جست‌وجوی استاد و پژوهشگر

Christian Seisمشاهده پروفایل

استاد

• Applied analysis
• Partial Differential Equations (PDEs)
• Mathematical fluid dynamics
• +۵ مورد دیگر

Prof. Dr. Christian Seis is a Professor of Applied Mathematics at the University of Münster, affiliated with the Institute of Analysis and Numerics. He is an Investigator in Mathematics Münster and specializes in applied analysis, partial differential equations (PDEs), and mathematical fluid dynamics. His research focuses on fluid dynamics phenomena, including vortex dynamics, mixing processes, and free boundary problems, with applications to convection and nonlinear diffusions. Education & Career: PhD from University of Leipzig (2011) Postdoctoral Fellow at University of Toronto (2011–2014) Lecturer (Akademischer Rat) at University of Bonn (2014–2017) Current position since 2017 at University of Münster Research Interests: Nonlinear PDEs, particularly fluid dynamics and transport equations Vortex dynamics, mixing in fluids, and boundary layer analysis Asymptotic behavior of solutions to Navier-Stokes and Euler equations Nonlinear diffusions, including thin film and porous medium equations Stability estimates and numerical schemes for advection-diffusion equations Recent Projects: Mathematical analysis of bubble rings in ideal fluids Optimal stability estimates for advection-diffusion equations Crossover of coarsening rates in demixing viscous liquids Analysis of the vanishing viscosity limit in 2D flows Grants & Collaborations: DFG Cluster of Excellence 'Mathematics Münster' (EXC 2044) Individual DFG grants for projects on transport equations and invariant manifolds Co-organizer of workshops on fluid dynamics and geometric PDEs Labs/Teams: Leads the research group on applied analysis and PDEs at the University of Münster, focusing on rigorous mathematical analysis of fluid dynamics and diffusion processes.

Angela Stevensمشاهده پروفایل

استاد

• Applied Mathematics
• Nonlinear Partial Differential Equations
• Mathematical Biology
• +۳ مورد دیگر

Prof. Dr. Angela Stevens is a Full Professor in Applied Mathematics at the University of Münster, Germany, leading the Applied Analysis group within the Institute for Analysis and Numerics. She is an Investigator in the Cluster of Excellence Mathematics Münster and holds an honorary position at the University of Leipzig. Her research focuses on applied analysis, nonlinear partial differential equations, mathematical modeling in biology, and interacting particle systems. Notable contributions include work on chemotaxis, cell motility, and regeneration processes in organisms like planarians. Education & Awards : Stevens earned her PhD in Mathematics from the University of Heidelberg (1992) and won the SIAM Student Paper Competition in 1992. She has held visiting positions at institutions such as the University of Minnesota, Hokkaido University, and Stanford University. Research Interests : Her work bridges theoretical analysis with biological applications, emphasizing mathematical models for cell behavior, pattern formation, and epidemiology. Key areas include taxis-driven dynamics, free boundary problems, and multi-scale processes in biological systems. Awards & Recognition : In addition to the SIAM award, her leadership in interdisciplinary research has been recognized through visiting professorships and contributions to collaborative networks like Cells in Motion and CeNoS. Grants & Collaborations : She leads research projects in Mathematics Münster and collaborates internationally on topics like PDEs and stochastic systems. Her work on the mathematical modeling of planarian regeneration highlights her innovative approach to biological problems. Labs & Teams : Stevens oversees the Applied Analysis research group, which actively contributes to the Mathematics Münster cluster and hosts events like the Workshop on Cell Dynamics and Mathematical Modeling (2023).

• Probability Theory
• Stochastic Processes
• Lévy Processes
• +۷ مورد دیگر

Víctor Rivero is a mathematician affiliated with the Department of Probability and Statistics at the Center for Research in Mathematics (CIMAT) in Guanajuato, Mexico. He specializes in stochastic processes, particularly Lévy processes, self-similar Markov processes, fluctuation theory, and excursion theory. His research explores applications in branching processes, local times, and regenerative sets. He has held roles including Director of CIMAT (2017–2022), Editor of ALEA - Revista Latinoamericana de Probabilidad y Estadística (2025–present), and member of the Scientific Committee for the 11th International Conference on Lévy Processes (2024–2025). He has collaborated internationally, including a sabbatical at the University of Warwick’s Probability Group (2023–2024). His research trends focus on advancing the theory of self-similar Markov processes, Lévy processes in cones, and applications of excursion theory. He has advised multiple PhD and master’s students, including notable advisees such as Harry Sapranidis Mantelos and Mehar Motala. He is part of collaborative platforms like the CIMAT-UNAM-Warwick-Bath research network and contributes to teaching through lecture notes on Lévy processes and stochastic models. His work bridges foundational probability theory with applied stochastic modeling.

