Being historically a manufacturing company, Grundfos aims to bring digital transformation into its core business. This radical move not only bring challenges, but also energizes a wave of exploring/adopting state-of-the-art cloud computing, machine learning and AI technologies that impact different business domains. The new advances in computing platforms and machine learning services brings convenience to productionize industrial intelligent solutions. However, practical obstacles are hindering the scaling capability. This talk will take you to peek into some of the challenges that are faced in researching and deploying AI solutions within Grundfos. I will give you a picture on Grundfos’s digital initiatives landscape and our hands-on experience on scaling AI solutions that accelerates enterprise level adoption. Two concrete use cases in sales and marketing and supply chain management can shed some light on how business value, agile development, DevOps, data science, and MLops together enable success in business value creation. In particular, I will address the data challenge and the statistical methods, machine learning/deep learning techniques that are adopted to solve some real life challenges. About the speaker: Currently, Lishuai Jing is working with advanced statistical inference methods, machine learning and deep learning techniques, and general AI in the largest pump manufacturing company. He has a PhD diploma in statistical signal processing and wireless communication from aalborg university, Denmark. Before joining Grundfos, he was a researcher on 4G/5G and IOT communication technologies. He advocates data and AI-driven approach to improve business intelligence, operating efficiency, productivity and customer satisfaction.

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12:00 - 13:00 hs GMT+1

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Business Intelligence and Analytics
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