Principal Investigators

Excellence and international visibility of the scientists and/or groups of researchers who comprise the project group:

Prof. Dr. Alexander Brenning (Friedrich Schiller University Jena) is a full professor of geographic information science, adjunct professor at the University of Waterloo, Canada, Humboldt fellow (2014), and former Dean of the Faculty of Chemistry and Earth Sciences (2017-2020). He is an internationally recognized expert in geospatial modeling of Earth surface processes, in particular natural hazards, focusing on uncertainty quantification and interpretability of spatial statistical and ML models. Having received funding from DFG, Umweltbundesamt, NSERC, BMBF, EU and Carl-Zeiss-Stiftung, his 116 publications have been cited >5500 times (h-index 39).

PD Dr. Solveig Franziska Bucher (Senckenberg Institute for Plant Form and Function, Friedrich Schiller University Jena, German Centre for Integrative Biodiversity Research) is an ecologist by training and an expert in ecophysiological and phenological adaptations of plants to climate change. Her research examines phenological observations using different methodologies from herbaria to remote sensing with a focus on frost resistance. She received funding from the DFG and Carl Zeiss Foundation and publishes in high-ranking journals (52 publications, h-index 17). She is the speaker of the PopBio chapter of the Ecological Society of Germany, Austria and Switzerland.

Dr. Nuno CarvalhaisExternal link (Max Planck Institute for Biogeochemistry in Jena) leads the Model-Data Integration Group at MPI-BGC since 2012, and is an Invited Researcher at the New University of Lisbon. His research interests focus on the dynamics of terrestrial biogeochemical cycles, particularly the improvement of ecosystem modeling through data assimilation and inverse optimization, and on the introduction of DL and hybrid modeling in modeling terrestrial ecosystem processes. Carvalhais has visited Boston University and NASA Goddard Space Flight Center, and has held several international (ESA, EU FP7, H2020) and nationally funded projects. His outstanding publication record (h-index 52, >100 publications, >18k citations) includes contributions to Nature and Science.

Prof. Dr. Joachim DenzlerExternal link (Friedrich Schiller University Jena) is a full professor and head of the Computer Vision group at FSU. His group (particularly Dr. Aishwarya Venkataramanan) focuses on the analysis of sensor data, especially image and videodata, and the development of lifelong learning methods, uncertainty quantification, active learning and anomaly detection. The explainability of black-box models, knowledge integration into ML techniques, uncertainty quantification for model’s predictions and the detection and use of causal relationships have become core areas of the group’s research in recent years. The group contributes to major computer vision and ML journals and conferences and receives competitive external funding (EU, BMBF, DFG), often in collaboration with partners from other disciplines, including several GENAI-X PIs.

Prof. Dr. Joachim Giesen (Friedrich Schiller University Jena) was trained in algorithms and data structures, especially in geometric algorithms. His research is guided by the algorithm engineering paradigm of combining theoretical guarantees with efficient implementations. He coordinated the European FP7 FET-Open project Computational Geometric Learning, focusing on efficient algorithms for geometric and topological data analysis. His current research interests include algorithms and data structures for probabilistic modeling. He served as the director of the Institute for Computer Science (2013-2016), and as the Dean of the Faculty of Mathematics and Computer Science (2019-2023).

Prof. Dr. Michael HabeckExternal link (Jena University Hospital, Friedrich Schiller University Jena) is a full professor of Microscopic Image Analysis at JUH. He is a former Emmy Noether fellow (2009-2014) and Carl-Zeiss-Stiftungsprofessor (since 2019). Trained as a physicist, Prof. Habeck is an  internationally recognized expert in Bayesian statistics, probabilistic ML and image analysis with a particular focus on applications in structural biology. He has participated in two CRCs funded by the DFG, and has received funding from Baden-Württemberg- Stiftung, Carl-Zeiss-Stiftung, DFG and the Max Planck Society. His publications have been cited > 6000 times (h-index 33).

