Session 3: Practice | Real-world AI use cases in hospitals and industry

Anna Fournier joined SDSC in 2019 as a Data Scientist focusing on industry collaborations. She completed her PhD in Bioinformatics at the University of Luxembourg, where she analyzed large-scale heterogeneous datasets and leveraged multiple disciplines: Statistics, Network Analysis, and Machine Learning. Prior to joining SDSC, Anna worked as a Data Scientist at Deloitte Luxembourg, with a focus on computer vision and time-series analysis. Currently, Anna is a Principal Data Scientist based at the ETH Zurich office, where she leads biomedical collaborations with industry partners. Anna works on a range of projects in the Health & Biomedical domain, including protein properties prediction, biomanufacturing optimization and statistical model evaluation.

Jean Louis Raisaro is Head of the Clinical Data Science Group at CHUV’s Biomedical Data Science Center and Tenure-Track Assistant Professor at Vaud University Hospital (CHUV) and the University of Lausanne (UNIL). He holds a PhD from EPFL and degrees in Biomedical Informatics and Bioengineering from the University of Pavia. His research focuses on safe, privacy-preserving AI/ML in healthcare, with contributions in federated analytics, secure cloud computing, anonymized data generation, and semantic interoperability. His work supports clinical decision-making and hospital optimization, and has been adopted by the Swiss Personalized Health Network. He has published in leading journals including Nature Communications, Nature Computational Science, JAMIA, and JMIR.

Snežana Nektarijevic joined the SDSC in 2021 on a mission to advance adoption of modern data driven solutions in the domain of public health care. She has a background in experimental particle physics with a Diploma from the ETH Zurich and a PhD from the University of Geneva. Snežana pursued fundamental research in the field of high energy physics at CERN for nine years, harnessing the power of machine learning and statistical methods to uncover the traces of new physics in petabytes of proton-proton collision data and to develop innovative particle identification algorithms. Since 2018, Snežana served as a Data Science consultant, supporting partners from industries such as manufacturing, insurances, compliance services and online platforms in creating business value from internal and external data.