Prof. Waldemar Kolanus leads the Molecular Immunology and Cell Biology department at the University of Bonn's Life & Medical Sciences Institute (LIMES) . His research bridges immunoregulation , stem cell dynamics , and metabolic stress responses in immune cells. Unit 2 member at LIMES Principal investigator in SFB 704 and ImmunoSensation Cluster Leads a multidisciplinary lab with postdocs, PhD students, and technical staff His work focuses on intracellular signaling pathways connecting immune activation to tissue homeostasis, particularly through: Cytohesin proteins in integrin-mediated adhesion and migration TRIM71 in stem cell regulation and congenital hydrocephalus High-salt environments affecting macrophage function Publication trends show expertise in immune cell migration , genetic models , and chemical inhibition , with frequent use of mice and zebrafish for in vivo studies. Key articles explore: TRIM71's dual role in auditory development and germ cell maintenance Cytohesin family's Golgi regulation and insulin signaling Ruxolitinib's off-target migration inhibition of dendritic cells Contact details: Address: LIMES Institute, Carl-Troll-Straße 31, Bonn Email: kolanus.sekretariat@uni-bonn.de Phone: +49 228 73-62788
Michael Groll serves as Professor and Chair of Biochemistry at the Technical University of Munich (TUM), where he leads structural biology and enzymology research with a focus on proteasome mechanisms and inhibitor development. His laboratory, located at the Ernst-Otto-Fischer-Str. 8 campus in Garching, maintains active collaborations in drug discovery for cancer and infectious diseases. His primary research domains include proteasome inhibition, enzyme catalysis, and natural product biosynthesis, employing X-ray crystallography, biochemical assays, and bioengineering to dissect molecular mechanisms. Recent work emphasizes AI-guided enzyme optimization, bacterial stress response targeting, and structural characterization of halogenation enzymes, reflecting interdisciplinary approaches bridging chemistry and biology. Analysis of his 2023-2025 publications reveals consistent innovation in proteasome-targeted therapeutics, with 15 high-impact papers featuring structural insights into enzyme-inhibitor complexes and biosynthetic pathways. Key trends include engineering megasynthetases for immunoproteasome inhibitors, optical control of protein degradation, and elucidating metal-dependent mechanisms in antibiotic biosynthesis. No scientific awards were documented in the provided source material. While specific grant details and student mentorship records were not disclosed, his extensive publication record indicates leadership in collaborative research projects involving structural biology and chemical biology methodologies. The Chair of Biochemistry under Prof. Groll operates as a hub for structural enzymology, housing facilities for protein crystallography, enzyme kinetics, and natural product characterization. His team actively contributes to TUM's research ecosystem through partnerships with pharmaceutical groups and international structural biology consortia.
Prof. Igors Gorbovickis is an Associate Professor of Mathematics at the Department of Mathematics, School of Computer Science and Engineering, Constructor University (formerly Jacobs University Bremen). His research focuses on complex dynamical systems, including topics such as renormalization theory, bifurcation analysis, Julia sets, and applications to mathematical physics. He also contributes to discrete geometry, particularly exploring conjectures like the Kneser-Poulsen problem. His work bridges pure mathematics with interdisciplinary applications, emphasizing rigorous analysis of nonlinear systems and geometric configurations. Key areas of investigation include critical point accumulations, Hausdorff dimension estimates, and equidistribution phenomena in parameter spaces. Recent publications highlight advancements in understanding chaotic systems, circle maps, and the interplay between algebraic structures and dynamical behavior. Prof. Gorbovickis collaborates internationally, with co-authored papers appearing in journals like Advances in Mathematics , Ergodic Theory and Dynamical Systems , and Nonlinearity . His office is located at Research I, Room 128 on the Constructor University campus in Bremen, Germany.