Dr. Shijie JiangExternal link (Max Planck Institute for Biogeochemistry in Jena) is an early-career researcher specializing in interactions among climate, water, and ecosystems under environmental change. His work integrates data and domain knowledge with hybrid and explainable machine learning methods to improve understanding and prediction of hydrological and ecological processes and extremes. Since completing his Ph.D. at the National University of Singapore, he has worked on challenges in modeling and interpreting the water cycle using AI-based approaches. He serves as an Associate Editor for Water Resources Research and has convened EGU and AGU sessions on machine learning in hydrological sciences since 2022.

Prof. Dr.-Ing. Kai Lawonn’sExternal link (Friedrich Schiller University Jena) research is motivated by scenarios from medical education, treatment planning, intraoperative support, life sciences, and computer graphics. Having a mathematical background, Lawonn has also contributed to important technical aspects of high-performance GPU algorithm development. His research ranges from analyzing an aneurysm to image triangulation in art to supporting architectural preservation. With his experience, he is ideally suited to work with a wide range of disciplines. In 2021 Lawonn received the DFG’s Heinz Maier-Leibnitz Prize.

Prof. Dr. Markus ReichsteinExternal link (Max Planck Institute for Biogeochemistry in Jena, Friedrich Schiller University Jena) is a world-leading researcher in datadriven Earth system science and was awarded Germany’s most prestigious science award, the Leibniz Prize in 2020. He received the Max Planck Research Prize of the Alexander von Humboldt Foundation, the Piers Sellers mid-career award of the American Geophysical Union. Reichstein is recognized as a highly cited researcher, with >90k citations of his >200 publications (h-index >100). He has been IPCC lead author, and coordinated several international projects.

Prof. Dr. Christine Römermann (Friedrich Schiller University Jena, Senckenberg Institute for Plant Form and Function, German Centre for Integrative Biodiversity Research) leads the Plant Biodiversity Group at FSU and is director of the SIP; she is affiliated with the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig and vice president of the Ecological Society of Germany, Austria and Switzerland. With her expertise in functional ecology and phenology, she coordinates the international PhenObs network. Previous work includes the cooperation with scientists from computer vision developing AI methodsto automatically extract plant coverage and plant phenology from images. In general, she is interested in the effects of climate and land-use change on biodiversity and ecosystem functioning using novel methods and interdisciplinary approaches.

Dr. Eng. habil. Maha ShadaydehExternal link (Friedrich Schiller University Jena) is a Senior Scientist with the Computer Vision Group at FSU Jena. Her research focuses on causal discovery in multivariate time series data, causal feature learning in computer vision, the analysis of the dynamical behavior of adaptive systems, and the development of mathematical models for biomedical and remote sensing applications. She received a DFG Individual Research Grant in 2021, as well as additional funding from the DFG and the Carl Zeiss Foundation. Earlier in her career, she was awarded the fellowship of the Japanese Ministry of Education for her postgraduate studies at Tohoku University, Japan. Shadaydeh regularly publishes in leading journals and conferences in computer vision and signal processing.

Dr. Aishwarya VenkataramananExternal link (Friedrich Schiller University Jena) is an early-career researcher specializing in uncertainty quantification and probabilistic modeling for deep learning. Her research aims to improve the robustness and reliability of machine learning systems by developing methods that model and quantify uncertainty. During her Ph.D., she designed novel deep learning approaches for ecological applications, focusing on uncertainty-aware prediction and model interpretability. In her current work with the Computer Vision Group Jena, she develops probabilistic frameworks and uncertainty-aware deep learning methods that integrate multimodal data and domain knowledge to improve model reliability and generalization.

Dr. Alexander J. WinklerExternal link (Max Planck Institute for Biogeochemistry in Jena) is an early-career research group leader at the MPI for Biogeochemistry, heading the Atmosphere-Biosphere Coupling, Climate and Causality group (ABC3). A climate scientist by training, he holds a PhD in Earth system modeling with the highest distinction (summa cum laude) from the University of Hamburg / MPI for Meteorology and collaboration with Boston University, USA. His group operates at the intersection of mechanistic and AI-driven modeling, focusing on causal relationships and biosphere-atmosphere feedbacks. He received a Humboldt fellowship and published as lead author of an international team of scientists in outstanding journals (Nature Climate Change, Nature Communications).