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Fredrik UllénView profile

Professor

• Cognitive Neuroscience
• Neuropsychology
• Behavior Genetics
• +4 more

Fredrik Ullén is a Professor of Cognitive Neuroscience at the Karolinska Institutet's Department of Neuroscience since 2012. He currently serves as Director of the Department of Cognitive Neuropsychology at the Max Planck Institute for Empirical Aesthetics. His previous roles at Karolinska include Professor of Cognitive Neuroscience (2010-2011), University Lecturer (2009-2010), Senior Researcher (2006-2009), and Assistant Professor (2001-2005) in the Department of Women's and Children's Health. Karolinska Institutet: Professor, Senior Researcher, Assistant Professor Max Planck Institute: Director Research Interests : Ullén's work spans cognitive neuroscience, neuropsychology, and creativity, with a focus on skill learning, genetic influences on expert performance, and brain mechanisms underlying creative cognition. He investigates how genetic factors interact with environmental variables to shape cognitive abilities and explores neural networks associated with flow states, improvisation, and individual differences in creative potential. Scientific Awards : Lifetime Fellow of the Swedish Royal Academy of Music (2007) Scientific Member of the Max Planck Society (2021) Member of Academia Europaea (1999) Award of Excellence (2001) Article Trends : Ullén’s recent publications examine creativity through genetic and neuroimaging lenses, linking polygenic risk scores for psychiatric disorders to creative traits. Earlier work investigates neural plasticity in musicians, functional connectivity in improvisation, and dopamine's role in implicit learning and flow experiences. His studies frequently employ interdisciplinary approaches combining cognitive psychology, genetics, and neuroimaging.

• Developmental Genomics
• Computational Biology
• Bioinformatics
• +2 more

Kristian Vlahoviček is a tenured Professor and Bioinformatics Group Leader at the Faculty of Science , University of Zagreb, Croatia, with a 18-year track record of leading an internationally competitive research group. He has held international appointments at the ICGEB Trieste (Italy) and the University of Oslo (Norway), and co-founded Exaltum Ltd. in 2013. Education: PhD in Computational Biology and Bioinformatics Research Focus: His group combines machine learning with bioinformatics to address key questions in developmental genomics and metagenomics , including protein interaction prediction, histone modification analysis, and retrotransposon dynamics in embryogenesis. Publications: His work appears in top-tier journals like Nature , Cell , and PNAS , with citations exceeding 4,000 (Google Scholar), reflecting significant impact in computational biology, genetics, and epigenetics. Scientific Awards: 2011 Annual National Science Award (Croatia) 2009 Croatian Academy of Sciences and Arts Award EMBO Young Investigator Installation Grant (2006-2011) ICGEB Fellowship (1996-2000) University of Zagreb Rector’s Award (1995) Service: He has served as a reviewer for major international funding programs including the European Science Foundation, EC FP7/H2020, ZonMw Vidi Programme, and Croatian structural funds. His research group develops computational tools and machine learning frameworks for genomic and metagenomic analysis.

Maryna ViazovskaView profile

Professor

• Sphere packing
• Fourier analysis
• Automorphic forms
• +3 more

Maryna Viazovska is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL), renowned for solving the sphere packing problem in dimensions 8 and 24. She holds a PhD from the Max Planck Institute for Mathematics and the University of Bonn (2013), with earlier degrees from Technical University Kaiserslautern (M.Sc., 2007) and Kyiv National Taras Shevchenko University (B.Sc., 2005). Her research focuses on sphere packing, optimal point configurations, Fourier analysis, automorphic forms, and number theory. Notable achievements include proving the E8 lattice's optimality in 8 dimensions and the Leech lattice in 24 dimensions, leveraging modular forms and interpolation techniques. Key awards include the Fields Medal (2022), Fermat Prize (2020), and Salem Prize (2016). She has held positions at Humboldt University of Berlin (BMS Dirichlet Postdoc), Institut des Hautes Études Scientifiques, and Princeton University. Her publications span top journals like Annals of Mathematics and address interdisciplinary topics such as superconductivity and combinatorial geometry. Viazovska’s work bridges pure mathematics with applications in coding theory and physics.