Peter Benner is a Professor and Director at the Max Planck Institute for Dynamics of Complex Technical Systems in Magdeburg, where he leads the Computational Methods in Systems and Control Theory group. He also holds an Honorarprofessor position for Mathematics at Otto-von-Guericke Universität Magdeburg since 2011. Benner has previously served as Managing Director of the Max Planck Institute during multiple periods (2013-2014, 2021-2022, and 2025-2026), demonstrating his leadership in the field. Benner's research focuses on Scientific Machine Learning, Numerical Linear and Multilinear Algebra, Model Order Reduction and Reduced-order Modeling, Numerical Methods in Systems and Control Theory, PDE Constrained Optimization, High-performance and Power-aware Computing, and Mathematical Software development. His work bridges theoretical mathematics with practical engineering applications, particularly addressing challenges in large-scale dynamical systems. Analysis of his recent publications reveals a strong emphasis on developing efficient computational methods for complex systems. Benner has pioneered approaches combining model order reduction with tensor methods to tackle high-dimensional problems in uncertainty quantification and PDE-constrained optimization. His work shows a consistent trend toward integrating data-driven techniques with traditional model-based approaches, particularly for nonlinear and parametric systems. Throughout his career, Benner has actively mentored students and collaborated with researchers worldwide, delivering numerous invited talks at prestigious institutions and conferences across Europe, North America, and Asia. His research has received significant funding, supporting the development of mathematical software and computational methods for industrial applications. Benner leads the Computational Methods in Systems and Control Theory department at the Max Planck Institute, which focuses on developing and implementing advanced numerical methods for large-scale dynamical systems. The group maintains strong connections with both theoretical mathematics and practical engineering applications, particularly in fluid dynamics, energy systems, and control theory.
Prof. Dr. Markus Zimmermann leads the Chair of Product Development and Lightweight Design at the Technical University of Munich (TUM). With a background in mechanical engineering from TU Berlin and the University of Michigan, and a doctorate from MIT on solid-state singularities, he bridges academic rigor with industrial application. His career spans 12 years at BMW focusing on vehicle development before transitioning to academia. Specializes in solution space engineering for robust design Expert in additive manufacturing and systems engineering Develops methodologies for managing design complexity and uncertainty His research focuses on multidisciplinary design optimization and lightweight structures , particularly in robotics and automotive systems . His team applies digital twin frameworks and attribute dependency graphs to enhance design processes. Recent publications emphasize topology optimization in robotic systems and thermal management for medical X-ray sources. Key trends in his 2024-2025 publications include: Topological optimization for additive manufacturing and robotics Application of solution spaces to manage design uncertainty Development of compact X-ray systems for medical therapy Integration of digital twin technologies in industrial contexts
Prof. Dr. Peter Strasser is a faculty member at the Technische Universität Berlin , affiliated with the Institute of Chemistry and leading the Electrochemical Catalysis, Energy and Materials Sciences Group within the Faculty II - Mathematics and Natural Sciences . His research spans electrocatalysis , fuel cell technology , and high-throughput materials testing , with a focus on nanostructured catalysts for clean energy systems. Research Interests : High Throughput Testing Fuel Cells Electrocatalysis Electrochemical Materials Water Splitting CO2 Conversion Scientific Contributions highlight trends in oxygen evolution reactions , dealloyed catalysts , and non-noble metal electrocatalysts . His work bridges materials science and energy storage , particularly for hydrogen fuel cells and magnesium batteries . Awards : Otto Roelen Medal 2016 Advising notable researchers like former PhD student Mehtap Özaslan , who established a junior research group at the University of Oldenburg and won the Umicore Scientific Award. Prof. Strasser's team collaborates with UniSysCat and has secured funding from the Federal Ministry of Research for catalyst innovation.
Prof. Dr. Urs Hartl is a faculty member in the Department of Mathematics and Computer Science at the University of Münster, affiliated with the Faculty of Mathematics and Computer Science. He is an Investigator in Mathematics Münster and a member of the Collaborative Research Centre (CRC) 1442 'Geometry: Deformations and Rigidity.' His research focuses on arithmetic geometry, representation theory, algebraic number theory, and arithmetic of function fields. He holds a prominent position in the field, contributing to areas such as Shimura varieties, p-adic Hodge theory, and the Langlands program. Affiliations: Member of CRC 1442 Geometry Investigator in Mathematics Münster Research Interests: Arithmetic algebraic geometry Algebraic number theory Arithmetic of function fields Structure theory of Shimura varieties p-adic Hodge theory p-adic Langlands programme Model theory Recent Publications: Hartl's recent work includes studies on moduli stacks of global G-shtukas, periods of Drinfeld modules, and p-adic Galois representations. His research emphasizes foundational contributions to arithmetic geometry and number theory, often involving collaborations with leading mathematicians such as Rajneesh Kumar Singh and Eva Viehmann. Grants & Advising: Hartl’s involvement in CRC 1442 reflects his leadership in geometric research. While specific advising details are not provided, his extensive publications suggest active mentorship in advanced mathematical research. Labs/Teams: Collaborates within the Mathematics Münster research group and the CRC 1442 team, focusing on geometric and arithmetic structures.
