Florian Strunk is a Professor in the Department of Mathematics at the University of Regensburg, working within the Faculty of Mathematics. His office is located in room M219 (phone: +49 941 943 2768) and his contact email is florian.strunk@ur.de. Dr. Strunk's research spans several interconnected areas of modern mathematics, with primary focus on Algebraic Geometry, Arithmetic Geometry, and Homotopy Theory. He has developed specialized expertise in Algebraic K-Theory, Motivic Homotopy Theory, and Derived Algebraic Geometry. His scholarly work bridges classical algebraic geometry with contemporary homotopy-theoretic methodologies, advancing our understanding of structural properties of algebraic varieties and schemes. His publication record demonstrates consistent contributions to Algebraic K-Theory and motivic homotopy theory, with significant work on descent properties, connectivity in motivic contexts, and algebraic cycles. His collaborative research with prominent mathematicians like Moritz Kerz and Georg Tamme has appeared in top-tier journals including Inventiones Mathematicae and Compositio Mathematica. As an educator, Dr. Strunk teaches across the mathematics curriculum, from foundational undergraduate courses to advanced graduate seminars. His teaching portfolio includes Algebraic Geometry I and II, Mathematics of Machine Learning, Introduction to Quantum Computing Mathematics, and specialized seminars on Algebraic K-Theory. He has developed comprehensive lecture notes for several courses, reflecting his commitment to effective pedagogy.
Prof. Dr. Gerhard Huisken is a Professor at Eberhard Karls University of Tübingen and Director of the Mathematical Research Institute Oberwolfach. His research focuses on geometric analysis, differential geometry, and mathematical relativity, with significant contributions to mean curvature flow, Ricci flow, and geometric evolution equations. He has authored numerous influential papers on topics such as curvature flows, singularity analysis, and applications to general relativity. Key positions include leadership at Oberwolfach and teaching roles in advanced courses like 'Mathematical Relativity' and 'Introduction to Ricci Flow'. His work bridges geometric analysis with physics, contributing to the Poincaré conjecture through Ricci flow studies. Collaborations include projects with S. Brendle and C. Sinestrari on convex solutions and flow surgeries. Research highlights include the Riemannian Penrose inequality, inverse mean curvature flow, and long-term behavior of geometric flows. His academic contributions are documented in top journals like Inventiones mathematicae and Journal of Differential Geometry .
Professor Vitali Wachtel of Bielefeld University's Faculty of Mathematics specializes in advanced stochastic processes, probability theory, and their applications in mathematical modeling. Since 2021, he holds a W3 Professorship and serves as Principal Investigator in CRC 1283 'Taming uncertainty and profiting from randomness and low regularity in analysis, stochastics and their applications' since 2023. Chaired Examination Boards for Bachelor & Master Business Mathematics Member, Bielefeld Graduate School in Theoretical Sciences Research focus: Markov processes, random walks in cones, branching processes Research Trends: His recent work spans critical multitype branching in random environments (2025), asymptotic expansions for conditioned random walks (2024), and invariance principles for integrated processes. He explores connections between stochastic processes, combinatorial structures, and risk modeling with level-dependent premiums. Awards: Feodor Lynen Research Fellowship (2017), Alexander von Humboldt Foundation Teaching: Coordinates modules including 'Stochastic Processes' (24-M-PT-STP) and 'Introduction to Probability Theory' (24-B-EW-5). Active in curriculum development and academic governance through multiple university committees.
Professor Asaf Shapira is a faculty member in the Department of Theoretical Mathematics at Tel Aviv University's School of Mathematical Sciences. He has been actively contributing to combinatorics and graph theory research for over a decade, with numerous publications in top journals including Journal of the ACM, Advances in Mathematics, and Geometric and Functional Analysis. Professor Shapira's research focuses on extremal combinatorics, graph theory, and property testing. His work explores fundamental questions in Ramsey theory, hypergraph theory, and probabilistic methods in combinatorics. He has made significant contributions to the study of graph regularity, removal lemmas, and extremal problems in dense and sparse graphs. His recent publications demonstrate a consistent focus on theoretical aspects of combinatorics with connections to theoretical computer science. A notable trend is his work on developing polynomial bounds for various combinatorial theorems and exploring connections between combinatorial structures and computational complexity. His research often bridges pure mathematics with theoretical computer science applications. Professor Shapira teaches advanced courses at Tel Aviv University including Extremal Graph Theory, Basic Combinatorics, and seminars on specialized topics in combinatorics. His teaching spans undergraduate and graduate levels, reflecting his commitment to educating the next generation of mathematicians.
