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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
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Posts
Using AWS Lambda with custom container image for Machine Learning inference
Published:
Using serverless offerings from cloud providers has many advantages like no provisioning and managing of servers and automatic scaling. But serverless functions also come with some limitiations like complicated deployment package management, limited package size and limited RAM. Especially if you want to use lambda functions for Machine Learning model inference, these limitations can be quite restrictive. AWS also recognized that so since December 2020 they extended their lambda offering by container image support. In this post I’ll describe my experiences using aws lambda with custom container images and describe the ups and downs of this approach.
IoT platform switching: From Conrad Connect to iobroker
Published:
In our research project Smart Air we were forced to get rid of Conrad Connect IoT platform. Why? To our annoyance they just shot it down - and announced the shut down just one month in advance! In this post I’ll describe what had to be done to migrate to the open source IoT platform iobroker and why I’m actually happy about this forced IoT platform switching.
portfolio
Portfolio item number 1
Short description of portfolio item number 1
Portfolio item number 2
Short description of portfolio item number 2
publications
Paper Title Number 1
Published in Journal 1, 2009
This paper is about the number 1. The number 2 is left for future work.
Recommended citation: Your Name, You. (2009). "Paper Title Number 1." Journal 1. 1(1). http://academicpages.github.io/files/paper1.pdf
Paper Title Number 2
Published in Journal 1, 2010
This paper is about the number 2. The number 3 is left for future work.
Recommended citation: Your Name, You. (2010). "Paper Title Number 2." Journal 1. 1(2). http://academicpages.github.io/files/paper2.pdf
Paper Title Number 3
Published in Journal 1, 2015
This paper is about the number 3. The number 4 is left for future work.
Recommended citation: Your Name, You. (2015). "Paper Title Number 3." Journal 1. 1(3). http://academicpages.github.io/files/paper3.pdf
talks
How Data Science was used to optimize energy consumption of transalpine oil pipeline
Published:
In this talk, I give some insights about a Data Science project I did at TAL Group. TAG Group is a pipeline operator that transports crude oil from the Mediteranean Sea all over the alps to different rafineries in Austria, Germany and Czech Republic. Therefore many pumps are operating all along the pipeline and in this project we identified inefficies and its root causes using Machine Learning.
Making Sense out of Sensor Data - Data Science at TAL-Group
Published:
In this talk, I give some insights about a Data Science project I did at TAL Group. TAG Group is a pipeline operator that transports crude oil from the Mediteranean Sea all over the alps to different rafineries in Austria, Germany and Czech Republic. Therefore many pumps are operating all along the pipeline and in this project we identified inefficies and its root causes using Machine Learning.
Kurz KI an der Pipeline
Published:
In this podcast, I give some insights about a Data Science project I did at TAL Group. TAG Group is a pipeline operator that transports crude oil from the Mediteranean Sea all over the alps to different rafineries in Austria, Germany and Czech Republic. Therefore many pumps are operating all along the pipeline and in this project we identified inefficies and its root causes using Machine Learning.
Produktdigitalisierung in der Industrie - Wann sollte ich eigentlich an Data Analytics & AI Denken?
Published:
In this talk, I describe my view on typical problems that occure during product digitalisation in industry companies. Especially, I give my optinion on on the “right” point in time to think about Data Analytics and Artificial Intelligence during the product digitalization cycle.
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Data Science - Der Weg vom Sensor in die Cloud bis hin zur Endanwendung
Published:
In this talk at VDI conference, I describe different views on Data and Data Science depending if you are a plant operators or a plant manufacturer. Furthermore, I give some insights about IT Infrastructure that brings sensor data from machines into the cloud in order to provide data driven services. Finally, I show my view on how Data Science is evolving in copounding technologies.
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Anomalieerkennung bei der KSB: Vom Experiment zum Produktiveinsatz von Maschine Learning Modellen
Published:
In this talk at VDMA Praxistag, I describe the different steps that are necessary to get from experimental phase of a digital Product to productive use of machine learning models. The talk is based on my project experiences at our customer KSB, that introduced a Digital Product for its pumps.
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Praxisbericht: ML Ops für Condition-Monitoring Anwendungen
Published:
In this talk I worked out some talkeaways regarding MLOPS from one of our customer projects: Firstly, a clear understanding of the importance of MLOps for the long-term operation of machine learning models. Secondly, I gave Insight into which problems AWS Sagemaker can and cannot solve (model registry, multi-model endpoints, serverless endpoints,…). Finally, I conveyed an understanding of a service architecture that promotes seamless collaboration between data science and operations teams.
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.