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DFG Research Unit 5336 “Learning To Sense”
The Confluence of Machine Learning and Sensor System Development
The German Research Foundation (DFG) has selected L2S as one out of eight research units in Germany that conduct dedicated fundamental research on artificial intelligence along with an interdisciplinary partner field, in this case sensor system development. The project is situated at ZESS where it can build upon more than 30 years of experience in the field of fundamental and application-oriented, interdisciplinary, research.
Sensor System Development
Developing and optimising the next generation of CMOS Sensors, THz imaging systems, and 3d microscopes taylored to specific automatic data analysis applications.
Sensor System Simulation
Developing faithful simulators of the three sensor modalities in order to know how the recorded data changes as the design parameters of a sensor system are changed.
Machine Learning
Developing new approaches to jointly optimize for the sensor system design along with neural networks parameters.
![The PIs of the DFG-Research Unit "Learning to Sense" at ZESS. Front, ltr: Prof Ivo Ihrke, Prof Bhaskar Choubey, Spokesperson Prof Michael Möller, rear, ltr: Prof Volker Blanz, Prof Andreas Kolb, Prof Margret Keuper. Not pictured: Prof Peter Haring Bolívar [Photo: Sascha Hüttenhain]](http://www.zess.uni-siegen.de/wp-content/uploads/2024/10/DFG-Research-Unit-Learning-to-Sense-at-ZESS_Copyright-Sascha-Huettenhain-1024x729.jpg)
Front, ltr: Prof Ivo Ihrke, Prof Bhaskar Choubey, Spokesperson Prof Michael Möller, rear, ltr: Prof Volker Blanz, Prof Andreas Kolb, Prof Margret Keuper. Not pictured: Prof Peter Haring Bolívar [Photo: Sascha Hüttenhain]
![DFG Research Unit Learning to Sense in Mannheim, March 2024 [Foto: Jan Soehlke/ZESS, University of Siegen]](http://www.zess.uni-siegen.de/wp-content/uploads/2024/10/DFG-Research-Unit-Learning-to-Sense-in-Mannheim_Copyright_Jan-Soehlke_ZESS-University-of-Siegen-1-1024x656.jpg)
For a period of four years (with a possible extension by another four years) a team of seven chairs from Electrical Engineering and Computer Science will closely collaborate on the question how to jointly develop and optimize image sensor system hardware and machine learning approaches to reach optimal performances for specific applications. Our research unit focusses on the development of novel CMOS sensors for visible light, optimal 3d microscopic setups, and optimal sub-surface THz imaging technology along with dedicated machine learning approaches in an application-specific setting.