Philipp Otto is a Professor of Statistics and Data Science at the University of Glasgow. Previously, he was a Reader in Statistics and Data Analytics (2023–2024) and held a Junior Professorship in Big Geospatial Data at Leibniz University Hannover (2018–2023). He earned his PhD in Statistics (summa cum laude) from European University Viadrina in 2016 and a B.Sc. in International Economics, with study visits to Saint Petersburg State University. His research focuses on spatial and spatiotemporal statistics, environmetrics, network modeling, and machine learning applications. Education: PhD in Statistics (2016), European University Viadrina, Frankfurt (Oder) B.Sc. in International Economics (with study visits to Saint Petersburg) Research Interests: Philipp’s work centers on spatial statistics, spatiotemporal volatility modeling, environmental data analysis, and network processes. He develops statistical methods for geo-referenced and network data, with applications in climatology, finance, and environmental risk assessment. His contributions include advancements in GARCH models, spatiotemporal clustering detection, and statistical process monitoring for AI systems. Grants & Projects: He has secured €1,038,847 in research grants, leading projects on historical map time series analysis, agricultural air quality impacts, and high-dimensional spatial dependence structures. Industry collaborations include survival analysis for building information models. Awards: 2017 Fellowship to attend the Lindau Nobel Laureate Meeting (Economic Sciences) 2017 Best Presentation Award (Data Science, Statistics, and Visualisation) Teaching: He teaches statistics and data science across disciplines, including economics, engineering, and mathematics, at both undergraduate and postgraduate levels. Professional Activities: Editorial Boards: Environmetrics (2021), AStA Advances in Statistical Analysis (2020) Member of German Statistical Society (Treasurer, 2013)
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.
Professor Stephan A. Sieber is a leading researcher in bioorganic chemistry at the Technical University of Munich (TUM), where he holds the Chair of Organic Chemistry II within the TUM School of Natural Sciences. His research program focuses on developing new drugs against multidrug-resistant bacteria through a multi-disciplinary approach that integrates synthetic chemistry, functional proteomics, microbiology, and protein biochemistry. His laboratory has made significant contributions to identifying unprecedented antibacterial targets beyond the scope of current antibiotics and exploiting these for chemical manipulation. Recent work has increasingly incorporated machine learning approaches to accelerate antibiotic discovery, with notable publications on AI-guided pipelines, drug-target interaction prediction, and high-throughput screening optimization. Sieber's research has resulted in the discovery of new active substances, some of which are currently being optimized for medical applications. His group's publications reveal a strong focus on chemical proteome mining, natural product mode of action studies, and novel antibacterial target identification. The lab has published extensively in top journals including Nature Chemistry, Nature Communications, and ACS Central Science. Inhoffen Medal (2024) Max Bergmann Medal (2023) ERC Advanced Grant (2023) Merck Future Insight Prize (2020) Klaus Grohe Prize (2020) ERC Consolidator Grant (2016) Professor Sieber leads an active research group that maintains a strong presence in the scientific community through regular publications, conference presentations, and collaborations. His laboratory website and BlueSky presence (@sieberlab.bsky.social) demonstrate ongoing research activities and engagement with the broader scientific community. He has successfully secured significant research funding including multiple ERC grants that have supported his innovative work in antibiotic discovery.
