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Seminarium: Data analysis for Industry 4.0, Sala NE140, 29.03.2018, 14:15

Dodano 2018-03-27 o godzinie 16:06:03, autor Sylwia Wielechowska
Zapraszamy na seminarium "Data analysis for Industry 4.0", które poprowadzi Mike Holenderski, Ph.D.

Abstrakt: Smart factories today generate large amounts of data that can be used for estimating the wear of critical components, predict tool failures or identify their root causes. However, industrial data is often noisy or incomplete. This talk presents several challenges and examples of how machine learning techniques can be applied to industrial data for solving common problems in the context of Industry 4.0.

Miejsce: Sala NE 140 (sala Rady Wydziału)
Termin: 29.03.2018 (czwartek), godz. 14:15
Bio:
Mike Holenderski is an Assistant Professor at the Eindhoven University of Technology. He received his PhD in 2012 on the topic of real-time systems, but has been working on Machine Learning ever since. His current interest is Reliable Machine Learning, where the goal is to perform machine learning tasks, such as failure prediction or wear estimation, using real industrial data which is often noisy, corrupted, partially missing or coming from dynamic environments which change over time. He is interested in putting the theory in practice, which he has been doing through collaborations with industry.
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