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Dan Jaeggi
Daniel graduated with a MEng in Engineering from Cambridge University in 2001, specialising in aeronautical engineering. During his studies he was sponsored by British Aerospace Airbus in Filton, Bristol, and worked there on a number of placements.
Following this, he moved to Germany, working first as an Engineering Consultant with Berata GmbH in Munich, and then as a software programmer for a bio-informatics research group in Heidelberg, a role that exposed him to the demands of large-scale parallel scientific computing. A further job in a similar research group in Barcelona, Spain, lead him to apply for a PhD back in Cambridge, which he started in 2003.
Daniel's PhD work was on Robust Design Optimization. This looks at ways of incorporating the effects of uncertainty, variability, and modeling errors into the design process, and generating designs that exhibit less sensitivity to these effects - this can lead to both higher performance (taking into account real-world effects) and lower technical risk (from a commercial viewpoint). He investigated the potential for robust designs in a CFD-based aerodynamic design process, using a diffuser design study which was coupled to surrogate models (Radial Basis Function, Kriging, Support Vector Machines) and a novel multi-objective meta-heuristic optimization algorithm.
Daniel paused his PhD to work for CFS for a year in 2005/6 with our Motorsport clients.
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