Anomaly detection is a critical aspect of predictive maintenance in Industry 4.0, requiring the ability to detect unusual patterns or behaviors in data collected from sensors. NanoEdge AI Studio, an auto-ML software developed by STMicroelectronics, enables the creation and training of machine learning models that can perform anomaly detection fully on-device, without the need for any pre-trained models. In this presentation, we will study the algorithms behind NanoEdge AI Studio and demonstrate its potential applications of predictive maintenance in Industry 4.0.
Schedule
Timezone: PST
NanoEdge AI Studio: All On-Device Anomaly Detection for Industry 4.0
He HUANG, Data scientist
STMicroelectronics
Pierrick AUTRET, Artificial Intelligence Solutions Marketing Manager
STMicroelectronics
He HUANG, Data scientist
STMicroelectronics
He Huang is a data scientist and researcher with expertise in embedded Machine Learning. He holds a Ph.D. in electronics from INSA Toulouse in France, earned in 2015 and completed a post-doctoral research fellowship at Politecnico di Torino in Italy in 2016. As the former chief data scientist at French start-up Cartesiam from 2017, He played a pivotal role in the development of NanoEdge AI Studio, an innovative platform for on-device machine learning at the edge. Currently, he serves as senior staff data scientist at STMicroelectronics, where he continues to advance the field of machine learning and develop cutting-edge solutions for Industry 4.0 applications.
Pierrick AUTRET, Artificial Intelligence Solutions Marketing Manager
STMicroelectronics
Pierrick AUTRET has been Artificial Intelligence Solutions Manager in STMicroelectronics’ microcontroller division since 2019. With a master’s degree in engineering specializing in Embedded Systems from the Ecole Polytechnique and a master’s degree in marketing, Economics and Management from the IAE d’Aix-en-Provence, he began his career as Hardware Product Owner on the STM32 series before developing ST’s software offering.
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Schedule subject to change without notice.