• Partial Differential Equations
• Interface Evolution Problems
• Fluid Mechanics
• +۲ مورد دیگر

Sebastian Hensel is a Researcher at the Hausdorff Center for Mathematics (HCM) at the University of Bonn since September 2021, under the mentorship of Prof. Tim Laux. He holds a PhD in Mathematics from the Institute of Science and Technology Austria (IST Austria), where he studied under Prof. Julian Fischer. His research focuses on partial differential equations, particularly interface evolution problems, fluid mechanics, stochastic homogenization, and stochastic PDEs. He has contributed to topics like mean curvature flow, free boundary problems, and weak-strong uniqueness principles. Education includes a PhD (2021, IST Austria), Master of Science in Mathematics (2017, Humboldt-Universität zu Berlin), and Bachelor degrees in Mathematics (2015, Freie Universität Berlin) and Business Administration (2013, Freie Universität Berlin). His work explores geometric PDEs, including multiphase systems, contact angle dynamics, and stochastic influences. Key contributions include stability analyses of evolving interfaces and convergence studies of phase-field models. His articles often bridge analytical rigor and applied mathematics, addressing challenges in nonlinear dynamics and calculus of variations. He has presented research at international conferences such as FBP 2020, SIAM MS20, and Equadiff 2019. His academic activities include seminars at institutions like TU Chemnitz, University of Regensburg, and Max-Planck Institute for Mathematics in the Sciences, Leipzig.

• Theoretical Physics
• Mathematical Physics
• General Relativity
• +۴ مورد دیگر

Eduardo Jesús Sánchez Villaseñor is an Associate Professor in the Department of Mathematics at Universidad Carlos III de Madrid since 2009. He holds a PhD in Theoretical Physics from Universidad Complutense de Madrid (2001). His research focuses on mathematical and theoretical physics, with emphasis on classical and quantum aspects of general relativity, field theory, statistical mechanics, and combinatorics. He has contributed extensively to topics like gravitational theories with boundaries, loop quantum gravity formulations, and geometric approaches to spacetime symmetries. Education: PhD in Theoretical Physics, Universidad Complutense de Madrid (2001) Bachelor's degree in Computer Science with courses in Calculus and Discrete Mathematics (UC3M) Research Interests: His work bridges theoretical physics and mathematics, addressing foundational questions in general relativity (e.g., Palatini formalism, nonmetricity, torsion), quantum gravity (loop quantization, black hole entropy), and combinatorial structures (permutations, recurrence relations). Recent efforts explore edge observables in gauge theories and geometric diffusion phenomena. Publications: His 15 most recent articles (2021–2025) reflect a focus on gravitational theories with boundaries, geometric constraint formulations, and topological field theories. Key themes include equivalence of phase space approaches, self-dual gravity formulations, and Dirac’s algorithm in boundary contexts. Teaching: He teaches courses including Perturbation Methods (Master’s level), Calculus , and Discrete Mathematics at UC3M. His pedagogical materials emphasize applications of advanced mathematical techniques to physics problems. Labs/Teams: Collaborates actively with researchers like F. Barbero, J. Margalef-Bentabol, and V. Varo, focusing on gravitational and mathematical physics projects. His work is supported by institutional research portals at UC3M.

Haye Hinrichsenمشاهده پروفایل

استاد

• Quantum Information Theory
• Exactly Solvable Systems
• Tensor Networks
• +۴ مورد دیگر

