Prof. Slawomir Stanczak is a Full Professor in Network Information Theory at Technische Universität Berlin and Head of the Wireless Communications and Networks department at Fraunhofer Heinrich-Hertz-Institut (HHI). His expertise spans wireless communications, signal processing, and machine learning, with a focus on 5G/6G networks and reconfigurable intelligent surfaces. He has held visiting roles at RWTH Aachen University and Stanford University, and leads initiatives like the 6G Research & Innovation Cluster and the xG-Incubator project. Education: Dipl.-Ing. in Electrical Engineering, TU Berlin (1998) Dr.-Ing. (summa cum laude), TU Berlin (2003) Habilitation (venia legendi), TU Berlin (2006) Research & Awards: Recipient of the Best Paper Award from the German Communication Engineering Society (2014) Research grants from the German Research Foundation Co-authored over 200 peer-reviewed papers and two books Chair of the ITU-T Focus Group on Machine Learning for Future Networks (2017-2020) Leadership & Projects: Chairman of 5G Berlin association since 2020 Coordinator of 6G Research & Innovation Cluster and CampusOS flagship project Project lead of xG-Incubator (StartUpConnect initiative) Teaching: Offers courses on Machine Learning and Wireless Communication at TU Berlin.
Prof. Dr. Anette Eva Fasang is a Full Professor of Microsociology at Humboldt University of Berlin, where she also serves as Director of the Department of Social Sciences and Academic Director of the Berlin Graduate School of Social Sciences (BGSS). She leads major research initiatives on life course stratification, social demography, and inequality, and has held leadership roles at the WZB Berlin Social Science Center. Her work bridges sociology, demography, and quantitative methodology, with a strong focus on comparative welfare state analysis. Ph.D. in Sociology, Jacobs University Bremen (2005–2009) B.A. and M.A. in Sociology, Ludwig-Maximilians-University Munich (1999–2004) Her research centers on life course dynamics, particularly how family formation, employment, and welfare regimes interact to shape social inequality across the lifespan. She employs advanced quantitative methods, especially sequence analysis, to study intergenerational transmission, gender disparities, and the long-term consequences of early-life trajectories. Her work spans comparative European and U.S. contexts and increasingly includes global perspectives, such as in Egypt and Senegal. The recent publications reflect a consistent focus on life course trajectories, social stratification, and methodological innovation. Key themes include the intersection of work and family, wealth and earnings accumulation, gender and racial inequality, and the impact of structural factors like welfare regimes and labor markets. Methodologically, her work advances sequence analysis and decomposition techniques for longitudinal data. Scientific Awards: Elected Fellow of the European Academy of Sociology (2024) Rosabeth Moss Kanter Award for Excellence in Work-Family Research (2023) Honorary Doctorate from the University of Turku (2022) Rosabeth Moss Kanter Award (2018) Prof. Fasang has supervised numerous doctoral students, many of whom have won top dissertation prizes. She leads significant research grants from the German Research Foundation (DFG), including the Cluster of Excellence SCRIPTS and the DYNAMICS research training group. Her advisory roles include the German Family Demographic Panel (FReDA) and scientific boards in Germany and Finland. She is actively involved in research teams and collaborative projects, such as the KOMPAKK study on household risks during the pandemic and the EQUALLIVES project on young adult life courses. Her work is deeply embedded in interdisciplinary networks across Europe and North America.
Max Planck Institute for Demographic ResearchGermany
Mikko Myrskylä is Director at the Max Planck Institute for Demographic Research (MPIDR) and Professor of Social Data Science at the University of Helsinki. Previously, he served as Professor of Demography at the London School of Economics. His academic training includes a PhD in Demography from the University of Pennsylvania and a PhD in Statistics from the University of Helsinki. His research focuses on population health, fertility dynamics, and demographic forecasting. Key areas include: Low fertility determinants through the ERC Synergy project BIOSFER Social inequalities in health via the Max Planck-University of Helsinki Center Labor demography and population aging He leads MPIDR's Laboratory of Population Health, Laboratory of Fertility and Well-Being, and Research Group Labor Demography. Myrskylä's recent publications show strong emphasis on: Fertility trends under economic uncertainty Health disparities across migration/life course stages Family dynamics and aging societies Methodological innovations in demographic analysis Work frequently employs large-scale register data and cross-national comparisons, particularly in Nordic contexts. He leads major collaborative initiatives including: ERC Synergy project BIOSFER (low fertility causes) MaxHel Center (social inequalities in health) with extensive interdisciplinary teams across Europe.
