Dr. Reena Debray
(Life Sciences)
MPI for Evolutionary Anthropology, Department of Primate Behavior and Evolution
“Ecology and Evolution of the Social Microbiome”

All animals live in close symbiotic relationships with communities of microorganisms, collectively termed the microbiome. Bacteria in the gut microbiome play essential roles in physiology and health, including breaking down complex nutrients into useable forms and training the immune system to recognize infections. These bacteria have adapted to live in the particular temperature and pH conditions inside the gut and to feed on the nutrients available in their hosts’ diets. But in the process, many have become so specialized that they can no longer live outside of a host. For example, at least 90% of gut bacterial species would die if they were exposed to oxygen. These observations raise an important question: How do animals acquire the microbiome they need if many key members are so specialized that they cannot be acquired from food, water, or surfaces? This project studies the social and environmental pathways of microbiome transmission, focusing on our close primate relatives to understand the evolutionary context of how host-microbiome associations have formed, specialized, and diversified over time.

Reena Debray holds a doctorate in biology from the University of California Berkeley (USA) and is head of a Minerva Fast-Track Research Group at the Max Planck Institute for Evolutionary Anthropology. She has received several honors for her research, including the National Science Foundation Graduate Research Fellowship, the Alexander von Humboldt Postdoctoral Fellowship, and Molecular Biology and Evolution’s Best Student Paper Award.

Dr. Florian Hartmann
(Engineering Sciences)
MPI for Intelligent Systems, Research Group for Biomimetic Materials and Machines
“Sustainable electric motors for robotics”

The constantly increasing volumes of electronic waste pose major challenges for our society. Along with entertainment electronics, robots are now likewise giving rise to new streams of waste. Examples include domestic robots, toys, and drones. Many of these products are made from materials that consume a great deal of energy in production and are difficult to recycle. This project sets out to develop more sustainable solutions for robotics. At the focus is a new type of biodegradable motor made from more environment-friendly materials.

The physicist Florian Hartmann, a Research Group Leader at the Max Planck Institute for Intelligent Systems since 2024, is head of the “Biomimetic Materials and Machines” group. He received his doctorate in Technical Sciences from the Johannes Kepler University Linz (Austria) in 2021. He undertook a sojourn as postdoc researcher at the École Polytechnique Fédérale de Lausanne (EPFL), Switzerland.

Dr. Jan Gerrit Horstmann
(Physics)
University of Würzburg, Institute for Physical and Theoretical Chemistry
“Ultrafast design of material properties with light”

Whether a material is metallic, insulating, superconducting, or magnetic depends on its microscopic structure, that is, on the arrangement and interaction of its atoms and electrons. Such technologically relevant properties can so far usually only be modified by changing the chemical composition, temperature, or pressure – processes that are comparatively slow and energy-intensive. An alternative approach is targeted excitation with extremely short light pulses: The strong electric field of light can manipulate the arrangement of atomic nuclei and electrons, thereby altering material properties within a millionth of a billionth of a second. The project investigates a new form of this optical control by specifically employing light pulses in the mid-infrared range. The aim is to switch functional material properties such as magnetism as quickly as possible, energy-efficiently, and even far below the surface using light – key prerequisites for future three-dimensional data storage technologies.

Dr. Jan Gerrit Horstmann leads the junior research group “Ultrafast Structural Dynamics” at the Institute for Physical and Theoretical Chemistry at the University of Würzburg. After completing his doctorate in physics at the University of Göttingen, he conducted research at the Department of Materials at ETH Zurich supported by an ETH Postdoctoral Fellowship and an SNSF Postdoctoral Fellowship. For his scientific work and his social commitment he has received several Lower Saxony Science Prize and the ETH Career Seed Award.

