Joana M. Warnecke is a research associate at the University of Cambridge, UK and the Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, Germany. She received her M.Sc. in Information Systems from the TU Braunschweig and is currently also a member of the executive committee of the Peter L. Reichertz Institute.

Her current research focuses on the health monitoring of babies in intensive care, developing algorithms for heart and breathing rate as well as the evaluation of video-based systems. As a PhD student she is also designing such sensor systems including machine learning approaches for multimodal sensor fusion for in-vehicle health monitoring.

Joana Warnecke on ResearchGate

Péter Kovács completed his habilitation in computer science in 2022; since then, he has been an associate professor at the Department of Numerical Analysis of Eötvös Loránd University in Budapest, Hungary. In 2012, he was a visiting researcher at the Department of Signal Processing, Tampere University of Technology in Finland. From 2018 to 2020, he was a postdoc at the Institute of Signal Processing, Johannes Kepler University Linz in Austria. In 2016, he was honored with the Farkas Gyula Prize in applied mathematics from the János Bolyai Mathematical Society. With over 40 published scientific papers, his work on Variable Projection Networks was recognized with the Hojjat Adeli Award by the International Journal of Neural Systems. He is a member of the public body of the Hungarian Academy of Sciences and the IEEE EMBS Young Professionals Committee.

His main research interests include signal and image processing, numerical analysis, system identification, and explainable AI. Currently, he is focusing on model-driven machine learning, which combines the advantages of traditional model-based signal processing algorithms with the data-driven discipline of deep learning.

Péter Kovács on ResearchGate

Patrique Fiedler studied electrical engineering and information technology at Technische Universität Ilmenau. He received his PhD in biomedical engineering in 2017. Subsequently, he moved to industry from 2017 to 2021 and held various development, project and product management positions at an internationally active medical technology manufacturer. Mr. Fiedler has been a visiting scientist at the University of Porto in Portugal and the University of Pescara-Chieti in Italy on several occasions . Since 2021, Patrique Fiedler returned to academia and currently is Junior Professor and Head of the group "Data Analysis in Life Sciences" at the Institute of Biomedical Engineering and Computer Science at Technische Universität Ilmenau. He also holds an Adjunct Assistant Professor position of the University of Texas Health Center, McGovern Medical School, Department of Pediatrics.

His research interests include data fusion, analysis of multimodal datasets and body sensor networks, as well as the exploration of novel sensor concepts for biomedical applications with a strong focus on neurosciences. Moreover, a focus is the development of online-capable analysis methods for close-to-sensor data processing.

Patrique Fiedler on ResearchGate

On Thursday, 29.02., we are offering you to visit the German Primate Center (DPZ) Göttingen with us, including a guided tour. The research of the DPZ includes basic biological and biomedical questions about the functioning of the body and about evolution and behavior by studying non-human primates. Included are also studies on and the preservation of primate populations in the wild and the improvement of the conditions of animal keeping.

Dr. rer. nat. Franziska Albers is part of the Academia Team at MathWorks and supports researchers in integrating machine learning with MATLAB into their research projects. She studied physics in Heidelberg and Münster and holds a PhD in neuroimaging from University Hospital Münster. Her research background is in multimodal fMRI and MR physics.

Did you ever wonder what is going on in an artificial neural network on a neural level? Did you ever wonder if we can build a real artificial neural network? In this workshop we will look at a mechanical model of an artificial neural network and understand how the distinct parts like neurons, activation functions, weights etc. function and connect. We will look at logical operators to examine how information flows in a network and how the network learns and adapts to different problems.

No computer programming knowledge is needed.

> Please register here for this workshop <

Axel Schaffland is a PhD student at Osnabrück University working on deep learning concepts and didactics of AI as well as image registration and rephotography. In his project "Mechanical Neural Network" he combines scientific modelling with hand-crafted modelling to make complex connections visible and touchable.