
The Hans Fischer Fellowship is for outstanding and talented early-career international scientists who intend to explore innovative, high-risk topics in their scientific research areas together with a Technische Universität München (TUM) Research Group.
My vision is to create a hub of diversified disciplines and scientific tools to improve the current traditional approach to predictive science for thermo-fluid applications. It is amazing to see how techniques from disparate fields, such as quantum mechanics and chaos theory, can help engineers design better engines.
Dr Luca Magri
The Bernard Lewis Fellowship was established to encourage high quality research in combustion by young scientists and engineers. Fellowships are awarded biennially during the International Symposium on Combustion.
Luca Magri is an aerospace engineer and theoretical/computational fluid dynamicist with majors in applied mathematics and physics. He is interested in multi-scale, multi-physical and inverse problems with relevance to energy conversion and aeronautical propulsion. His techniques are applied to a number of engineering problems, notably the design of safe, environmentally friendly and quieter aeronautical engines. He is currently a Royal Academy of Engineering Research Fellow and Hans Fischer Fellow at University of Cambridge, Department of Engineering with principal investigator (PI) status and a research team.
Luca says “My vision is to create a hub of diversified disciplines and scientific tools to improve the current traditional approach to predictive science for thermo-fluid applications. It is amazing to see how techniques from disparate fields, such as quantum mechanics and chaos theory, can help engineers design better engines. In the Hans Fischer Fellowship, my objective is to predict and control rare and extreme events, such as violent turbulent events in aero-engines, with machine learning and artificial intelligence algorithms. In the era of data science, the challenge for fluid dynamicists is to infer new mathematical predictive models from observations consistently with the physics that mother nature imposes!”