Machine learning techniques from Imperial and BASF advance experimental design

Earlier this year Dr Detlef Kratz (President, Group Research at BASF) and Profes
Earlier this year Dr Detlef Kratz (President, Group Research at BASF) and Professor Ian Walmsley (Imperial’s Provost) signed a new framework agreement, marking a new phase in the strategic partnership. Photo: Fergus Burnett
Earlier this year Dr Detlef Kratz (President, Group Research at BASF) and Professor Ian Walmsley (Imperial's Provost) signed a new framework agreement, marking a new phase in the strategic partnership. Photo: Fergus Burnett Imperial and chemical company BASF will reveal new techniques for optimising experimental design at leading machine learning conference NeurIPS. Three papers outlining new machine learning techniques that address important needs in the chemical industry have been judged ground-breaking enough to win acceptance at the NeurIPS conference, one of the most competitive international venues for research in machine learning. At BASF we see digitalisation as key for strengthening our role as a leader in R&D in the chemical industry, and addressing the industry's pressing needs for sustainability and resilience. Dr Christian Holtze BASF - The techniques, developed as part a wide-ranging partnership between Imperial and BASF , are designed to help research and development (R&D) scientists in chemistry and other fields improve industrial processes with minimal trial and error by predicting which experiments will return the most useful results. They could also help automate the R&D process. These advances are expected to help accelerate the development of innovative new chemical products and more efficient and sustainable methods of manufacturing.
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