Olaf Kaczmarek is a researcher at the Faculty of Physics , Bielefeld University , specializing in Lattice Quantum Chromodynamics (QCD) and Strongly Interacting Matter . He leads projects related to QCD thermodynamics , quark-gluon plasma , and heavy quark transport . Principal Investigator in TRR 211/2 Subproject A06: Hadronic Excitations and Spectral Functions in the Medium (2025) Co-PI in TRR 211/2 Subproject Z02: Software Development Center (2025) Contributor to GPUHEP2014 and LATTICE2024 symposia Research Focus: Thermal QCD phase transitions, heavy quark diffusion , transport coefficients , lattice simulations , and quarkonium spectroscopy . His work bridges theoretical physics and high-performance computing , particularly in Multigpu Systems for QCD calculations. Recent Publications explore topics like the chiral crossover , spatial string tension , and thermal photon production , with keywords spanning Quantum Chromodynamics , Lattice Gauge Theory , and High Temperature Physics . Teaching: Offers courses in Lattice Field Theory , GPU Computing , and Gradient Flow for graduate students. Contributes to collaborative seminars in the CRC-TR211: Strong-interaction matter under extreme conditions .
Prof. Melanie Schienle is a Professor and Chair of Statistical Methods and Econometrics at the Department of Economics and Management, Karlsruhe Institute of Technology (KIT). She also holds a professorship in the Department of Mathematics at KIT since 2021. Her expertise spans statistical methods, econometrics, financial risk analysis, and forecasting. She leads the HKMetrics Network and the RespiNow Hub for respiratory disease forecasting. She serves as a Senior Fellow at the Rimini Center for Economic Analysis (RCEA), a steering committee member of the German Economic Association, and a member of the University Research Council at KIT. Education: Ph.D. (Dr. rer. pol.) in Economics from Mannheim University (2008), summa cum laude; Diploma in Mathematics (University of Karlsruhe, 2003) with a minor in theoretical physics. She has held academic positions at Leibniz University Hannover (2012–2015) and Humboldt University of Berlin (2008–2012). Research interests focus on financial networks, systemic risk, time series analysis, and machine learning applications in economics. She co-leads projects on nowcasting and forecasting, including collaborative efforts during the pandemic to predict hospitalizations. Her work integrates advanced statistical techniques with real-world policy implications. Prof. Schienle is an Associate Editor for the International Journal of Forecasting and Journal of Time Series Analysis . She has authored over 50 peer-reviewed publications and contributed to high-impact journals like Nature Communications and Journal of Business & Economic Statistics . She leads the Institute of Statistics at KIT and chairs the MathSEE initiative for interdisciplinary mathematical applications.
Daniel Wilhelm is a Professor of Statistics and Econometrics at LMU Munich, with a courtesy appointment in the Department of Economics. His research focuses on econometric theory, nonparametric methods, measurement error modeling, and statistical inference. He leads the Statistics and Econometrics Group at LMU and holds affiliations with the Centre for Microdata Methods and Practice (CeMMAP), Institute for Fiscal Studies (IFS), and the Centre for Research and Analysis of Migration (CReAM). Wilhelm’s work includes groundbreaking contributions to NPIV estimation, robust statistical testing, and the development of R and Stata packages for rank inference and econometric analysis. His recent publications address topics like rank-based inference, measurement error detection, and high-dimensional independence testing. He organizes academic events such as the Munich Econometrics Seminar and the LMU-Todai Econometrics Workshop. His research emphasizes methodological rigor and practical applications, with a focus on improving statistical techniques for social science and policy analysis.
