Summary
Gian Paldino is a postdoctoral researcher and former PhD student at the Machine Learning Group of Université Libre de Bruxelles, specializing in multivariate time series forecasting, causal discovery, and concept-drift-aware learning. With dual master’s degrees (Politecnico di Milano summa cum laude and ULB magna cum laude), he blends strong theoretical grounding with practical systems experience in Python, TensorFlow/PyTorch, Kafka, Docker and AWS. His research has produced applied wins—outperforming industrial baselines in electricity flow forecasting and developing TD2C, an asymmetric conditional mutual information method for causal discovery in temporal data. He also built a Virtual Power Plant simulation that integrates synthetic data, MLflow and real-time streaming for grid optimization, showing his ability to move models toward production. An experienced teaching assistant, Gian pairs research depth with pedagogy and nine years of experience across academia and engineering. He’s particularly fluent at transferring methods from fraud detection and thermal-rating problems to energy systems and other non-stationary domains.
9 years of coding experience
Master's degree, Computer Science and Engineering, 110L/110 (eq. Summa Cum Laude), Master's degree, Computer Science and Engineering, 110L/110 (eq. Summa Cum Laude) at Politecnico di Milano
Master's degree, Computer Engineering, Grande Distinction (eq. Magna Cum Laude), Master's degree, Computer Engineering, Grande Distinction (eq. Magna Cum Laude) at Université libre de Bruxelles
Italian, English, French