Yaochu Jin is one of the leading pioneers of swarm robotics. In this special sub-area, he conflates his outstanding expert knowledge from various fields of computational intelligence. In Bielefeld, his expertise will be utilised to span the interdisciplinary bridge between AI research in the Technical Faculty and applications in bioinformatics and biotechnology in the newly established Medical Faculty.
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Both as one of the pioneers of the young discipline of the philosophy and ethics of artificial intelligence and an intermediary between topics in the humanities and technology, Vincent C. Müller is invited to help develop a guiding vision for “humane AI” in Germany.
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When mathematics meets AI, and optimisation, machine learning: mathematician Suvrit Sra’s fundamental works on methods of optimisation have made a seminal and incomparable contribution to the theoretical understanding and continued development of learning systems. TUM Munich wants to harness the Humboldt Professorship for Artificial Intelligence to expand its leading position in the field of artificial intelligence.
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The fundamental research conducted by computer scientist Stefanie Jegelka has led to a better understanding and optimisation of graph neural networks (GNNs) and made her name. In Munich, she is called upon to drive our theoretical understanding of machine learning and develop algorithms as well as trustworthy machine learning tools.
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The mathematician, statistician and computer scientist Sayan Mukherjee has produced crucial work in the still young field of topological data analysis through which imaging methods can be improved and predictions made about diseases. In Leipzig, Mukherjee’s expertise in the evaluation of biological data is set to open up new avenues in precision medicine.
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Whether in smartphones, traffic detectors or medical images – in many aspects of our everyday lives, we take high-quality images for granted, in some situations they have become vital. In Würzburg, Radu Timofte’s work on image enhancement will forge links between different research areas.
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Peter N. Robinson is a pioneer in the computer-assisted genome and phenotype analysis of genetic diseases. His major work has been the development of the Human Phenotype Ontology, which is now a standard tool used internationally to diagnose gene-related diseases. At the Charité in Berlin, Robinson is invited to develop algorithms for AI-based precision medicine.
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Alexander von Humboldt Professorship for Artificial Intelligence 2020 Peter Dayan At the University of Tübingen, Peter Dayan will connect informatics and neuroscience, also building bridges to clinica
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In most artificial intelligence (AI) applications, models learn from data that derives from a single information source. Additional data sources or so-called modalities can make AI models better and more reliable. An expert in multimodal learning, Marcus Rohrbach is set to become a Humboldt Professor for Artificial Intelligence in Darmstadt.
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By introducing innovative mathematical and bioinformatics methods in modelling and quantifying the impacts of climate change on public health, Joacim Rocklöv is on course to give fresh impetus to climate change research at the University of Heidelberg.
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