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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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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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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Living and working with robots changes people. How can artificial intelligence (AI) be innovative whilst respecting social values at the same time? In the person of Aimee van Wynsberghe, Bonn is gaining one of the world’s leading researchers in AI and robot ethics.
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Whether you think in terms of autonomous drones, self-driving cars or robots that care for the sick or support older people, machines constantly have to respond to new and unexpected situations. Not all of these situations can be predicted and programmed with the appropriate default response. Machine learning and robots that learn from their experience are the solution.
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Ingmar Weber conducts research at the interface of the social sciences and artificial intelligence. He uses statistical methods to analyse data generated by social platforms in order to make statements about political polarisation or to model migration movements.
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The human gait – which usually looks intuitive and natural – is an extremely complex form of locomotion. When you are walking, you are constantly defying gravity and have to keep fine-tuning your balance. This is precisely why the upright gait is still difficult to replicate technically. Mechanical engineer Heike Vallery studies gait and balance and develops applications in hardware and control technology for the rehabilitation of people with reduced mobility.
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By developing and applying differential dynamic logics, André Platzer has made a crucial contribution to testing the security of cyber-physical systems in, for example, traffic, aviation and shipping as well as robotics.
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