On November 1, 2022, Prof. Dr. Marina Höhne was jointly appointed head of the department "Data Science in Bioeconomy" at the Leibniz Institute for Agricultural Engineering and Bioeconomy e.V. (ATB) and professor of "Digital Bioeconomy" at the Faculty of Mathematics and Natural Sciences of the University of Potsdam.
With the appointment of Prof. Dr. Marina Höhne, ATB is strengthening its competencies in the field of intelligent data analysis and artificial intelligence as well as in their application to issues of the bioeconomy. Machine learning methods support the intelligent automation of processes and are increasingly finding their way into the development of sustainable processes for a biobased circular economy. With the help of data science methods, usable knowledge for the intelligent management of agricultural and bioeconomic processes can be generated from the large volumes of data obtained by sensors.
"A strong motivation for my decision to join ATB was the opportunity to intensively combine my basic research with socially relevant topics such as animal welfare, environmental and climate protection," explains Prof. Dr. Marina Höhne. "Improving the methodological basis for the use of AI technologies in agriculture and their reliability in decision-making is a challenging task. First of all, it is important for me to better understand the highly complex bioeconomic processes. Therefore, I am very much looking forward to collaborating with colleagues from the different research areas at ATB."
Marina Höhne's research interests focus in particular on explainable artificial intelligence and the development of methods that enable a holistic understanding of AI models and their decisions. In this context, she focuses on the use of so-called Bayesian neural networks to obtain information about uncertainties in the decisions made by the AI system and display them in a way that is understandable to humans. "To use AI models in a reliable way, a certain transparency of the model is needed. We need to know how the AI model behaves before we use it to minimize the risk of wrong decisions", Marina Höhne explains her research approach. "For example in image recognition, individual decisions made by the system can be traced if the relevant areas in an image that contributed significantly to the AI system's decision are marked."
Marina Höhne (nee Vidovic) studied technomathematics in Aachen and Berlin. After graduating in 2012, she first worked on time series data and domain adaptation for prosthesis control at Ottobock in Austria. In 2014, she started her PhD on explainable AI at TU Berlin, where she graduated summa cum laude in 2017. After a year of parental leave, she returned to the Chair of Machine Learning at TU Berlin as a postdoc in 2018 and founded her own junior research group 'Understandable Machine Intelligence (UMI lab)' in 2020. The research group is still funded by the German Federal Ministry of Education and Research (BMBF) until the end of August 2024. Since 2021, Prof. Höhne has also been working at the Berlin Competence Center for AI, the Berlin Institute for the Foundations of Learning and Data (BIFOLD) and is an Associated Professor at the University of Tromsø in Norway.
"We are very pleased about the personnel reinforcement and the fresh wind for the research in the field of Data Science", underlines Dr. Uta Tietz, ATB's Administrative Director (acting). "With the appointment of Prof. Höhne as head of department, we can further strengthen the institute's expertise in this research field. In addition, it is a very welcome situation for ATB that with Prof. Höhne, her junior research group will also move to ATB until the end of the project period. So from January on, we can also welcome three new PhD students and student assistants from 'UMI lab' at ATB. In addition, the department will be strengthened by three more postdocs in the months to come."
The Leibniz Institute for Agricultural Engineering and Bioeconomy is a pioneer and a driver of bioeconomy research. We create the scientific foundation to transform agricultural, food, industrial and energy systems into a comprehensive bio-based circular economy. We develop and integrate techniques, processes and management strategies, effectively converging technologies to intelligently crosslink highly diverse bioeconomic production systems and to control them in a knowledge-based, adaptive and largely automated manner. We conduct research in dialogue with society - knowledge-motivated and application-inspired. https://www.atb-potsdam.de/en/