Sebastian Basterrech

Sebastian Basterrech is a Postdoctoral Researcher (Researcher) in the Department of Civil and Mechanical Engineering at the Technical University of Denmark (DTU), actively contributing to interdisciplinary research at the machine learning-engineering interface. His work spans materials science, energy systems, and climate science with strong international collaborations.

Research interests focus on:

• Physics-informed machine learning for additive manufacturing process optimization
• Time series forecasting of seasonal extremes and energy consumption using AutoML
• Topological data analysis for environmental landscape shift detection
• Neural network-enhanced materials characterization via instrumented indentation

Recent publications (2024-2025) reveal a cohesive trajectory: integrating domain physics with data-driven models across diverse applications. Key trends include advancing continual learning for non-stationary energy data, developing topology-based change detection for environmental monitoring, and creating hybrid experimental-ML frameworks for materials science—demonstrating exceptional methodological versatility.

Active collaborations with institutions across Europe and South America support this work, with consistent output in high-impact journals and conferences. The research group maintains computational resources through DTU's infrastructure, accessible via http://www.construct.dtu.dk, focusing on real-world engineering solutions aligned with sustainability goals.