• Environmental Medicine
• Indoor Air Quality
• Air Purification
• +3 more

Renate Weisböck-Erdheim serves as a University Assistant at the Institute for Ecomedicine, Paracelsus Medical University. Holding both Mag. (Diplom-Magister equivalent to Master's) and MBA qualifications, her work bridges environmental science and public health through empirical research on built and natural environments. Her educational foundation includes: Mag. (Diplom-Magister) - Advanced Master's-level degree in Austria MBA - Specialized management training Research centers on quantifiable health impacts of environmental interventions, particularly air quality management in indoor spaces and therapeutic benefits of alpine/natural settings. Her methodology emphasizes controlled observational studies and randomized clinical trials measuring physiological and psychological outcomes, with current work focusing on non-thermal plasma air purification efficacy, classroom ventilation optimization, and comparative analysis of mountain versus forest therapies. Publication trends (2022-2025) reveal consistent focus on evidence-based environmental health solutions. Key contributions include establishing causal links between mechanical ventilation strategies and particulate matter reduction in educational settings, demonstrating infection rate reductions through advanced air purification, and quantifying mental health benefits from structured nature exposure. This work forms a cohesive framework connecting engineering solutions with public health outcomes. No scientific awards are documented in available sources. Grant leadership includes the HEALPS project (2018-2019) positioning the Alps as a global health destination and Trail for Health Nord (2015-2018) developing health tourism capacity. She actively organizes major conferences including the 2024 Healing Power of the Alps conference and 2016 Alpine Health Tourism Congress, facilitating knowledge exchange between researchers and industry stakeholders. She operates within the Institute for Ecomedicine's research ecosystem, collaborating with Hartl's team on multi-disciplinary projects that integrate environmental monitoring equipment, clinical assessments, and tourism infrastructure analysis across real-world settings from classrooms to mountain trails.

• Stochastic Processes
• Applied Mathematics
• Computational Mathematics
• +3 more

Erika Hausenblas holds the position of Chair of Applied Mathematics. Her research focuses on stochastic processes, computational mathematics, and their applications in fluid dynamics and mathematical biology. She actively participates in international conferences such as the World Congress in Probability and Statistics and the Symposium on Sparsity and Singular Structures. Her work spans theoretical developments in stochastic partial differential equations and practical applications in ecological modeling and financial mathematics. Research Interests: Stochastic Analysis, Numerical Methods for SDEs, Fluid Dynamics, and Mathematical Biology. Recent Activities: Invited talks at CRC 1283 and participation in workshops on aggregation-diffusion equations.

• Statistical Methods
• Machine Learning
• Materials Science
• +5 more

Matthias Neumann is an Assistant Professor at the Institute of Statistics, Graz University of Technology . He completed his PhD in 2020 at Ulm University under Prof. Volker Schmidt, earning the PhD prize of Ulm University . His research focuses on stochastic 3D modeling and statistical analysis of micro- and nanostructures for functional materials, including battery electrodes , fuel cells , and paper-based materials . He has received start-up funding from ProTrainU (2020-2022) and served as principal investigator in the POLiS Cluster of Excellence (2022-2023). Research Interests: His work integrates mathematical morphology , machine learning , and spatial statistics to develop methods for microstructure quantification , estimation of geometrical descriptors (e.g., tortuosity, constrictivity), and data-driven models linking morphology to effective physical properties . He utilizes random fields , point processes , and copulas for virtual microstructure generation and parameter estimation. Teaching: He lectures on Applied Statistics , Statistical Modeling , and Mathematical Statistics at Graz University of Technology, with prior teaching experience at Ulm University in Multivariate Stochastic Modeling , Point Processes , and Spatial Statistics . Scientific Achievements: PhD prize of Ulm University (2020) ProTrainU start-up funding (2020-2022) POLiS Cluster of Excellence grant (2022-2023) Publications: His 15 most recent articles (2023-2025) emphasize machine learning techniques for microstructure segmentation , stochastic 3D modeling of nanoporous materials , and data-driven quantification of transport-property relationships . Key topics include random forests , neural networks , and R-vine copulas applied to fuel cells , sodium-ion batteries , and polymer electrolytes .

Ekaterina FokinaView profile

Associate Professor

• Computable Structure Theory
• Computable Model Theory
• Equivalence Relations
• +8 more

Ekaterina Fokina is an associate professor at the Institute of Discrete Mathematics and Geometry, Vienna University of Technology. Her research focuses on computable model theory, equivalence relations, and algorithmic properties of structures. Projects: Stand-alone Project P27527, Elise Richter Project V206, Stand-alone Project P23989, Lise Meitner Project M1188. Collaborators: V. Harizanov, D. Turetsky, N. Bazhenov, L. San Mauro, P. Semukhin, S. Goncharov, J. Knight, R. Miller. Her work investigates categoricity spectra, bi-embeddability, and the complexity of equivalence relations. Key contributions include solving the long-open Covering Problem for Martin-Löf randomness and analyzing the computational complexity of the Finite Intersection Principle. She has published in journals like Annals of Pure and Applied Logic , Archiv für Mathematische Logik und Grundlagenforschung , and Journal of Symbolic Logic . Articles supported by FWF grants explore computable categoricity, equivalence relation complexity, and parameterized complexity theory. Her recent work includes bi-embeddability spectra, degree spectra, and intrinsic complexity bounds. Scientific Awards: Elise Richter Fellowship (FWF V206) Lise Meitner Fellowship (FWF M1188) She has contributed to understanding algorithmic randomness, effective versions of the Axiom of Choice, and hyperarithmetic isomorphism complexity.