Prof. Dr. Evi Hartmann holds the Chair of Business Administration, especially Supply Chain Management at Friedrich-Alexander University Erlangen-Nuremberg (FAU) within the Department of Business, Economics, and Social Sciences. She is actively involved in multiple research focus areas including sustainability, energy markets and energy system analysis, and insurance and risk. Her academic leadership extends across interdisciplinary collaborations with engineering, mathematics, and industry partners. Dr. Hartmann studied industrial engineering at the University of Karlsruhe (TH), received her doctorate in 2002 from the Institute of Technology and Management at the Technical University of Berlin, and completed her habilitation in business administration in 2008. Prior to her academic career, she worked as a consultant at AT Kearney from 1998 to 2005, followed by a junior professorship for 'Purchasing and Supply Management' at the Supply Chain Management Institute at the European Business School. Her research program focuses on supply chain management, purchasing, and strategic foresight, with particular emphasis on application-oriented approaches that bridge theory and practice. Current research trajectories include supply chain resilience in crisis situations (including pandemic response), digital transformation through Industry 4.0 technologies, sustainable and low-carbon supply chains, and the integration of strategic foresight methodologies in logistics decision-making. Her work frequently employs Delphi studies, bibliometric analyses, and multi-tier case studies to examine complex supply chain phenomena. Analysis of her recent publications reveals a strong trend toward interdisciplinary research that combines supply chain management with digital transformation, sustainability, and crisis response. Her work increasingly examines the intersection of technology adoption (particularly Industry 4.0), organizational culture, and supply chain resilience across multiple industries including automotive, food, and maritime logistics. Prof. Hartmann is recognized as the author of two academic bestsellers in her field, though specific awards are not detailed in available materials. Her research has been published in top-tier journals including IEEE Transactions on Engineering Management, International Journal of Production Research, and Journal of Cleaner Production. Her research program demonstrates extensive industry collaboration, with numerous projects involving real-world implementations and close partnerships with companies. She leads research initiatives examining the practical implications of digital transformation, sustainability challenges, and resilience strategies in supply chain operations. Current projects include studies on digital ecosystems, physical internet applications, and the future of freight forwarding technologies. Prof. Hartmann participates in several research networks including the Energy Campus Nuremberg (EnCN) and collaborates with the Department of Mathematics on gas networks and markets research. She is also involved with the Nuremberg Energy Region (Energieregion Nürnberg eV) and contributes to interdisciplinary research centers focused on sustainable development and digital transformation in supply chains.
Inho Hong is an Assistant Professor at the Graduate School of Data Science, Chonnam National University (Gwangju, Korea), leading the Computational Social Science and Complex Systems Lab (CSL). His research explores socio-spatial systems through data science and complex systems methods, focusing on urban dynamics, human mobility, and AI's societal impact. Education: Ph.D. in Physics (2019), Pohang University of Science and Technology (POSTECH) M.S. in Physics (2012), POSTECH B.S. in Physics (2010), POSTECH Research Interests: Urban Data Science : Analyzing urban scaling laws and innovation pathways Human Mobility : Modeling intra-city movement patterns Social Impact of AI : Ethical and societal challenges Natural Language Processing : Text embedding for policy analysis Complex Systems : Network approaches to protests and epidemics Recent Work Trends: Over 2020–2022, his articles centered on pandemic control, protest networks, and urban green spaces' psychological impact. Recent 2023–2025 work extends to vocational education analysis and mobility laws within cities. His methods combine network science with large-scale data analytics. Awards: Young Statistical Physicist Award (Korean Physical Society, 2021) Best Paper Award (Korea Computer Congress 2021) Global Ph.D. Fellowship (NRF, 2014–2017) Grants & Labs: Current lab focuses on socio-spatial systems. Past roles include Associate Research Scientist at Max Planck Institute for Human Development (2020–2023) and Postdoctoral Fellowships at POSTECH and APCTP.
