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Stefan Rilling

Research Associate
Fraunhofer Institute for Intelligent Analysis and Information Systems
Participates in 2 items

Dr. Stefan Rilling is a computer scientist working at the Fraunhofer Institute for Intelligent Analysis and Information Systems (IAIS) in Sankt Augustin, Germany. He studied computer graphics at the University of Koblenz-Landau, where he worked as a Research Associate in the Computer Graphics Group (2007 - 2011). In 2013 he obtained the PhD degree focusing on "Dynamic object behavior in the context of training simulations in the digital factory". Since 2011, he is a Research Associate in the IAIS of the Fraunhofer Institute, handling key roles across series or research projects.

He is currently working as researcher and coordinator of the H2020 funded project ATLAS and as researcher and project manager in several national and international research projects related to the fields of sensor-systems, data analysis and visualization. He was involved as researcher and project manager of the ERA-NET ICT-AGRI funded project S3-CAV, as work package leader in the H2020 funded project PROTON, as researcher in the in the EU FP7 funded project CIPRNet, and as researcher in the research project SeisViz3D funded by German Government Department for Environment, and as technical manager in the industrial consortium VRGeo.

Sessions in which Stefan Rilling participates

quarta-feira 20 outubro, 2021

Time Zone: (GMT+01:00) Paris
16:00
16:00 - 17:00 | 1 hour

The use of digital technologies can benefit farmers by improving productivity and sustainability. Farming sustainably can help to safeguard the environment, deliver economic profitability, and ensure social and economic equity for the farmer.  In this session, we share experiences on how digital technologies are helping to increase agricultural sustainability. 

quinta-feira 23 junho, 2022

Time Zone: (GMT+01:00) Paris
14:45
14:45 - 16:00 | 1 hour 15 minutes
Smart Agriculture: when tech meets and transforms farming2. IoT Markets and Applications in Industry, Agriculture & Smart Communities

Discuss and learn about data marketplaces, data models, standards, data governance and business models for data monetization.