Dr. Sung-Ching Lee
(Earth Sciences)
MPI for Biogeochemistry, Department of Biogeochemical Integration
“Process understanding for implementing nature-based climate solutions in drylands and coastlines”

Nature-based climate solutions are a key supplement to accelerating climate mitigation, yet we lack critical knowledge about how they can be effectively implemented in dryland and coastal ecosystems, which harbor more than half of the world's population, store vast carbon, and safeguard high biodiversity. This project addresses these gaps using advanced monitoring and modeling techniques to assess the effects of diverse water inputs and salinity changes on ecosystem metabolism of drylands and coastal areas, respectively. Establishing this scientific foundation is essential for implementing impactful and sustainable nature-based climate solutions in the two ecosystems, fostering more reliable climate mitigation strategies implemented worldwide.

Sung-Ching Lee is a group leader at the Max Planck Institute for Biogeochemistry, focusing on underlying processes of ecosystem functions. He completed his PhD 2020 in physical geography at the University of British Columbia.

Dr. Julia Mierbach
(Literary Studies)
University of Bonn, Department of German Studies
“Security. A literary and cultural history of the divided Germany”

This project examines how “security” became a central socio-cultural concept of the present era. The comparative analysis of the cultural and literary history of “security” in East and West Germany not only sets out to reconstruct the political languages of the two systems. Rather, the collective imaginative space of security concepts is measured, whereby media-related and literary formations are placed in the context of the political discourses of the post-war order. The objective is to make the conceptual-historical preconditions under which security debates are conducted today visible in the cultural memory.

Dr. Julia Mierbach is a temporary member of the Academic Council at the Department of German and Comparative Literature and Culture at the University of Bonn. She has undertaken research sojourns for example at Yale University and at New York University, NYC. In her dissertation, Mierbach reconstructed the theoretical history of serial forms and formation in literary theory, aesthetics, and knowledge systems of modernity. In her current research, she analyzes the historical depth structures of key sociopolitical concepts of the present era.

Prof. Dr. Katarzyna Reluga
(Mathematics)
Humboldt University, Berlin Chair of AI in Business and Economics
“AI-supported statistical methods for precise estimation of socio-economic indicators”

Precise socio-economic indicators are essential for effective policymaking and equitable resource allocation, but population-based methods often mask local differences. This project uses interpretable machine learning (ML) to provide reliable, fine-resolution estimates at the district and community level. By combining statistical rigor with the flexibility of ML, theoretically sound methods and practical tools are developed for data-poor contexts, supported by an R-based platform for visualization and uncertainty analysis.

Katarzyna Reluga is a junior professor and head of the Chair of AI in Business and Economics at HU Berlin. Previously, she was a Lecturer in Statistical Science at the University of Bristol and held research positions at the University of California, Berkeley, the University of Toronto and the University of Cambridge. She received her doctorate in Statistics from the University of Geneva. Her research develops methods at the interface of statistics and ML to address challenges in public health and economics.

Jun.-Prof. Dr. Marcel Schorpp
(Chemistry)
University of Regensburg, Institute of Inorganic Chemistry
“From bond activation to sustainability: Mechanochemical catalysis with main group elements”

The quest for greater sustainability permeates our society, but at the same time presents us with technological challenges; chemical processes often play a key role in their solution. However, established processes are usually very energy-intensive or rely on catalysts made from toxic or rare elements. In this project, catalysts are developed from commonly occurring elements that are not toxic. Fundamental principles of polar bond activation are transferred here to the socially relevant problems of hydrogen storage, CO₂ utilization, and plastics recycling in order to make industrial processes safer and more sustainable. A further focus is on mechanochemical techniques that make these processes solvent-free and more energy-efficient.

Marcel Schorpp studied chemistry at the University of Freiburg (doctorate in 2020). After undertaking research sojourns in Heidelberg and Oxford, he has now headed a working group at the University of Regensburg since 2023.

Dr. Sven Weinzierl
(Information Systems)
Friedrich-Alexander-Universität Erlangen-Nürnberg, Institute of Information Systems
“Improving patient care in hospitals with precise, interpretable predictions in patient pathways”

Specialist hospital staff often have to make critical decisions regarding the further course of patient treatment within a very short time, in order to make efficient use of limited resources and save lives. To support these decisions, AI-based systems are used to generate predictions about the further course of treatment. However, these systems are based on prediction models that are either transparent but inaccurate, or are accurate but not transparent. This project therefore focuses on the development of approaches based on advanced, intrinsically interpretable machine learning models – i.e. neural generalized additive models – to generate both accurate and transparent predictions, thereby improving the care of hospitalized patients.

