Name: ML Operations and ML for Manufacturing
Start: 2020-05-14T19:30:00+02:00
End: 2020-05-14T21:30:00+02:00

🎉 We are happy to announce a new Virtual Meetup Series, starting on May 14! We could win two speakers for this Zoom event (link below).

Simon Müller will give insights into NEA-X's approach and use-cases on "Machine learning for manufacturing shop floors" (https://neaxplore.de).

Next, Kevin Stumpf will present his new San Francisco based startup Tecton (see https://tecton.ai) and their approach on ML operations.

🖋 Speaker Bios

Simon Müller studied at RWTH Aachen and completed his PhD at the WZL. While pursuing towards his PhD, he co-founded innoTecS to develop a production planning and control system, which has been widely adopted in the tool and die making industry. After the acquisition of innoTecS by the Neuman & Esser Group (NEA), Simon stayed with the team as the CTO of Neuman & Esser's digitalization branch: NEA X. In his talk, he will provide insights into NEA X's current approaches to apply machine learning to the manufacturing shop floor. His talk will highlight the challenges of different use cases, associated data pipelines and the influence of industrial IoT.

After finishing his Bachelor's degree, Kevin did his MBA at Stanford. He was CTO and co-founder of Dispatcher, an app based long-haul trucking brokerage. In 2016, Dispatcher joined Uber to help launch Uber's new freight division. He then went on to work on Uber’s Michelangelo machine learning platform as a tech lead and eng manager. He then left Uber to found Tecton with two other creators of Michelangelo. Tecton came out of stealth mode on April 28th 2020 and is backed with $25M by two of Silicon Valley's largest venture capital firms (Sequoia Capital and Andreessen Horowitz). Tecton focuses on MLOps, and provides the industry’s first data platform to build and productionize operational machine learning. It empowers data scientists to build ML features, deploy and serve them in production, and to do it at scale. In his talk, Kevin will discuss his learnings from building Michelangelo at Uber, the greatest technical challenges of operational ML today, and how Tecton's data platform helps solve these challenges.

✨ Image copyrights: Joshua Sortino @ Unsplash.

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Jermain Kaminski

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