Helmholtz Centre for Environmental ResearchGermany
Prof. Dr. Ralf Merz serves as Head of the Department of Catchment Hydrology at the Helmholtz Centre for Environmental Research (UFZ) and holds a Full Professorship in Catchment Hydrology at Martin-Luther University Halle-Wittenberg since 2011. His career bridges hydrological modeling, flood risk assessment, and water quality analysis across diverse climates from Central Asia to Europe. MSc in Civil Engineering (Technical University of Karlsruhe, 1997) PhD in Hydrology (Vienna University of Technology, 2002) Habilitation in Hydrology (Vienna University of Technology, 2009) Research Interests span comparative hydrology, flood generation mechanisms, climate change impacts on water resources, and nitrate dynamics in river systems. His work emphasizes process-based understanding of runoff events and regional flood modeling through innovative approaches like the PHEV distribution framework. Scientific Contributions include over 100 publications (2003-2025) on: Flood frequency analysis in changing climates Groundwater recharge in arid regions Hydrochemical response to droughts Remote sensing applications for groundwater studies Multi-response calibration of hydrological models Key projects involve MOSES observatory development, TRACER research school, and Pamir Mountains glaciological studies. Recognitions : APART research grant (Austrian Academy of Sciences, 2006) Leadership extends to directing the Catchment Hydrology department and participating in European hydrological networks like the Bode Hydrological Observatory and TERENO infrastructure. His methodological advancements include flood time-scale analysis and event runoff coefficient regionalization.
Barbara Drossel is a Full Professor at the Institute of Solid State Physics within the Faculty of Physics at the Technical University of Darmstadt, where she has been conducting research since February 2002. Her work bridges theoretical physics, complex systems theory, and theoretical ecology, focusing on interdisciplinary approaches to understanding emergent phenomena in natural systems. She leads the AG Drossel research group that investigates the theoretical foundations of complex networks, ecological communities, and quantum systems. Professor Drossel's research spans multiple domains with emphasis on complex systems theory, where she has made significant contributions to understanding random Boolean networks, food web modeling, and the physics of ecological communities. Her work demonstrates how simple rules can lead to complex emergent behavior across different scales, from quantum systems to ecological networks. She investigates how top-down causation operates in complex systems and explores the relationship between microscopic dynamics and macroscopic patterns in diverse contexts. Analysis of her recent publications reveals a consistent focus on theoretical frameworks that connect physics with ecology. Her work shows increasing integration of quantum mechanics with ecological modeling, particularly in understanding emergence and time evolution in complex systems. She frequently employs network theory to analyze ecological communities and has developed innovative approaches to studying species interactions, mutualistic networks, and spatial dynamics in meta-communities. Minerva Fellowship Heisenberg Fellowship DFG Fellowship for research at MIT Professor Drossel has supervised numerous doctoral students whose work spans theoretical ecology, complex systems, and statistical physics. Her research group has secured funding for projects examining the stability of ecological networks, quantum decoherence, and the mathematical foundations of complex systems. She maintains active collaborations with researchers across Europe and has contributed to major theoretical advances in understanding how complexity emerges from simple interactions in diverse systems. The AG Drossel research group operates at the intersection of physics and theoretical biology, maintaining strong connections with both the physics and biology departments at TU Darmstadt. The group combines mathematical rigor with biological relevance, developing models that capture essential features of complex natural systems while remaining analytically tractable. Their work has influenced both theoretical physics and ecological theory, demonstrating the power of interdisciplinary approaches to complex systems.
Ulrich Tallarek serves as Professor of Analytical Chemistry in the Faculty of Chemistry at Philipps University of Marburg, where he has held a W3 professorship since 2011. He also serves on the Board of Directors for the Materials Science Center at the university, a position he has held since 2007. His research group focuses on the fundamental understanding of transport phenomena in porous media with applications spanning chromatography, battery technology, and microfluidic systems. The group maintains strong collaborations with institutions worldwide and secures substantial research funding for advanced computational and experimental work. Professor Tallarek's research interests center on functional porous solids, with specific focus on morphology-transport-performance relationships. His work bridges multiple scales from molecular dynamics simulations of solute behavior in nanopores to macroscopic transport in chromatographic columns and battery electrodes. Key research