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
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. 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.
Professor Sarah E. O'Connor is the Director of the Department of Natural Product Biosynthesis at the Max Planck Institute for Chemical Ecology in Jena, Germany. Her research focuses on understanding and engineering biosynthetic pathways for plant-derived natural products. 2024 Prelog Medal and Lectureship, ETH Zurich 2024 Member of the German National Academy of Sciences Leopoldina 2024 Doctors honoris causa, Université de Tours 2023 Gottfried Wilhelm Leibniz Prize 2023 Fellow of the Royal Society 2022 Ernest Guenther Award in Natural Product Chemistry 2019 RSC Perkin Prize for Organic Chemistry O'Connor's work bridges plant biochemistry, enzymology, and synthetic biology to explore complex natural product synthesis. She is recognized for her contributions to biotechnology and chemical ecology through prestigious awards and memberships.
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.
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.
Vladimir Spokoiny is a Professor at the Departments of Mathematics and Economics of the Humboldt University of Berlin and Head of the Research Group "Stochastic Algorithms and Nonparametric Statistics" at the Weierstrass Institute for Applied Analysis and Stochastics (WIAS) in Berlin, Germany. His research spans multiple areas of statistics, machine learning, and financial mathematics, with significant contributions to nonparametric statistics, high-dimensional data analysis, and statistical methods in finance. Spokoiny received his M.Sc. in applied mathematics from the Moscow Institute of Railway Engineering in 1981 and his Ph.D. in mathematics from Lomonosov Moscow State University in 1988. He completed his Habilitation at Humboldt University in 1996. His academic career includes positions at the All-Union Institute of Railway Transport in Moscow, the Institute for Information Transmission Problems in Moscow, and the Institute for Applied Analysis and Statistics in Berlin before joining the Weierstrass Institute and Humboldt University where he has been a professor since 2002. Spokoiny's research focuses on adaptive nonparametric smoothing and hypothesis testing, high dimensional data analysis, statistical methods in finance, image analysis with applications to medicine, classification, and nonlinear time series. His work often addresses the challenges of nonstationarity in time series data and develops innovative methods for volatility estimation and risk management. He has made significant contributions to the development of adaptive weights smoothing procedures, which have applications in image processing, community detection, and manifold learning. His recent work has expanded into high-dimensional statistics, Bayesian inference, and optimization methods for machine learning, with publications demonstrating novel approaches to Gaussian approximation, Laplace methods, and statistical inference in non-Euclidean spaces. Spokoiny has supervised numerous PhD students including Oliver Reiss, Danilo Mercurio, Ying Chen, Elmar Diederichs, and Mstislav Elagin, whose research has focused on mathematical finance, time series analysis, and statistical methods. He serves as an Associate Editor for The Annals of Statistics (since 2004) and Statistics and Decisions (since 2002), and has previously served on the editorial board of the Journal of Statistical Planning and Inference. His professional activities include reviewing for major statistical journals including Annals of Statistics, Bernoulli, Econometrica, and Journal of American Statistical Association, as well as reviewing grant proposals for the National Science Foundation (USA), German Research Foundation, and Netherlands Organisation for Scientific Research. Spokoiny is a member of several professional societies including the International Statistical Institute, American Statistical Association, Institute of Mathematical Statistics, and Bernoulli Society. He is fluent in Russian (mother tongue), English, and German, and has good knowledge of French. His research group at WIAS focuses on developing novel statistical methodologies with applications across various scientific domains, particularly emphasizing adaptivity and robustness in complex data environments. The group's work has significant implications for financial risk management, medical imaging, and machine learning applications, with recent publications addressing fundamental questions in high-dimensional statistics and nonparametric inference.