Prof. Haye Hinrichsen holds a C3 professorship at the University of Würzburg within the Chair of Theoretical Physics III . His academic journey includes roles as Acting Professor at the University of Wuppertal (2001), Senior Assistant at Duisburg-Essen (2000), and postdoctoral research at institutions like the Weizmann Institute of Science (1995–1997). He earned his PhD in 1993 from the University of Bonn under Prof. V. Rittenberg, focusing on quantum groups. His research interests span quantum information theory , exactly solvable systems , statistical physics far from equilibrium , reaction-diffusion processes , and non-equilibrium phase transitions . Notable achievements include the 2007 Award for Good Teaching and contributions to understanding entropy-based tuning systems in music. His recent work explores topics like causal set propagators in anti-de Sitter spacetime, eigenmodes on hyperbolic lattices, and renormalization techniques in quantum field theories. He has also applied physics principles to music acoustics, developing adaptive tuning schemes using entropy maximization. Key Research Themes: Quantum gravity, non-equilibrium dynamics, topological complexity, and interdisciplinary applications in music. Teaching: Courses include Theoretical Physics I, Computational Physics, and General Relativity. Lab/Affiliation: Chair of Theoretical Physics III at Hubland South, Building M1.

Perc Matjažمشاهده پروفایل

استاد

• Phase transitions
• Complex networks
• Stochastic processes
• +۷ مورد دیگر

Matjaž Perc is a Full Professor of Physics at the University of Maribor and holds leadership roles including Vice Dean of Natural Sciences at the European Academy of Sciences and Arts. His research focuses on complex systems, nonlinear dynamics, and socio-physical phenomena. He has been recognized with prestigious awards such as the Young Scientist Award for Socio- and Econophysics (2015) and the Zois Award (2018), Slovenia's highest national research honor. Perc is also a Fellow of the American Physical Society and among the world's top 1% most cited physicists. Research Interests : Phase transitions in social systems, evolutionary game theory, complex networks, stochastic processes, and self-organization mechanisms. Awards : Extensive list includes recognition for refereeing excellence, societal memberships (APS, EPS), and national accolades. Publications : Over 300 articles in top journals like Physical Review E , Chaos , and Scientific Reports , focusing on interdisciplinary applications of physics to social, biomedical, and environmental challenges. His work bridges physics, computer science, and social sciences, addressing global issues through mathematical modeling and network analysis.

Valerio Lucariniمشاهده پروفایل

استاد

• Climate variability
• Thermodynamics of the climate system
• Tipping points and multistability
• +۶ مورد دیگر

Valerio Lucarini is a Professor of Applied Mathematics at the School of Computing and Mathematical Sciences, University of Leicester. His research spans Statistical Mechanics, Climate Dynamics, Dynamical Systems Theory, and Meteorology. He has held leadership roles such as Director of the Centre Mathematics of Planet Earth at the University of Reading (2016-2024) and has been a Visiting Professor at the University of Hamburg. His scientific contributions focus on the thermodynamics of climate systems, tipping points, stochastic processes, and extreme event predictability. Recent work explores Koopman operator theory for response analysis, multiscale dynamical indices, and saddle avoidance in noise-induced transitions. Scientific Awards : 2024 IUGG Keilis-Borok Medal 2022 SIAM Mathematics of Planet Earth Prize 2022 Academia Europaea membership 2021 AGU E. N. Lorenz Lecture 2020 EGU L. F. Richardson Medal His publications demonstrate a multidisciplinary approach combining climate science, statistical physics, and mathematical modeling to address critical questions in climate change, ocean circulation stability, and nonlinear system response to perturbations.

Jaya Bishwalمشاهده پروفایل

دانشیار

• Probability
• Stochastic Processes
• Statistical Inference
• +۲ مورد دیگر

Dr. Jaya Bishwal is an Associate Professor in the Mathematics & Statistics Department at the University of North Carolina at Charlotte. Her research expertise centers on Probability and Stochastic Processes, with applications in mathematical finance and statistical inference. Her extensive publication record demonstrates deep specialization in fractional processes, stochastic differential equations, and statistical estimation methods. Recent work focuses on advanced econometric applications including Levy process modeling, fractional Ornstein-Uhlenbeck systems, and volatility estimation in financial mathematics. Methodological innovations include developments in quasi-likelihood estimation, Kolmogorov distance analysis for estimators, bootstrap methods for financial derivatives, and asymptotic theory for nonergodic systems. Her research bridges theoretical probability and practical applications in quantitative finance.