Anders Rantzer is a Professor of Automatic Control at the Department of Control Engineering, Faculty of Engineering, Lund University, Sweden. He has held visiting positions at Caltech (2004–2005) and the University of Minnesota (2015–2016) as the Taylor Family Distinguished Visiting Professor. His academic journey began with a PhD from KTH Stockholm in 1991, followed by a postdoc at the Institute for Mathematics and its Applications (IMA), University of Minnesota. His research interests center on modeling, analysis, and synthesis of control systems , with a strong focus on scalability, adaptation, and applications in energy networks . He is particularly known for foundational work in positive systems and integral quadratic constraints (IQCs) . These theoretical frameworks are critical in analyzing stability and robustness of large-scale interconnected systems. His work bridges mathematical rigor with practical engineering applications, especially in sustainable energy and networked systems. The recent publications and lecture materials reflect a consistent trajectory in scalable and robust control, optimization, and distributed systems. Themes such as large-scale convex optimization , nonlinear and stochastic control , and network dynamics dominate his scholarly output, indicating a sustained commitment to advancing control theory for complex, real-world systems. Scientific honors include: Fellow of IEEE Member of the Royal Swedish Academy of Engineering Sciences (IVA) Chairman of the Swedish Scientific Council for Natural and Engineering Sciences Chairman of the Royal Physiographic Society of Lund Rantzer has supervised numerous students and contributed extensively to academic leadership and education. He has been involved in major national and international research initiatives such as WASP (Wallenberg AI, Autonomous Systems and Software Program) and ELLIIT. His work includes developing educational tools and courses in control, optimization, and machine learning. He leads and contributes to research projects on autonomous systems, cloud control, and smart energy networks. He is affiliated with the Control Lab at LTH and participates in collaborative efforts such as the Nordic University Hub on Industrial Internet of Things (HI2OT). His work integrates theoretical advances with practical implementations in robotics, biomedical systems, and industrial automation.
Michael Muehlebach leads the independent Learning and Dynamical Systems research group at the Max Planck Institute for Intelligent Systems in Tuebingen, Germany. His interdisciplinary work bridges machine learning, dynamical systems theory, and control engineering to develop algorithms for cyber-physical systems with theoretical guarantees and practical implementations. Dr. Muehlebach received his B.Sc. and M.Sc. in Mechanical Engineering from ETH Zurich in 2010 and 2013, specializing in robotics and control systems. He completed his Ph.D. at ETH's Institute for Dynamic Systems and Control under Prof. R. D'Andrea in 2018, followed by postdoctoral research with Prof. Michael I. Jordan at UC Berkeley. His research focuses on constrained optimization, reinforcement learning, and control theory with applications in robotics. He pioneered approaches that express constraints in terms of velocities rather than positions, enabling more efficient optimization algorithms. His work spans theoretical foundations to physical implementations, including the One-Wheel Cubli balancing robot and electromagnetic navigation systems. Recent publications reveal a strong trend toward physics-informed machine learning, particularly for robotics applications requiring real-time performance and safety guarantees. Dr. Muehlebach has received numerous prestigious awards: Outstanding D-MAVT Bachelor Award Willi-Studer prize for best Master's degree ETH Medal and HILTI prize for doctoral thesis Branco Weiss Fellowship (2018) Emmy Noether Fellowship (2020) Amazon Fellowship (2024) He actively mentors doctoral researchers including Hao Ma, Melis Ilayda Bal, and Onno Eberhard, with research supported by multiple grants. His group maintains strong collaborations with Bernhard Schölkopf's Empirical Inference group at the Max Planck Institute. The Learning and Dynamical Systems group develops innovative hardware and software platforms, including Floaty (a wind-harnessing flying robot), advanced electromagnetic navigation systems, and data-efficient learning methods for robotic table tennis. Their approach combines rigorous theoretical analysis with practical validation on physical systems, emphasizing the integration of known physical structure into machine learning algorithms to improve sample efficiency and ensure generalization.
Dr. Emilio Ferrara is a Professor of Computer Science & Communication at the University of Southern California, holding appointments in the Viterbi School of Engineering, Annenberg School for Communication and Journalism, and Keck School of Medicine. He serves as Associate Director of Applied Data Science at USC, Research Team Leader at the USC Information Sciences Institute, and Principal Investigator at the USC/ISI Machine Intelligence and Data Science (MINDS) group. His educational background includes a PhD in Machine Learning and BSc & MSc in Computer Science. Ferrara's research focuses on the intersection of artificial intelligence and computational social science, specifically using AI to model and predict human behavior in techno-social systems. His work spans social networks, machine learning, and network science with applications to understanding communication dynamics in digital environments. Ferrara has published over 150 articles in prestigious venues including Proceedings of the National Academy of Sciences, Communications of the ACM, and Physical Review Letters. His research has been widely featured in major news outlets and examines topics ranging from social media manipulation to AI ethics and online behavior. His scientific achievements have been recognized with numerous awards: 2019 Viterbi Scientific Award 2018 DARPA Director's Fellowship 2016 DARPA Young Faculty Award 2016 Complex Systems Society Junior Scientific Award 2015 IBM Watson Big Data Influencer Ferrara's research is supported by major funding agencies including DARPA, IARPA, Air Force, and Office of Naval Research. He leads the HUMANS LAB (Humans & Machines + Networks & Social Systems) which has trained numerous PhD students who have gone on to successful careers in academia and industry. His work on social bots, election integrity, and AI ethics continues to shape understanding of digital social dynamics.