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
Prof. Dr. Matthias Weidlich is a faculty member at Humboldt University of Berlin within the Institute of Computer Science under the Faculty of Mathematics and Natural Sciences . His research focuses on Process Mining , Complex Event Processing , and Data Privacy with applications in Business Process Management and Scientific Workflows . Research Interests: Business Process Management and Process Mining Complex Event Processing and Stream Data Analysis Data Privacy and Security in Process Systems Scientific Workflow Systems and User Behavior Heterogeneous Network Embeddings Algorithm Design and Optimization Recent Publications (2023-2025) demonstrate expertise in: Efficient stream processing techniques Privacy-preserving process mining frameworks Scientific workflow analysis tools Graph neural network applications Multi-modal data integration Adaptive querying systems Contact: Office: Unter den Linden 6, 10099 Berlin Phone: 030 2093-41277 Email: matthias.weidlich@hu-berlin.de Web: hu.berlin/data
Prof. Dr. Barbara Praetorius is a leading scholar in sustainability economics at HTW Berlin since 2017. She co-chaired Germany's Coal Commission ("Kommission Wachstum, Strukturwandel und Beschäftigung") and serves on advisory boards for Berliner Wasserbetriebe and VERBUND AG. Her work bridges climate policy, energy economics, and social equity, with a focus on Germany and the Global South. Research Themes: Climate economics, decarbonization pathways, renewable energy integration, and sustainable development in emerging economies. Policy Influence: Regular contributor to national climate policy debates, particularly on carbon pricing and coal phase-out strategies. Academic Roles: Professor at HTW Berlin's Department 3: Economics and Law since 2017, previously Deputy Director of Agora Energiewende (2014-2017). Recent Publications emphasize plug-in solar systems' socio-economic impacts, just coal transitions in Hesse, and ecological industrial policy frameworks. Her 2024 work on energy market transformation highlights the need for policy innovation and market redesign. Scientific Recognition : Ranked among Germany's most influential female economists by FAZ Active in EU energy policy advisory roles Recipient of BMBF research funding for international projects
Matthew K. Tam is an Associate Professor at the School of Mathematics and Statistics, The University of Melbourne, specializing in Operations Research. He is also an investigator at the Melbourne Centre for Data Science and an associate investigator in the ARC Training Centre OPTIMA. PhD in Mathematics (2016) from University of Newcastle under Jonathan Borwein Postdoctoral research at University of Göttingen with RTG-2088 and Alexander von Humboldt Foundation Junior Professor at University of Göttingen (2017-2020) His research focuses on continuous optimization, monotone operator theory, and variational analysis, with applications in wavelet construction and inverse problems. Key trends include distributed algorithms, resolvent splitting, and convergence analysis for feasibility problems. Discovery Early Career Researcher Award (DECRA) Alexander von Humboldt Fellowship He collaborates with institutions like ANZIAM, Springer, and IEEE, with publications spanning mathematical optimization, harmonic analysis, and computational mathematics. His work emphasizes algorithmic design for complex data systems and real-world applications in imaging and industrial modeling.
Angkana Rüland is a Professor at the University of Bonn's Mathematical Institute and holder of the Hausdorff Chair at the Hausdorff Center for Mathematics (HCM), a Cluster of Excellence. She is a member of the Transdisciplinary Research Area ‘Modelling’ and a recipient of the prestigious Leibniz Prize (2025). Her research focuses on inverse problems, fractional PDEs, and phase transformations in materials science, with contributions to the Calderón problem and microstructure analysis. She has held positions at Oxford, the Max Planck Institute in Leipzig, and Heidelberg University before returning to Bonn in 2023. Education: She completed her Abitur, bachelor's/masters, and PhD (2014, Hausdorff Memorial Prize) at the University of Bonn, where she also co-founded the Bonn Math Club. Her academic journey includes postdoctoral research at Oxford and leadership roles in Leipzig and Heidelberg. Research interests span inverse problems (e.g., fractional Calderón problem), material microstructures (shape-memory alloys), and mathematical physics. Her work bridges pure and applied mathematics, addressing questions in elasticity, nonlocal operators, and energy scaling laws. Scientific awards include the Leibniz Prize (2025) for her groundbreaking research and the Hausdorff Memorial Prize for her doctoral thesis. She aims to use Leibniz Prize funds to strengthen her research group at HCM, furthering interdisciplinary collaborations. Her contributions have positioned Bonn as a global leader in mathematical research, with 20 Leibniz laureates since 1986.
Dr. Ruojun Huang is affiliated with the Department of Mathematics and Computer Science at the University of Münster, part of the Institute for Analysis and Numerical Analysis within Applied Mathematics Münster. His research focuses on probability theory and mathematical physics, particularly stochastic processes and their applications. He contributes to advancing theoretical frameworks such as regularity structures to analyze complex systems. His work includes a notable publication on scaling limits in exclusion processes, published in 2025. Huang’s academic role involves research activities within the institute, with no explicit mention of awards or grants in the provided texts. He is reachable via email and is based in Room 130.025 at Orléans-Ring 10, Münster.
