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Expertise Deep Learning, Computer Vision, Domain Adaptation, Generative Modeling Open Projects: Test-Time Domain Adaptation for Anomaly Detection: SiROP link for detailed information Han obtained her master's degree in Geomatic from the Federal Institute of Technology in Zürich (ETHZ). Before joining IMOS Lab - EPFL, she focused on computer vision with a particular interest in domain adaptation & style adaptation. During her Ph.D. study, she will explore more in the field of domain adaptation with its application in industrial data sets. ResearchDomain Adaptation Domain adaptation for anomaly detection & fault diagnosisGenerative Modeling Generative adversarial network, diffusion model, generative model-based domain adaptation & style adaptation Teaching & PhDCIVIL-332 Data Science for infrastructure condition monitoring Course BookCIVIL-426 Machine learning for predictive maintenance applications Course Book Awards ETH Medal Master's Thesis: Robust Object Detection with Efficient Labeled Data Factory 2022 Esri Young Scholar Award 2021 HoloInspect: A Mixed Reality BIM software on HoloLens 2021
Please note that this is not a complete list of this person’s publications. It includes only semantically relevant works. For a full list, please refer to Infoscience.