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Alexander von Humboldt Professorship for Artificial Intelligence 2021

Angela Schoellig

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.

  • Nominating University: TUM Munich
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Robotics and artificial intelligence

How can we push back the limits of machine learning? And, at the same time, what limits do we need to set to robots’ autonomous decision-making to prevent them from becoming a threat. Angela Schoellig is searching for the answers. She conducts her research at the University of Toronto on robotics, controls and machine learning, working both theoretically and on practical applications: with her self-driving cars, for instance, she has won several competitions. At TUM Munich she will advance the development of safer, more efficient service robots for the future. Industrial collaborations with aerospace, transport and energy companies are set to support extensive, practice-related experiments.

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Angela Schoellig at the University of Toronto

Brief bio

After completing her university education at the University of Stuttgart (engineering cybernetics) and Georgia Institute of Technology, Atlanta, United States, German-born Schoellig gained her doctorate at ETH Zurich in 2013. She then transferred to the University of Toronto, Canada, as an assistant professor in robotics (Canada Research Chair 2019). Since summer 2020, she has held an associate professorship there, working in parallel at the Vector Institute for Artificial Intelligence in Toronto. She has already received a raft of honours and funding, most recently the Canada CIFAR AI Chair awarded by the Canadian Institute for Advanced Research.