Ummugul Bulutمشاهده پروفایل

استادیار

• Stochastic Differential Equations
• Mathematical Biology
• Epidemiological Modeling
• +۴ مورد دیگر

Dr. Ummugul Bulut is an Assistant Professor of Mathematics at the University of the Incarnate Word (UIW), serving since 2022. Her academic journey includes a Ph.D. in Mathematics from Texas Tech University (2012), followed by postdoctoral research at Grand Valley State University and teaching roles at Texas A&M University-San Antonio. Education: Ph.D. Mathematics, Texas Tech University, 2012 M.S. Mathematics, Texas Tech University, 2009 B.S. Mathematics, Fatih University (Istanbul, Turkey), 2006 Research Interests: Dr. Bulut specializes in stochastic differential equations and mathematical biology, focusing on computational methods for applied problems. Her work includes epidemic modeling to predict disease spread, climate change impacts on wildlife diseases, and cybersecurity curriculum development. She actively collaborates on projects such as the NSA-funded initiative to enhance cybersecurity education and the Rand Corporation’s smart city risk triage analysis. Awards and Recognition: Her pharmacokinetics modeling project earned the Best Poster Award at the 2015 SIAM Great Lakes Section meeting. Community Engagement: Dr. Bulut promotes STEM education through women-in-science initiatives and supports immigrant/refugee families. She is also involved in interfaith activities and mentors Girl Scouts.

Torben Knudsenمشاهده پروفایل

دانشیار

• Wind Turbine Engineering
• Process Control
• Control Systems
• +۶ مورد دیگر

Torben Knudsen is an Associate Professor at the Department of Electronic Systems, Aalborg University, Denmark. He is affiliated with the Automation & Control Learning and Decisions Lab and holds positions in The Technical Faculty of IT and Design. His research focuses on control systems, wind turbine engineering, stochastic processes, and biomedical applications such as diabetes modeling. Education: Advanced degrees in engineering, though specific details are not explicitly listed. Research Interests: Wind turbine dynamics, offshore wind farm control, stochastic modeling of biomedical systems, fault detection, and optimization techniques. His work integrates control theory with renewable energy systems, particularly addressing challenges in wind turbine aeroelasticity and floating offshore wind farms. Recent projects include the development of health-aware simulation platforms (FOWLTY) and insulin dose optimization algorithms for type 2 diabetes. Key Projects: ICONIC (2023-2027) : Focuses on intelligent control of industrial processes. PRESTIGE (2020-2023) : Explored predictive manufacturing and quality control. Modelling and Control of Type 2 Diabetes (2019-2024) : Developed stochastic models for glucose-insulin dynamics. Knudsen has received the Best Paper Award (2015) for contributions to predictive manufacturing. His research also extends to pandemic modeling, including work on SARS-CoV-2 variant outbreaks and hospital preparedness during epidemics. Advising & Grants: Active in interdisciplinary collaborations, including funding from EU projects like Aeolus and OFFWIND. He contributes to grants focusing on wind farm control, diabetes modeling, and stochastic systems. Labs & Teams: Leads the Automation & Control Learning and Decisions Lab, collaborating with international teams on energy systems and biomedical engineering challenges.

Catherine Forbesمشاهده پروفایل

استاد

• Bayesian Statistics
• Econometrics
• Financial Econometrics
• +۵ مورد دیگر

Catherine Forbes is a Professor and Deputy Head of the Department of Econometrics and Business Statistics (EBS) at Monash University, where she also serves as Director of Education. She holds an adjunct professorship at Sunway University, Malaysia, and is an Associate Editor of Applied Stochastic Models in Business and Industry . Her research focuses on Bayesian statistics, econometrics, and computational methods for analyzing financial risks and complex time series. She has led multiple research grants, including ARC and NHMRC-funded projects, and contributed to policy reforms, such as the Victorian Children, Youth and Families Act 2005. Her research interests span Bayesian modeling, financial econometrics, robust statistical methods, and nonparametric techniques. She has supervised 20 PhD students and 20 Honours projects, emphasizing mentorship in statistical methodologies. Notable collaborations include work with the Centre of Excellence in Child and Family Welfare on predictive analytics for youth outcomes. Dr. Forbes has led over 20 research projects, including grants focused on Bayesian empirical likelihood, financial risk dynamics, and health care analysis. Her recent work includes advancements in cross-validation methods and familial inference techniques, with applications in housing affordability and mental health linkages.

