Summary
Esteban Bautista is an assistant professor at Université du Littoral Côte d'Opale with eight years of experience at the intersection of machine learning, signal processing, and network science. His research, rooted in a PhD on graph-based semi-supervised learning, spans temporal and spatial data analysis, link streams, anomaly detection in temporal networks, and efficient algorithms for evolving graphs. He combines strong theoretical tools—Fourier and wavelet analysis, compressive sensing, dictionary learning—with practical implementation skills in Python, PyTorch, C/C++, and Matlab to deliver real-time and scalable solutions. Esteban’s work is notable for extending classical signal-processing ideas to graph-structured and time-varying data, enabling updates to ML solutions on large, rapidly changing networks rather than retraining from scratch. Based in St.-Omer, France, he balances academic publishing with hands-on algorithm and software development for practical data-analysis challenges.
8 years of coding experience
1 year of employment as a software developer
Universidad Nacional Autónoma de México (UNAM)
Doctor of Philosophy - PhD, Machine Learning, Doctor of Philosophy - PhD, Machine Learning at École normale supérieure de Lyon
Spanish, English, French