.

Modèle de maintenance prédictive basé sur un Random Forest optimisé pour détecter les pannes industrielles (AI4I 2020)

End-to-end industrial data pipeline built on Medallion architecture (Bronze / Silver / Gold) — SCADA ingestion, anomaly detection and Azure Blob Storage export

Predictive maintenance analysis of Scania vehicle components using feature engineering, PCA, and association-rule mining.

Industrial stability and risk analytics framework for solar ingot puller operations using engineered variability, control deviation (SP–PV gaps), drift features, and interpretable regression modeling.

Simulation, stockage et visualisation de mesures industrielles en Python/MySQL

Motor failure prediction using real industrial data (ELGi internship)