areas include diffusion in hierarchical porous media, electrokinetic phenomena in microfluidic systems, molecular simulation of chromatographic processes, and advanced characterization of porous materials using tomography and other techniques. His group has pioneered multiscale simulation approaches that connect molecular-level surface chemistry to macroscopic transport properties. The research output demonstrates consistent focus on understanding fundamental transport mechanisms in porous systems, with recent publications emphasizing multiscale simulation techniques, molecular dynamics studies of solvent effects in chromatography, advanced characterization of mesoporous structures, and applications to separation science and energy storage. The work shows strong integration of computational modeling with experimental validation across multiple length scales. 2003: Desty Memorial Prize for Innovation in Separation Science, The Royal Institution of Great Britain, London 2006: Young Scientist Award from DECHEMA e.V. 2011: Named Discussion Leader at the 2011 Gordon Research Conference on Physics & Chemistry of Microfluidics 2011–2012: Chairman of the German Chemical Society (GDCh), Marburg 2013: Finalist, World Technology Awards, for category Environment 2013: Named as one of the 100 most influential analytical scientists in the world (The Analytical Scientist Power List) 2017: Recipient of the Silver Jubilee Medal 2017, The Chromatographic Society, UK Professor Tallarek's research has been supported by numerous grants enabling high-performance computing resources, advanced instrumentation, and international collaborations. His group maintains strong ties with industry partners in separation science and analytical instrumentation. The Tallarek Research Group includes postdoctoral researchers, PhD students, and technical staff working across experimental and computational domains. Current projects focus on molecular simulation of chromatographic processes, advanced characterization of porous battery electrodes, and development of novel separation methodologies. The Tallarek Research Group operates state-of-the-art facilities for computational modeling, including access to high-performance computing resources at Forschungszentrum Jülich. The group also maintains experimental capabilities for chromatographic analysis, materials characterization, and microfluidic device development. Their work on physically reconstructed porous media has established new standards for connecting microstructure to transport properties in complex materials systems.
Volker J Schmid is a Professor of Bayesian Imaging and Spatial Statistics at the Department of Statistics, Ludwig Maximilian University of Munich. He leads the Bayesian Imaging and Spatial Statistics group and contributes to interdisciplinary initiatives like the Munich Center of Machine Learning. His work bridges statistical theory with applications in medical imaging and biology. PhD in Statistics (2004), LMU Munich Diploma in Statistics (2000), LMU Munich Abitur, Joseph-von-Fraunhofer-Gymnasium Cham (1993) His research focuses on Bayesian computational methods for high-dimensional data, particularly in medical imaging (MRI, DCE-MRI) and biological microscopy (e.g., 3D nuclear architecture analysis via super-resolution microscopy). Key applications include disease mapping , image segmentation , and spatio-temporal modeling . His software tools (e.g., nucim , bioimagetools , BAMP ) enable quantitative analysis in nuclear imaging and age-period-cohort modeling. His 15 most recent publications span Bayesian modeling for medical imaging , spatio-temporal epidemiology , and computational biology . Topics include co-localization metrics in fluorescence microscopy, nuclear architecture analysis, and dynamic Bayesian frameworks for MRI data. Collaborations extend to neuroimaging, oncology, and nuclear biology.
Niels Dingemanse is a tenured Professor of Behavioural Ecology at Ludwig Maximilians University (LMU) in Munich, Germany, and leads the Evolutionary Ecology of Variation research group at the Max Planck Institute for Ornithology. His academic journey includes roles as a Postdoctoral Research Fellow at the University of Groningen and the University of Wales, Bangor. He holds a PhD in natural sciences from Utrecht University (2003) and an M.Sc. in Ecology from the University of Groningen (1997). His research focuses on evolutionary and behavioural ecology, particularly the ecological and evolutionary significance of individual variation in behaviour, physiology, and life-history traits. Key themes include personality evolution, indirect genetic effects, and the integration of genomic approaches with ecological field studies. Dingemanse has contributed to projects like the Great Tit HapMap initiative, exploring genomic variation across continental scales. Publications emphasize interdisciplinary methods, combining field experiments with genomic and statistical tools. His work addresses topics such as mate choice evolution, the role of environmental fluctuations in shaping social plasticity, and the genetic basis of vocal rhythms in birds. Grants and fellowships include the Veni Innovational Research Incentives Scheme (Netherlands Organisation for Scientific Research) and ALW open competition grants. He has advised numerous postdoctoral researchers and leads collaborative projects across Europe.