Wolfram Mey serves as Curator of the Lepidoptera and Trichoptera Collection (Butterflies, Moths, Caddisflies) at the Museum of Natural History, Leibniz Institute for Evolution and Biodiversity Research in Berlin since 1990. His role encompasses collection management, providing specialized services to the international entomological community, and public outreach through lectures and information dissemination. Education: Biology studies at Martin Luther University Halle-Wittenberg (1973-1978) Doctorate in Natural Sciences (Dr. rer. nat.) from Martin Luther University Halle-Wittenberg (1980) Dr. Mey's research centers on the taxonomy, phylogeny, biogeography, and biodiversity of Lepidoptera and Trichoptera in the Old World, with significant fieldwork in southwestern Africa, the Philippines, and Colombia. His work integrates morphological analysis with ecological and historical biogeographical frameworks to document species diversity in understudied regions. Key methodologies include systematic revision of genera, fauna inventories, and development of identification tools for complex insect groups. His publication record demonstrates sustained focus on African Lepidoptera systematics (particularly the Brandberg Massif in Namibia) and global Trichoptera diversity. Recent works emphasize field-based inventory projects in biodiverse hotspots like the Colombian Páramo, reflecting a commitment to documenting micro-endemic species in threatened ecosystems. The 2002 Trichoptera symposium proceedings highlight his role in fostering international taxonomic collaboration. Research Leadership: Basic pattern of Lepidoptera diversity in southwestern Africa Identification book for Lepidoptera of southwestern Africa Caddisfly fauna survey of the Philippines Trichoptera and Micro-Lepidoptera inventory in Colombia's Páramo
Stephen Meisenbacher is a Research Associate at the Technical University of Munich (TUM) , affiliated with the School of Computation, Information and Technology and the Department of Computer Science, I19 . He has been part of the Software Engineering for Business Information Systems (SEBIS) chair since March 2022. His research focuses on Privacy-Preserving Natural Language Processing (NLP) , Differential Privacy , and Privacy-Enhancing Technologies (PETs) , with a particular interest in their integration into software development and business applications. His work also explores Hybrid, Expert-Driven Classification Systems and Usable Privacy solutions. Stephen’s recent publications address trends in AI Privacy Risks , Text Rewriting with DP , Legal AI Use Cases , and Data Protection Compliance . He has contributed to GDPR-related research and PETs adoption in small enterprises. His teaching includes Natural Language Processing seminars and Software Engineering lecture courses for Master’s and Bachelor’s students at TUM. He also organizes Entrepreneurship for Small Software-Oriented Enterprises seminars. Stephen holds a Master’s in Informatics from TUM (DAAD Graduate Scholarship) and a Bachelor’s in Computer Science from the University of Notre Dame, with additional studies in German Language and Literature. Contact: stephen.meisenbacher@tum.de | LinkedIn
Dr. Yolanda Gil is a Research Professor in Computer Science and Spatial Sciences at the University of Southern California, where she serves as Principal Scientist and Senior Director for Strategic Initiatives in Artificial Intelligence and Data Science at the Information Sciences Institute (ISI). She is also the Director of AI and Data Science Initiatives in the Viterbi School of Engineering and leads the USC Center for Knowledge-Guided Interdisciplinary Data Science (CKIDS). Dr. Gil received her Licenciatura in Computer Science from the Polytechnic University of Madrid and her M.S. and Ph.D. in Computer Science from Carnegie Mellon University, with a focus on artificial intelligence and cognitive science. Her research focuses on developing AI approaches that use knowledge to accelerate scientific discovery processes. Her key research interests include knowledge capture and representation, semantic workflows, ontology tools, scientific discovery methods, task-based collaboration, provenance tracking, knowledge networks, reproducibility in science, and machine learning for data analysis. She collaborates with scientists across multiple domains to improve how scientific knowledge is created, shared, and used. Dr. Gil's work has significant impact across multiple scientific domains including climate science, neuroscience, and omics research. Her projects demonstrate her commitment to building knowledge-guided systems that transform how scientists conduct research. She has pioneered approaches to capture the provenance of scientific experiments and to automate the analysis of complex scientific data. Fellow of the Association for Computing Machinery (ACM) Fellow of the Association for the Advancement of Science (AAAS) Fellow of the Institute of Electrical and Electronics Engineers (IEEE) Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) 24th President of the Association for the Advancement of Artificial Intelligence Co-chair of the CRA/AAAI 20-Year Artificial Intelligence Research Roadmap for the US Initiator and leader of the W3C Provenance Group that resulted in a widely-used standard for web trust As an educator and leader, Dr. Gil directs the Data Science Program in Computer Science and serves as Co-Director of multiple joint MSc programs including Communication Data Science, Spatial Data Science, Environmental Data Science, Public Policy Data Science, and Healthcare Data Science. She also leads the new dual degree USC-Tsinghua University on Communication Data Science. Her leadership extends to mentoring numerous students and researchers in AI and data science. Through the USC Center for Knowledge-Guided Interdisciplinary Data Science (CKIDS), Dr. Gil organizes DataFest events each semester, fostering collaboration and innovation in data science across disciplines.