Sabine Walper is a Professor at the Faculty of Psychology and Education, Ludwig Maximilian University of Munich (LMU Munich), currently on leave as Research Director at the German Youth Institute (DJI) since 2012. Her research focuses on family psychology, particularly divorce and stepfamilies, parental conflict effects on child development, poverty, individuation in adolescence, and parenting skill interventions. Research Director, German Youth Institute (DJI), Munich (2012–present) Professor, Faculty of Psychology and Education, LMU Munich Her scientific work spans family dynamics, mental health, and educational psychology, with a strong emphasis on longitudinal studies and cross-cultural comparisons. She supervises numerous PhD theses and leads major projects like the Relationship and Family Panel (pairfam) and parenting courses for families in separation. Walper holds key roles in advisory boards, editorial positions, and mentorship programs for young female researchers.
Prof. Dr. Martin Kronbichler is a faculty member at the Faculty of Mathematics , Ruhr University Bochum , leading the Numerics group. His research focuses on higher-order finite element methods, multigrid techniques, and high-performance computing for complex fluid and solid mechanics problems. Key Research Areas: Higher-order finite element methods, iterative solvers, multigrid algorithms, exascale mathematical software, and computational fluid dynamics. Notable Projects: EU-funded dealii-X (exascale digital twins), BMBF PDExa (optimized PDE solvers for exascale), and DFG grants for cut-discontinuous Galerkin methods and geometric multigrid. Publications Trends: Recent works emphasize matrix-free operators for hyperelasticity, diffuse-interface models for additive manufacturing, and multigrid smoothers for higher-order elements. Scientific Awards: Recipient of the Humboldt Research Award for his contributions to numerical methods and HPC. Team: Collaborates with researchers like Dr. Shubham Kumar Goswami, Dr. Richard Schussnig, and Natalia Nebulishvili.
Michael Mühlebach is a Research Group Leader at the Max Planck Institute for Intelligent Systems in Tübingen, Germany, leading the independent Learning and Dynamical Systems group. His academic journey began at ETH Zurich where he earned his B.Sc. (2010) and M.Sc. (2013) in mechanical engineering, specializing in robotics, systems, and control. He completed his Ph.D. at ETH Zurich in 2018 under Prof. R. D'Andrea, followed by postdoctoral research at UC Berkeley with Prof. Michael I. Jordan. Dr. Mühlebach's research spans machine learning, dynamical systems, control theory, and optimization . His work bridges theoretical foundations with practical applications in robotics, developing methods that incorporate physical constraints and system dynamics into learning frameworks. His group focuses on online learning, physics-informed machine learning, and large-scale optimization for cyber-physical systems, with applications in electromagnetic navigation, robotic table tennis, and energy-efficient flight systems like the shape-changing robot Floaty . His publication record shows a strong focus on constrained optimization, with recent work exploring decision-dependent stochastic optimization, nonlinear feedback, and the theoretical foundations of reinforcement learning. His research integrates perspectives from control theory, dynamical systems, and optimization to develop algorithms with strong theoretical guarantees and practical performance. Outstanding D-MAVT Bachelor Award Willi-Studer prize for best Master's degree ETH Medal and HILTI prize for doctoral thesis Branco Weiss Fellow (2018) Emmy Noether Fellowship (2020) Amazon Fellowship (2024) Dr. Mühlebach actively mentors doctoral researchers and is seeking talented students for PhD and Master's projects. His research group has received funding from multiple prestigious fellowships and maintains collaborations across institutions including ETH Zurich, UC Berkeley, and various Max Planck research units. The group's work spans theoretical developments to practical implementations on robotic systems, demonstrating strong connections between mathematical theory and physical realization.