Rainald Loehner is a Distinguished Professor of Fluid Dynamics at George Mason University's Center for Computational Fluid Dynamics. Since 2003, he has led the Center for Computational Fluid Dynamics at George Mason University. He is currently a Hans Fischer Senior Fellow at the Technical University of Munich's Institute for Advanced Study (TUM-IAS) for 2023, hosted by Professors Kai-Uwe Bletzinger and Roland Wüchner in the 'Adjoint-Based System Identification of Large-Scale Structures' Focus Group. Loehner received his Diplom Ingenieur (Maschinenbau) degree from the Technical University of Braunschweig, and his PhD and a DSc in civil engineering from the University College of Swansea, Wales. After teaching at Swansea for a year, he worked at the Naval Research Laboratory in Washington, DC, followed by a research professorship at George Washington University. He joined George Mason University as an associate professor and was promoted to full professor in 1995 and distinguished professor in 2004. With over 35 years of experience, Professor Loehner's research spans the complete pipeline of numerical solvers and simulation tools. His expertise includes pre-processing, grid generation, numerical methods, field solvers, parallel computing, adaptive mesh refinement, fluid-structure interaction, shape optimization, system identification, and computational crowd dynamics. His current work focuses on developing advanced field solvers for compressible and incompressible flows, acoustics, electromagnetic wave propagation, heat and mass transfer, structural mechanics, and fluid-structure interaction. Key application areas include blast mitigation, ship hydrodynamics, blood flow, contaminant transport, and pedestrian safety. Loehner's recent research output (2020-2024) shows a strong trend toward digital twin technology and adjoint-based methods for structural analysis and optimization. His publications focus on high-fidelity digital twins for detecting structural weaknesses, risk assessment in engineering systems, and optimization of sensor placement. His work bridges computational mechanics with machine learning approaches, particularly in system identification and inverse problems, demonstrating how computational methods can solve complex real-world engineering challenges. 2020: Ranked #15119 in the Stanford List of Most Influential Scientists of the World; #8 in Aerospace and Aeronautics 2010: Distinguished International Career Award, Argentine Association of Computational Mechanics 2008: Fellow, International Association for Computational Mechanics 2006: Associate Fellow, AIAA 2005: Honorary Professor, University of Wales Swansea 2005: Advisory Professor, Shanghai Jiao Tong University 2004: Distinguished Professor of Fluid Dynamics, George Mason University 1999: Computational Mechanics Achievements Award, Japan Society of Mechanical Engineering 1993: Doctor of Science in Civil Engineering, University College of Swansea 1979-1983: Studienstiftung des Deutschen Volkes (Top 1% of German Students) Professor Loehner has mentored numerous students through his work at George Mason University and has supervised research in computational fluid dynamics, structural mechanics, and related fields. His research has been supported by various grants from government agencies and industry partners, enabling the development of advanced simulation tools applied in aerodynamics, hydrodynamics, shock-structure interaction, and medical applications. His codes and methods have been widely adopted in industry and academia for applications ranging from aircraft and ship design to medical simulations and urban pathogen transmission modeling. Loehner leads the Center for Computational Fluid Dynamics at George Mason University, which focuses on developing cutting-edge computational methods for fluid dynamics and related multiphysics problems. The center works on strategic application areas including blast mitigation, ship hydrodynamics, blood flow simulation, and pedestrian movement modeling. As a TUM-IAS Fellow, he collaborates with the Chair of Computational Modeling and Simulation at TUM on adjoint-based system identification of large-scale structures, bringing together expertise in computational mechanics and digital twin technology to address complex engineering challenges.
Benny Moldovanu is Professor of Economics at the University of Bonn, where he holds the Chair of Microeconomics. He is a principal investigator in the Collaborative Research Center TR 224 (CRC TR 224) and a member of the Cluster of Excellence ECONtribute: Markets & Public Policy, as well as the Hausdorff Center for Mathematics and the Bonn Graduate School of Economics (BGSE). Education: Detailed curriculum vitae available at CV link . Research Interests: His research focuses on auctions and mechanism design , microeconomic theory , information design , voting theory , and dynamic allocation problems . He has made significant contributions to understanding strategic behavior in auctions, optimal voting rules, and the design of mechanisms under incomplete information. Recent Publications Trend: Recent work (2020–2025) explores entropy-regularized optimal transport in information design, optimal security design for risk-averse investors, order independence in sequential voting, and insurance design under adverse selection. These studies combine sophisticated theoretical tools with applications in finance, political economy, and market design. Scientific Awards and Honors: Winner of the first AEA Best Paper Award for the American Economic Journal: Microeconomics (2009) for “Dynamic Revenue Maximization with Heterogeneous Objects: A Mechanism Design Approach”. Advising and Doctoral Training: Professor Moldovanu has supervised a large cohort of doctoral students and postdocs, many of whom now hold faculty positions worldwide (e.g., Philipp Strack—Clark Medal recipient, Alex Gershkov, Andreas Kleiner, Xianwen Shi, Thomas Kittsteiner). He teaches Microeconomics II (summer 2025) and offers thesis supervision to BGSE students. Labs and Research Groups: He leads the Microeconomics Research Group at Bonn and coordinates research activities in the CRC TR 224 project B01, focusing on market design and information economics.