• Experimental Economics
• Fairness and Moral Behavior
• Choice Architecture
• +3 more

Essi Kujansuu is a Researcher at the University of Innsbruck, with affiliations at the University of Turku and the Institute of Replication (I4R). She holds a PhD in Economics from the European University Institute. Her work focuses on experimental economics, exploring themes like fairness, trust, moral behavior, and choice architecture. Recent research emphasizes meta-science and Open Science, particularly computational reproducibility and robustness analysis of published studies. Her experimental designs often involve real-effort tasks and real-time interaction platforms like oTree. Key contributions include analyzing wage rigidity in labor markets, the psychological impacts of wage cuts, and the effectiveness of nudges under transparency. She collaborates internationally on projects ranging from field experiments in credence goods to assessing reproducibility in quantitative social science through human-AI teams. Current projects include investigating how transparency affects nudge deployment by choice architects and comparing human vs AI-assisted methods in research reproducibility. She frequently contributes to replication efforts of high-impact studies in development and health economics. Her technical expertise spans experimental platform development (e.g., Django Channels integration) and advanced statistical methods for reproducibility analysis. Future work aims to bridge behavioral economics with modern computational tools, enhancing both theoretical understanding and practical applications of economic decision-making models.

Elisa DavoliView profile

Professor

• Calculus of Variations
• Micromagnetics
• Solid-Solid Phase Transitions
• +4 more

Elisa Davoli is a Professor at TU Wien, affiliated with the Multiscale Calculus of Variations Research Group (E101-01-3). Her work focuses on calculus of variations, micromagnetics, and material science, with applications in phase transitions, nonlocal models, and stochastic homogenization. She collaborates extensively with researchers such as Irene Fonseca, Manuel Friedrich, and Ulisse Stefanelli. Her recent research includes studies on fractional Cahn-Hilliard systems, sharp-interface limits, and optimal control in nonlocal frameworks. She also investigates stochastic homogenization in micromagnetics and structural changes in nonlocal denoising models through bilevel learning. Key contributions include existence results in large-strain magnetoelasticity, two-scale convergence methods for composite materials, and the derivation of linearized fracture models under non-interpenetration constraints. Her work bridges mathematical analysis with applications in solid mechanics and image processing.

• Numerical Analysis
• Partial Differential Equations
• Finite Element Methods
• +3 more

Markus Faustmann is a Senior Scientist at the Institute for Analysis and Scientific Computing (E 101) within the Faculty of Mathematics and Geoinformation at TU Wien. His research focuses on numerical methods for partial differential equations, with particular emphasis on fractional differential operators, finite element methods (FEM), boundary element methods (BEM), and hierarchical matrices. He has held roles including Senior Lecturer (2016-2021) and currently serves on the management team of TUForMath since 2023. Education: PhD in Mathematics (Dr.techn.), TU Wien (2015) Dipl.-Ing. in Technical Mathematics, TU Wien (2009) Bachelor of Science in Technical Mathematics (B.Sc.), TU Wien (2008) Research Interests: His work addresses non-local operators, elliptic regularity theory, and efficient numerical techniques for fractional PDEs. He develops and analyzes methods like hp-FEM and matrix compression strategies to tackle fully populated matrices arising from non-local problems. Recent projects include FEM-BEM coupling for fractional diffusion and exponential convergence analysis of hp-FEM. Awards: TU Best Teacher Award 2022 TU Best Paper Award 2022 Teaching & Advising: Faustmann teaches courses such as Nonlocal Operators and Numerical Methods for PDEs . He has supervised numerous students in master's theses (e.g., Paul Dunhofer, Tobias Slowiak) and bachelor's projects (e.g., Lukas Sichert, Paul Lucan). His seminars cover topics like randomized algorithms and differential equations. Labs/Teams: Active in the TUForMath initiative and collaborates on projects involving adaptive FEM for fractional operators and H-matrix approximations.