Sven Weinzierl is a temporary member of the Academic Council of the Institute of Information Systems at Friedrich-Alexander-Universität Erlangen-Nürnberg. He has received prestigious scholarships and awards for his research on data-driven decision support using machine learning methods, including the Schöller Fellowship, the Software Campus Fellowship, and the Hermann Gutmann Award.

Dr. Felix Weiss
(Life Sciences)
German Rheumatology Research Institute (DRFZ), Berlin,
“Allele selection as a determinant of inflammation”

We inherit two copies, or alleles, of every gene, one from our mother, and one from our father. However, we all know that we don’t represent our parents equally, and the same can be said for whether our cells choose to use our paternal or maternal alleles. Which gene copy our cells choose to use can influence the body’s ability to fight infection, repair tissue damage, or even develop disease. Felix Weiss is researching how allele selection occurs in immune cells, and how when correct allele selection is disrupted, the body’s ability to regulate inflammation is impaired. This project aims to shed new light on a fundamental mechanism controlling inflammation, as well as open new therapeutic opportunities to manipulate allele selection in disease.

Felix Weiss holds a PhD in gene regulation and since May 2025 has led an independent junior research group at the German Rheumatology Research Centre (DRFZ), a Leibniz Institute, in Berlin. After completing his PhD, he carried out his postdoctoral work at the University of Bonn, analyzing how strain-specific genomic variation impacts innate immunity, and myeloid signaling in the central nervous system during autoimmunity.

Dr. Tizian Wenzel
(Mathematics)
LMU Munich, Department of Mathematics
“Understanding and exploiting alignment effects in deep learning”

Artificial intelligence is a highly topical issue; it assists us in many aspects of everyday life. Although these systems basically only consist of simple mathematical operations such as addition and multiplication, with trainable parameters, their interaction gives rise to complex behavior that to date has been only partly understood. The underlying mathematical mechanisms have not yet been sufficiently researched. In particular, so-called alignment effects – how parameters orient themselves to relevant data points during learning – play a key role in their understanding. This project sets out to systematically investigate these mathematical principles. The findings should help in better understanding how they function and thus in making artificial intelligence more reliable.

Tizian Wenzel studied physics and mathematics at the University of Stuttgart, where he received his doctorate in 2023. He was then active as a postdoc researcher at the University of Hamburg and has been a member of the Academic Council of LMU Munich since 2024. The awards he has received for his mathematical work include the IMA Leslie Fox Prize.

Dr. Barbara Wichtmann
(Medicine)
University of Bonn, Department of Diagnostic and Interventional Neuroradiology and Pediatric Neuroradiology
“AI makes the hidden extent of glioblastomas measurable”

Glioblastomas are the most commonly occurring malignant brain tumors, with a poor prognosis. Their highly aggressive growth leads to structural changes in the brain far beyond the boundaries of a tumor, which can be measured by means of imaging and correlate with the progression of a disease and survival rate. However, standard image analysis methods fail when the anatomy is greatly distorted by tumors or surgical cavities. Modern AI models synthetically compensate for tumor-related changes by means of tissue with a healthy appearance, making it possible to analyze the entire brain for the first time. Dr. Barbara Wichtmann is validating this innovative approach based on a longitudinal cohort of glioblastoma patients at the University Hospital Bonn in order to develop image-based biomarkers.

Dr. Barbara Wichtmann, a radiologist and medical physicist, is head of the Oncological Imaging Research Group at the University Hospital Bonn. Research sojourns at Harvard Medical School and a management fellowship at Mass General Brigham in Boston have played a formative role in her scientific career. She is involved in national and international professional societies and has received numerous distinctions, including a Junior Fellowship with the International Society for Magnetic Resonance in Medicine (ISMRM), and the Doctorate Award and the Eugenie and Felix Wachsmann Innovation Award of the German Radiological Society (DRG).