جست‌وجوی استاد و پژوهشگر

Karsten Kruseمشاهده پروفایل

مدرس

• Functional Analysis
• Operator Semigroups
• Abstract Cauchy Problems
• +۱۱ مورد دیگر

Karsten Kruse is a Lecturer in the Department of Applied Mathematics at the University of Twente, affiliated with the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) and the Mathematical Systems Theory (MAST) group. Previously, he was a postdoctoral researcher and teaching assistant at Hamburg University of Technology and held an adjunct lecturer position at Hamburg University of Applied Sciences. PhD in Mathematics, University of Oldenburg (2014) Diploma in Mathematics, University of Oldenburg (2010) German Abitur, Graf-Anton-Günther-Schule (1997) His research centers on Functional Analysis, with focus on operator semigroups, abstract Cauchy problems, locally convex spaces, and vector-valued functions. He also investigates hyperfunctions, the \(\overline{\partial}\)-operator, and Laplace transforms. Complementing his theoretical work, Kruse is deeply engaged in e-learning and e-assessment, particularly through his innovative Surviving Math project, which uses gamification and storytelling to enhance problem-solving skills in engineering students. His teaching spans linear algebra, calculus, analysis, and topology across multiple institutions. His recent publications (2022–2025) consistently explore advanced topics in functional analysis, especially bi-continuous semigroups, preduals, and vector-valued function spaces, demonstrating a cohesive and evolving research program. Several papers involve interdisciplinary applications in queueing networks and robotic logistics. He frequently collaborates with mathematicians such as Felix L. Schwenninger and Christian Seifert. Scientific Awards Award for an outstanding Diploma thesis, University of Oldenburg Award for the best tutorial (Faculty V), University of Oldenburg (2012–2013 and 2013) 2nd place, MINTchallenge by Stifterverband Kruse has supervised multiple bachelor’s and master’s theses and coordinated international research workshops such as ISEM and DETN. He has been involved in several research projects, including those on bi-continuous semigroups and robotic mobile fulfilment systems, supported by institutions like the Simons Foundation. His teaching innovation project Surviving Math has been recognized and further developed at the University of Twente. He is actively involved in academic service, including organizing conference sessions such as at IWOTA 2025, and contributes to the mathematical community through arXiv, ORCID, and zbMath. He maintains a strong publication record and is engaged in both theoretical and applied mathematical research.

Giorgio Bacciمشاهده پروفایل

دانشیار

• Behavioural Metrics
• Model Synthesis and Automata Learning
• Analysis and Verification of Cyber-Physical Systems
• +۳ مورد دیگر

Giorgio Bacci is an Associate Professor at the Department of Computer Science , Aalborg University , Denmark. He is a member of the Distributed, Embedded, and Intelligent Systems (DEIS) research group led by Prof. Kim G. Larsen. He earned his Ph.D. in Computer Science from the University of Udine (2013) under Prof. Marino Miculan, following M.Sc. and B.Sc. degrees in Computer Science from the same university (2008 and 2005, both 110/110 cum laude ). Research Interests include: Behavioural Metrics : Quantitative methods for system equivalence and approximation. Model Synthesis and Automata Learning : Automated construction of models for probabilistic/stochastic systems. Analysis of Cyber-Physical Systems : Formal verification techniques for real-time and hybrid systems. Process Algebras : Nondeterministic, probabilistic, and stochastic process calculi. Semantics of Programming Languages : Formal models for probabilistic and concurrent computation. Scientific Service includes roles as PC member for LICS 2025 , ICALP 2025 , and co-chair for EXPRESS/SOS 2025 and GandALF 2025 . He has contributed to 35 publications in areas like probabilistic automata , Markov processes , and bigraphical models , with a focus on computational complexity and behavioral distances . Awards include: Teacher of the Year 2022/2023 (Department of Computer Science, Aalborg University) Best Paper Award at CALCO 2021 .

Joshua A. Grochowمشاهده پروفایل

دانشیار

• Theoretical Computer Science
• Computational Complexity
• Algebraic Complexity
• +۱۶ مورد دیگر

Joshua A. Grochow is an Associate Professor in the Department of Computer Science and, by courtesy, in the Department of Mathematics at the University of Colorado at Boulder. He is a member of the CS Theory Group and the Complex Systems Group. Previously, he was an Omidyar Fellow at the Santa Fe Institute and a postdoctoral researcher at the University of Toronto. He completed his Ph.D. in Computer Science at the University of Chicago under Lance Fortnow and Ketan Mulmuley. His research bridges theoretical computer science and mathematics, focusing on algebraic complexity, group and tensor isomorphism, proof systems, and the theory of complex systems. His work explores deep connections between algebra, computation, and complexity, with applications in quantum information, ecology, and thermodynamics. He has developed new frameworks for matrix multiplication using infinite groups and advanced the theory of higher-order interactions in complex networks. His recent publications span top venues such as ITCS, CCC, FCT, and SIAM Journal on Computing, with notable results on tensor isomorphism completeness, parallel group isomorphism algorithms, and algebraic proof complexity. He has mentored several Ph.D. students to completion, including Michael Levet, Maya Ornstein, and Tzu-Chi Yen. Best Paper Award at FCT 2023 Outstanding Faculty Mentor Award, CU Boulder (2021–2022) Dean’s Faculty Fellowship (2021) He actively collaborates across disciplines and is involved in educational innovation, including standards-based grading in large algorithms courses. His recent work emphasizes the role of symmetry, structure, and algebra in understanding computational complexity and emergent phenomena.