Raimundo SaonaView profile

Research Fellow

• Game Theory
• Probability Theory
• Algorithmic Game Theory
• +3 more

Raimundo Saona is a Research Fellow in the Department of Mathematics at the London School of Economics and Political Science (LSE), where he joined in 2025. His work bridges theoretical mathematics with practical applications in computer science and decision theory. His research focuses on Game Theory, Probability Theory, Algorithmic Game Theory, Stochastic Analysis, Optimal Control, and Imprecise Probability Theory. He develops mathematical tools to provide new insights on situations involving uncertainty, working with both continuous and discrete models, proving theoretical existence theorems, coding efficient algorithms, and analyzing both dynamic online and static offline settings. His publication record shows a strong focus on stochastic games, Markov decision processes, and prophet inequalities. His recent work (2022-2024) has centered on ergodic unobservable MDPs, marginal values in stochastic games, and zero-sum random games on directed graphs, demonstrating his continued contribution to advancing theoretical frameworks in game theory and decision processes. His earlier work established foundational results in POMDPs and prophet inequalities.

Ariane CarranceView profile

Researcher

• Combinatorics
• Probability Theory
• Discrete Metric Spaces
• +5 more

Ariane Carrance is a postdoctoral researcher at the Department of Mathematics, Faculty of Mathematics, University of Vienna, where she works with Professor Nathanaël Berestycki. Her research program bridges combinatorics, probability theory, and theoretical physics with applications to quantum gravity. PhD in Mathematics, Institut Camille Jordan, supervised by Grégory Miermont and Fabien Vignes-Tourneret Postdoctoral position at Laboratoire de Mathématiques d'Orsay with Nicolas Curien and Jean-François Le Gall Hadamard lecturer at Centre de Mathématiques Appliquées de l'École polytechnique Dr. Carrance specializes in the combinatorial and probabilistic aspects of discrete metric spaces. Her work in dimension 2 focuses on specific families of maps, while in higher dimensions she investigates "colored trisps" and associated tensor models. She has made significant contributions to the understanding of random discrete structures and their continuum limits, with implications for quantum gravity theories. Her research combines deep theoretical insights with computational approaches, including development of mathematical software. Dr. Carrance's publication record demonstrates a consistent progression from foundational work on planar maps and triangulations toward more complex higher-dimensional structures. Her recent work shows increasing sophistication in handling the interplay between combinatorial structures and probabilistic phenomena, with particular attention to asymptotic behaviors and scaling limits. The mathematical tools she employs span from classical combinatorics to advanced probability theory and computational mathematics. Dr. Carrance has collaborated with leading researchers in probability theory including Nicolas Curien, Jean-François Le Gall, and Nathanaël Berestycki. She co-developed the SageMath package dynpuiseux for Puiseux series expansions, demonstrating her commitment to computational approaches in pure mathematics. Her research is supported through postdoctoral fellowships and academic positions at prestigious institutions across Europe. As a member of the probability research group at the University of Vienna, Dr. Carrance contributes to a vibrant mathematical community focused on stochastic processes, random geometry, and their applications. Her work connects with broader efforts to understand the mathematical foundations of quantum gravity through discrete approaches.

• Global Optimization
• Numerical Analysis
• Data Analysis
• +3 more

Waltraud Huyer is a faculty member at the Department of Mathematics, Faculty of Mathematics, University of Vienna. Her office is located in Room 04.120 at Oskar-Morgenstern-Platz 1, 1090 Wien, Austria. She actively teaches courses including Numerical Mathematics and Introduction to Mathematics for both undergraduate and secondary school teacher accreditation programs. Her research spans Global and Local Optimization , Numerical Analysis , Data Analysis , Protein Folding , and Population Dynamics with structured populations. She develops advanced optimization algorithms like SNOBFIT for noisy environments and MINQ8 for quadratic programming, while applying mathematical techniques to biological problems such as protein structure prediction and age-structured population modeling. Analysis of her 14 most recent publications (1994-2018) reveals three dominant research thrusts: (1) Algorithmic development in global optimization (7 papers), including multilevel coordinate search and exact penalty functions; (2) Mathematical biology applications (5 papers), particularly in protein folding and population dynamics; (3) Computational verification methods (2 papers) for linear systems and feasibility problems. Her work consistently bridges theoretical mathematics with practical computational implementations. Her scientific contributions include widely-used algorithms implemented in MATLAB, such as the MCS global optimizer and SNOBFIT for noisy optimization, available through the University of Vienna's software repository. Huyer supervises teaching activities for foundational mathematics courses, emphasizing practical computational skills using MATLAB for numerical analysis and regression problems. Her teaching materials include detailed exercise sets with structured assessment criteria requiring both theoretical understanding and programming implementation.