Omer Bayraktar is a Group Leader at the Wellcome Sanger Institute , leading research in the Cellular Genomics Programme. His work focuses on decoding human brain cellular diversity using spatial transcriptomics , imaging , and functional screening to study neural complexity in health and disease. Bayraktar's educational background includes a PhD from HHMI under Chris Doe, investigating neural diversity development in Drosophila , followed by postdoctoral work at University of California, San Francisco and University of Cambridge as a Life Sciences Research Foundation Fellow. He developed a spatial transcriptomic pipeline during his postdoc to analyze astrocyte heterogeneity in the cerebral cortex. His research explores neural cell type mapping , glial-neuronal interactions , and cellular pathways in neurodevelopmental disorders . Recent publications emphasize 3D tissue mapping , multi-omic integration , and computational tools like Cell2fate and WebAtlas. His work bridges neurogenetics and computational biology to advance understanding of human tissue ecosystems. Bayraktar's lab collaborates with the Human Cell Atlas initiative and develops technologies such as automated histology pipelines and highly-multiplexed smFISH for molecular cell typing. His team also investigates glia-based therapies and astrocyte functional heterogeneity in neurodevelopmental contexts. Key scientific contributions include: Discovering astrocyte layer patterns independent of neuronal laminae Developing cell2location for spatial cell mapping Characterizing Drosophila neural stem cell models with human relevance Notable awards include the Life Sciences Research Foundation Fellowship during his postdoctoral training. His current group includes a PhD student , Senior Data Scientists , and Bioinformaticians .
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.
Prof. Dr. Harald Lesch is a distinguished Professor of Theoretical Astrophysics at Ludwig Maximilian University of Munich and Lecturer in Natural Philosophy at the Munich School of Philosophy. Born on July 28, 1960 in Giessen, he completed his physics studies at Justus Liebig University of Giessen and Rheinische Friedrich-Wilhelms University of Bonn, earning his doctorate in 1987. After research positions at the Heidelberg-Königsstuhl State Observatory and University of Toronto, he received his habilitation at the University of Bonn in 1994. Lesch is renowned for making complex scientific concepts accessible to the public. His research interests span theoretical astrophysics, cosmology, gravitational waves, and the philosophical implications of scientific discoveries. He has authored numerous books exploring the relationship between science, philosophy, and everyday life, focusing particularly on how cosmic phenomena connect to human existence. His television career began in 1998 with 'Alpha Centauri' and 'The Physics of Albert Einstein' on BR-alpha. Since September 2008, he has presented ZDF's science magazine, which evolved from 'Abenteuer Forschung' to 'Leschs Kosmos' in 2014, and most recently to 'Terra X Harald Lesch' in 2024. In February 2016, he launched the YouTube channel 'Terra X Lesch & Co,' further expanding his science communication efforts. Patron of the Children's University Weimar since 2018 Presenter of 'The Big Questions' since 2023 Host of numerous documentary series including 'Fascination Universe' (2009-2023), 'Supercodes - The Secret Formulas of Nature' (2021/2022), and 'Das Rätsel Zeit' (2024) Lesch has received over 20 major awards recognizing his exceptional contributions to science communication, including the Communicator Prize (2005), multiple Deutscher Fernsehpreis awards (2018, 2020), and Germany's highest honor, the Verdienstorden der Bundesrepublik Deutschland (2023). His work bridges the gap between academic research and public understanding, making him one of Germany's most influential science communicators.
Prof. Daniel Memmert is a Professor at the German Sport University Cologne, leading research in Sport Informatics and Sports Games within the Institute of Exercise Training and Sport Informatics. His work focuses on cognitive aspects of sports performance, decision-making, and data-driven analysis in football (soccer) and other sports. He has published extensively on topics like penalty kick strategies, home advantage dynamics, artificial intelligence applications in coaching, and route-setting in climbing. Memmert's research bridges sports science, computer science, and psychology, with over 550 publications and 41 projects to his name. He frequently engages with media, explaining complex sports phenomena to the public. Key Research Areas: Football analytics, cognitive psychology in sports, sports technology, decision-making under pressure Media Contributions: Over 50 media features discussing topics such as AI in coaching, referee bias, and athlete creativity Projects: Includes initiatives on sports data visualization, performance metrics, and prevention of sports betting addiction His work emphasizes translating academic findings into practical tools for athletes, coaches, and sports organizations, combining rigorous data analysis with real-world applications.
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.
