19 October 2020 to 7 December 2020
Zoom Webinar
Europe/London timezone

Industrial Data Science, Machine-, Transfer- and Federated Learning


Digitization and the Internet of Things (IoT) are transforming complete industries and allow the collection of large amounts of data of various types as machine data and sensor data. Data Science and Machine Learning offer the potential to generate enormous value and a competitive advantage. Typical industrial use cases include soft sensors, machine failure detection, predictive maintenance, and product quality assessment. One major challenge in Industrial Data Science is the Scalability of Machine Learning tasks due to the non-unified data format, varying data distribution and missing ground truth. Two approaches have the potential to overcome this challenge: Transfer Learning applying gained knowledge presented in a trained Machine Learning Model to a novel, but similar task and Federated Learning enables privacy preserving training of a Machine Learning Model across multiple decentralized edge devices allowing the collaboration across different companies. This talk will also address the challenges in Industrial Data Science and Machine Learning projects, what skillset is needed in a team and how to make sure the right problem is being solved.



Dr Jana Kemnitz is a Senior Data Scientist and Machine Learning Expert at the Distributed-AI-Systems Research Group, Siemens. Previously she was based at the Paracelsus Medical University in Salzburg and the ETH in Zurich where she specialised in deep learning for medical image analysis. During this time she was also a lecturer in signal- and image processing at the University of Vienna and worked as a machine learning specialist at the Chondrometrics GmBH. Dr Kemnitz graduated with a BSc and MSc in Electrical Engineering and Information Technology in 2015 followed by a PhD on Biomedical Image Processing, Statistics and Machine Learning in 2018. 

During her PhD she was awarded a Marie Curie Fellowship by the European Union, the DAdorW Future Prize by the German Academy of Osteological and Rheumatological Sciences, a visiting scholarship for the ETH Zurich by the German Society for Biomechanics and the Paracelsus Science Prize by the Paracelsus Medical University. Between 2018-2019 she was the vice chair of the Austrian Chapter of the Marie Curie Alumni Association.