Stefan Riezler is a full professor of Statistical Natural Language Processing at Heidelberg University's Department of Computational Linguistics (since 2010), affiliated with the Faculty of Mathematics and Computer Science. Prior to this, he worked in Silicon Valley at Xerox PARC and Google Research. He holds a PhD in Computational Linguistics from the University of Tübingen (1998) and conducted postdoctoral research at Brown University (1999). His research spans machine learning, NLP, and medical informatics, focusing on interactive statistical learning. He co-leads the Interdisciplinary Center for Scientific Computing (IWR) and serves on the editorial boards of Computational Linguistics and Transactions of the Association for Computational Linguistics . Key research areas include neural machine translation, healthcare AI (e.g., sepsis prediction), data augmentation, and reproducibility in ML. He develops tools like JoeyNMT and explores ethical challenges in clinical machine learning. Notable recent work includes advancements in time series analysis, multimodal interfaces (e.g., NLMaps for OpenStreetMap), and ethical frameworks addressing validity in healthcare ML. His publications emphasize practical applications of NLP in healthcare, speech translation, and cross-lingual systems. Grants and collaborations include interdisciplinary projects on medical data science and training next-gen NLP researchers. He actively contributes to open-source toolkits and reproducible research practices.
Prof. Laura Busse is a Professor at Ludwig Maximilian University of Munich (LMU), leading the Research Group in the Department of Biology II, Division Neurobiology. She holds roles as a Regular Member of MCN, Full Member of GSN, and Deputy Head of the GSN Examination Board. Her research focuses on cellular and systems neuroscience, particularly investigating how contextual information influences visual perception through neural circuits in mice. Key areas include feedback mechanisms, behavioral state effects, and thalamocortical interactions. Her work employs advanced techniques like high-density extracellular recordings and optogenetics to study active behavior in rodents. Current students include Simon Renner, Gregory Born, and others. Recent research highlights include studies on corticothalamic feedback effects, thalamic spatial integration, and the role of pupil dynamics in neural activity. She leads the Vision Circuits Lab (https://visioncircuitslab.org), exploring how sensory inputs and brain states shape visual processing. Her articles reveal trends in understanding thalamocortical communication, adaptive sensory systems, and the biological basis of neural network models. She coordinates the SPP2411 project on cortico-subcortical loops, emphasizing interdisciplinary neuroscience.
Weierstrass Institute for Applied Analysis and StochasticsGermany
Marco Cuturi is a Research Scientist at Apple ML Research in Paris and Professor of Statistics at CREST-ENSAE, Institut Polytechnique de Paris. His work bridges machine learning , optimal transport , and optimization , with applications in time-series analysis , kernels , and multiresolution methods . He has held academic roles at Kyoto University and Princeton University, and previously worked in the financial industry. Research Interests: Optimal transport theory and computational methods Kernel design for structured data and histograms Time-series alignment and soft-DTW Entropic regularization in optimization Applications to computer vision and genomics Teaching: Cuturi has taught courses on linear optimization at Princeton, geometric methods in machine learning at Kyoto, and scientific English. He has also organized machine learning summer schools in Kyoto, Les Houches, and other international venues. Recent Trends: His 2024-2025 publications focus on entropic optimal transport solvers, disentangled representation learning via Gromov-Monge gaps, and applications to text-to-image diffusion models. Collaborative work with institutions like Google Research, MIT, and University of Tokyo highlights his interdisciplinary impact.
Prof. Dr. Helen Baykara-Krumme is a full-time Professor of Sociology with a focus on Migration and Participation at the Institute of Sociology, University of Duisburg-Essen since March 2019. She serves as Managing Director of the Institute of Sociology (2020-2022), Chair of the Faculty of Humanities Ethics Committee since 2020, and Chair of the InZentIM Board since 2024. Her research spans migration, transnationalization, integration, and participation, with specialized focus on family processes in migration contexts, life course analysis, aging in migration contexts, migration-related organizational change, migration-disability intersections, and urban research methodologies. Education: Sociology, Statistics, and Agricultural Sciences (1995-2002, Free University & Humboldt University Berlin); PhD in Philosophy (2007, Free University Berlin); Habilitation (2017, Chemnitz University of Technology) Research Leadership: Coordinated BMBF-funded ZOMiDi project on civil society responses to migration diversity; edited Organisationaler Wandel durch Migration? (2022); contributed to the Ninth Family Report of the Federal Government (2016-2021) Methodological Expertise: Quantitative survey methods, intergenerational solidarity analysis, urban ethnography, and intersectional frameworks Awards: Fellow of the International Max Planck Research School LIFE (2002-2006) Teaching: Supervises final theses, leads courses on migration and globalization, and maintains regular consultation hours