Christian O Ewaldمشاهده پروفایل

استاد

• Quantitative Finance
• Risk Management
• Commodities
• +۳ مورد دیگر

Christian O Ewald is a Professor in Financial Economics at the University of Glasgow. He holds additional Research Professorships at the University of Inland Norway and Umeå University in Sweden. His research focuses on Quantitative Finance, Risk Management, Commodities, Derivatives, and Natural Resources. Ewald earned his MSc from the University of Mainz, PhD from the University of Heidelberg, and a Habilitation from the University of Kaiserslautern, all in Germany. Prior roles include positions at the University of Sydney, Nottingham University Business School (China), University College Cork, University of St. Andrews, and the University of Leeds. He has supervised over 20 PhD students, with notable alumni now in academia and finance sectors globally. Ewald's research explores commodity markets (e.g., salmon futures, crude oil), stochastic volatility models, real options, and risk management strategies. His work often integrates advanced mathematical techniques like Malliavin calculus and stochastic optimal control. Notable grants include leadership in the 'Aquarisk' project (NOK 8 million) and a Kempe Foundation grant on longevity risk. Publications span journals such as *Quantitative Finance*, *Journal of Economic Dynamics and Control*, and *Energy Economics*. His contributions address practical challenges like hedging strategies, asset pricing under uncertainty, and environmental risk assessment.

Tiziana Di Matteoمشاهده پروفایل

استاد

• Econophysics
• Complex Systems
• Complex Networks
• +۷ مورد دیگر

Tiziana Di Matteo is a Professor of Econophysics in the Department of Mathematics at King's College London, part of the Faculty of Natural, Mathematical & Engineering Sciences. She is also External Faculty at the Complexity Science Hub and affiliated with the UCL Centre for Blockchain Technologies, the Complex System Laboratory, the Complex Systems Society, and the Museo Storico della Fisica e Centro Studi e Ricerche “E. Fermi”. Her research focuses on econophysics, complex systems, complex networks, and data science , with applications in financial modeling, systemic risk, and multiscaling analysis. She integrates methods from statistical physics and network science to analyze financial markets and economic interactions. The most recent publications reveal a strong trend in financial network modeling, multiscaling volatility, tensor-based learning for multidimensional data, and early warning systems using scaling properties . Her work bridges econophysics and traditional financial economics, emphasizing empirical validation and interdisciplinary approaches. Scientific Leadership and Editorial Roles: Editor-in-Chief, Journal of Advances in Mathematical Physics Main Editor, Physica A Editor, European Physical Journal B Editor, Artificial Intelligence in Finance Former Editor-in-Chief, Journal of Network Theory in Finance Guest Editor for multiple special issues Tiziana is the co-founder of the Econophysics Network and has served as a consultant for the Financial Services Authority, hedge funds, and financial companies. She has authored over 100 papers and delivered keynote talks globally. She supervises PhD students and leads collaborative research in complex financial systems. She is actively involved in interdisciplinary research collaborations with institutions like the Francis Crick Institute and industrial partners including EDF Research and Unilever.

Yoshiharu Maenoمشاهده پروفایل

استاد

• Data Science and Engineering
• Complex Systems Theory
• Stochastic Process Theory
• +۷ مورد دیگر

Dr. Yoshiharu Maeno is a Professor at the School of Interdisciplinary Mathematical Sciences, Meiji University, where he conducts interdisciplinary research at the intersection of mathematics, data science, and social systems. His work applies advanced mathematical frameworks to real-world complex phenomena in economics, finance, epidemiology, and social networks. Position: Professor Institution: Meiji University School: School of Interdisciplinary Mathematical Sciences Research Interests Dr. Maeno's research focuses on data science and engineering, complex systems theory, and stochastic process theory applied to economics and social sciences. He specializes in modeling reaction-diffusion processes to understand the dynamics of infectious disease spread, financial crises, and misinformation dissemination on social media. His work bridges theoretical mathematics with practical applications in societal challenges. Publication Trends His recent scholarly output demonstrates a consistent focus on applying reaction-diffusion and stochastic models to complex social and economic systems. The publications span interdisciplinary domains including econophysics, computational social science, and mathematical epidemiology, showing a strong trend toward data-driven modeling of real-world dynamic processes. Scientific Awards No specific awards mentioned in the provided text. Advising and Grants While specific students or grant details are not listed, Dr. Maeno's active research program suggests involvement in mentoring graduate students and securing research funding. His participation in events like the Econophysics Colloquium and CSH Workshop indicates collaboration within the global complexity science community. Labs and Teams Dr. Maeno is associated with research initiatives focused on complex systems and data science, likely involving collaborative teams working on interdisciplinary projects. His involvement in workshops and colloquia suggests membership in international research networks studying complexity in economic and social systems.