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PROGRAM
How should we teach data science to the future generation?
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Software infrastructures for teaching at scale
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Applied Chemonmetrics – an engaging 20-minute challenge based on spectral data
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Networks, data, society and AI
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Level up your data & life science lab’s reproducibility
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Resource-aware machine learning
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Clinical predictive modeling: closing the gap between data science and clinical research
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Unlocking the digital academic talent pool potential to accelerate entrepreneurship and innovation
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More user involvement now – how may science contribute?
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Selv-supervised learning from time series
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AI, human rights and regulation: challenges and opportunities around the AI-Act
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Trends in algorithms research in Denmark
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Moderator: David Budtz Pedersen, Dept. of Communication and Psychology, AAU
Forum on Embedded AI
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Bayesian methods for uncertainty quantification
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Supercharge your causal inference with machine learning
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What lessons are AI researchers re-learning that HCI researchers have known about for years?
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A guided our through the Danish public data landscape
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Use of health-care data and AI – the need for collaboration between data scientists and healthcare professionals
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The dataethics of GenAI for public administration – challenges, opportunities and solutions
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Deeply qualitative AI
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From classroom to career: data science degrees and early career opportunities
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Overcoming the “Valley of Death” in AI-assisted preventive mental-health technology
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Hackathon: Unified data analytics with Apache Wayang
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Security by design
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Machine learning theory
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Transforming human-centric software engineering with generative AI: insights and innovations
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Verifiable, robust and explainable AI
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Synthetic data generation and augmentation for deep learning 2.0
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Future technologies for hybrid work
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XR visions: challenges and future directions of human-centered extended reality
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From brain circuits to the edge AI: Active inference of movement computing
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Fair division – Economics, computational social science, and AI
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Equity and inclusion in genomic studies: unravelling the complexities
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Drug discovery in the era of big data: AI vs. regulation
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Data management aspects of analytics
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