My name is Lou Lerren Chan Curacha. I recently completed a Master’s degree in Geography with a concentration in Remote Sensing at the University of Zurich (UZH). I am currently a PhD researcher on the FOURIER project, hosted by Infra Plan consulting d.o.o. (INFRAPLAN). I bring a multidisciplinary background in remote sensing, GIS, photogrammetry, and machine/deep learning, developed through research assistant roles at UZH and ETH Zurich and complemented by industry experience. In my master’s thesis, I quantified land surface temperature changes associated with land cover change using satellite observations, with an emphasis on interpretable, decision-relevant insights from large-scale Earth observation data. I showed that transitions such as deforestation and urbanization correspond to distinct cooling and warming patterns at the global scale.
My PhD research focuses on training AI based infrastructure health monitoring algorithms using large-scale synthetic data to address the scarcity of labeled field observations of damage and degradation events. The project develops procedures for generating synthetic multi-time series datasets by combining digital twin simulations grounded in engineering models and incorporating uncertainties, pre-stress effects (e.g., aging), external loading, failure response, and recovery, together with generative adversarial networks (GANs), to scale these simulations into large training datasets. These datasets are then used to train and validate AI algorithms that infer physical degradation parameters from multi-time series sensor data.
I was drawn to the FOURIER project because it integrates AI, modeling, and monitoring to produce practical, decision-relevant tools for resilient infrastructure management. Its interdisciplinary structure and strong real-world orientation align closely with my research interests, my background in geospatial analytics and my current focus on robust data-driven methods for infrastructure monitoring under uncertainty.