• Computational Mechanics
• Numerical Methods (Meshfree/XFEM/Isogeometric)
• Mixed Variational Methods
• +۳ مورد دیگر

Jack HALE is a Research Scientist at the University of Luxembourg's Faculty of Science, Technology and Medicine (FSTM), Department of Engineering. He joined Prof. Stéphane Bordas' team in 2013, focusing on computational mechanics and numerical methods. His work integrates advanced techniques like meshfree methods, XFEM, and isogeometric analysis to address challenges in solid mechanics and high-performance computing. Education : PhD in Aeronautics, Imperial College London (2009-2013), supervised by Dr. Pedro M. Baiz Villafranca. MEng in Engineering, University of Bristol (2004-2008). Research exchange at Rice University (2006-2007) on cross-flow filtration processes. Research Interests : Implicit boundary methods for medical image-based simulations. Development of scalable meshfree/XFEM/isogeometric analysis frameworks. Mixed variational methods to resolve locking phenomena in solid mechanics. High-performance computing for distributed parallel systems. Publications & Software : His 50+ publications emphasize open-access research via ORBilu, with a focus on FEniCSx-based tools (e.g., DOLFINx, FEniCS-shells). Recent work addresses Bayesian model selection, melt instability identification, and SAR data assimilation in aquifer modeling. Collaborations : Open to academic/industrial partnerships in computational mechanics, material science, and biomedical engineering.

Matthias Hieberمشاهده پروفایل

استاد

• Partial Differential Equations
• Fluid Dynamics
• Evolution Equations
• +۳ مورد دیگر

Prof. Dr. Matthias Hieber is a Professor of Applied Analysis at the Department of Mathematics, Technical University of Darmstadt, and serves as Vice Director at the Mathematical Research Institute of Oberwolfach (MFO). His primary research focuses on partial differential equations, fluid dynamics, evolution equations, and harmonic analysis, with significant contributions to geophysical fluid models and liquid crystal theory. Hieber's research centers on the mathematical analysis of nonlinear PDEs arising in fluid mechanics, particularly the primitive equations for geophysical flows, Ericksen-Leslie equations for liquid crystals, and stochastic fluid models. His work establishes fundamental properties including well-posedness, regularity, and long-time behavior in diverse functional settings such as $L^p$ spaces and spaces of bounded functions. Key innovations include analyses of turbulent pressure effects, compressible liquid crystal dynamics, and hydrostatic Stokes operators. Recent publications reveal a concentrated focus on geophysical fluid dynamics and liquid crystal models, with increasing emphasis on stochastic formulations and non-isothermal effects. His work consistently bridges abstract harmonic analysis with concrete physical applications, demonstrating exceptional technical mastery in maximal regularity theory and operator calculus. Hieber's scientific recognition includes: Jean-Morlet Chair at CIRM, 2022 He leads the DFG Research Group FOR 5528 on Mathematical Investigations of Geophysical Fluid Models and has supervised Humboldt Fellows like Dr. Arnab Roy on fluid-structure interaction. His projects include the Geophysical Flows retreat in Manigod, France (2025), and the Leipzig Summer School (2024). At TU Darmstadt, Hieber heads the Applied Analysis research group, which organizes international workshops including the Oberwolfach conference on Mathematical Advances in Geophysical Fluid Dynamics (2022) and the CIRM conference on Nonlinear PDEs in Fluid Dynamics (2022).

Gautam Iyerمشاهده پروفایل

استاد

• Partial Differential Equations
• Probability
• Fluid Mechanics
• +۴ مورد دیگر

Gautam Iyer is a Professor in the Department of Mathematical Sciences at Carnegie Mellon University. His research intersects partial differential equations and probability theory , with applications to fluid mechanics, mixing phenomena, and mathematical finance. Current research focuses on mixing-diffusion interactions , high-dimensional sampling , and anomalous diffusion in various flow models. He has worked on diverse topics including Bose-Einstein condensation , Q-tensor models for liquid crystals , and stochastic-Lagrangian formulations of Navier-Stokes equations. His recent publications (2023-2025) analyze: Dissipation enhancement in cellular flows and advective systems Residual diffusivity in Bernoulli map models Enhanced mixing in Langevin dynamics and nonlinear PDEs Anomalous diffusion in comb-like structures and random flows Major awards include: NSF CAREER Award (2013-18) Alfred P. Sloan Research Fellowship (2013-15) Simons Fellowship (2016-17) NSF RTG Grant (2024-29) and multiple collaborative NSF grants He has advised students in topics ranging from heat transfer dynamics to financial stochastic calculus , with their work often appearing in journals like SIAM Journal on Mathematical Analysis and Nonlinearity . His teaching spans advanced mathematics courses including Stochastic Calculus , Partial Differential Equations , and Markov Chains .