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A global automobile parts manufacturer, a client of NineSigma, believes credible air cleaning technology is key to comfortable automobile experience; particularly deodorization and sterilization technology will become increasingly important. The Client has promoted research and development on their own, however they now face a challenge to find a suitable solution to ensure both deodorization/sterilization and safety in a short time. Given that technological development of such air cleaning is done globally, the Client decided to find a partner to further accelerate the development speed, which lead to this offering.

The SD2 program aims to develop data-driven methods to accelerate scientific discovery and robust design in domains that lack complete models. Engineers regularly use high-fidelity simulations to create robust designs in complex domains such as aeronautics, automobiles, and integrated circuits. In contrast, robust design remains elusive in domains such as synthetic biology, neuro-computation, cyber, and polymer chemistry due to the lack of high-fidelity models. SD2 will develop tools to enable robust design despite the lack of complete scientific models.