جستجوی استاد راهنمای دانشگاهی

Guenter Landsmann is a Researcher at the Research Institute for Symbolic Computation (RISC) of Johannes Kepler University in Linz, Austria. His primary research focuses on Algebraic Geometry and Symbolic Computation, with significant contributions to Gröbner bases, polynomial functions, and differential algebra. His work bridges theoretical mathematics and computational methods, addressing challenges in algebraic structures, geometric modeling, and topological properties. His research interests include Gröbner Reduction techniques, parametrization of algebraic varieties and canal surfaces, and the application of symbolic computation to problems in differential equations and topology. Notable contributions include studies on polynomial functions over GL(2,R), implicitization of algebraic varieties, and the development of algorithms for dimension computation in filtered free modules. Publications span ISSAC conferences, technical reports, and journals like Mathematical and Computer Modelling of Dynamical Systems. His work demonstrates a sustained focus on advancing computational tools for algebraic geometry and their applications in geometric modeling and abstract algebra. While no scientific awards are explicitly listed, his extensive publication record reflects a dedicated academic career in symbolic computation and related fields. His affiliation with RISC positions him at the forefront of interdisciplinary research combining mathematics and computer science.

• Algebraic Geometry
• Symbolic Computation
• Differential Algebra
• +۵ مورد دیگر

Liana Khazaliya is a PreDoc Researcher in the Department of Algorithms and Complexity at Vienna University of Technology , specializing in parameterized complexity and graph theory. Her work intersects computational complexity, graph drawing, and structural decomposition techniques. Research Focus: Double-exponential lower bounds for NP problems, crossing number analysis, planar graph extensions, and metric dimension parameterizations Key Collaborations: Works with teams in computational geometry, graph drawing, and algorithmic research Her recent publications analyze algorithmic hardness through treewidth and vertex cover parameterizations, contributing to the understanding of complexity thresholds in graph problems. She actively participates in international conferences like SoCG, GD, and IPEC, advancing fixed-parameter tractability frameworks.

• Parameterized Complexity
• Graph Theory
• Computational Complexity
• +۳ مورد دیگر

Petter E. Bjørstad is a Professor of Computer Science and Mathematics at the University of Bergen, Norway, where he has served as Head of the Department of Informatics since 2010. Previously, he was Director of the Bergen Center for Computational Science (2000-2010) and Professor in both the Department of Mathematics (2006-2010) and Department of Informatics (1985-2005). He also held a position as Professor of Mathematics at the University of Minnesota during 1996-1997 on unpaid leave from Bergen. Dr. Bjørstad earned his PhD in Computer Science from Stanford University in 1980, following which he completed a postdoctoral fellowship at the Courant Institute of Mathematical Sciences at New York University. Before entering academia, he worked as a Principal Engineer at Det Norske Veritas from 1981-1985. Dr. Bjørstad's research focuses on numerical analysis and high-performance computing, with particular expertise in domain decomposition methods, parallel algorithms for elliptic partial differential equations, and scientific computing. His work bridges theoretical mathematics with practical computational challenges, especially in industrial applications. He has led significant research projects including 'Multiscale Domain Decomposition: Algorithms and Analysis' (2010-2014), funded by the Research Council of Norway and the University of Bergen. His publication record demonstrates consistent contributions to the field of numerical methods and parallel computing over several decades. The research trends show a strong focus on developing efficient algorithms for solving partial differential equations through domain decomposition techniques, with applications spanning structural analysis, reservoir simulation, semiconductor device modeling, and other industrial contexts. His work increasingly emphasizes practical implementation on modern parallel architectures including SIMD and MIMD systems. Large number of research grants from Norway and the European Union Dr. Bjørstad has been actively involved in mentoring students and collaborating with industry through projects like the Europort effort, where industrial codes were ported to parallel computing platforms. His laboratory for parallel computing (Parallab) has been instrumental in advancing practical applications of high-performance computing since its establishment in 1985 with Europe's first 64-processor Intel hypercube. The lab has evolved to include multiple MIMD machines including an Intel Paragon, Parsytec GC/Power-Plus, and DEC α-cluster. As Head of the Department of Informatics, Dr. Bjørstad leads one of Norway's premier computing research units with expertise spanning theoretical computer science, numerical methods, and practical applications in various scientific domains. His leadership has helped establish Bergen as a significant center for computational science in Europe.

• Numerical analysis
• Domain decomposition
• Elliptic PDE
• +۴ مورد دیگر

Hermann Schichl is an Associate Professor at the University of Vienna , affiliated with the Faculty of Mathematics and Department of Mathematics. His work spans mathematical modeling, global optimization, and numerical analysis.

• Global Optimization
• Interval Arithmetic
• Mathematical Modeling
• +۵ مورد دیگر

Christian Pötzsche is a Professor at the Department of Mathematics, Alpen-Adria Universität Klagenfurt, Austria. His research focuses on nonautonomous dynamical systems , difference equations , stability theory , and nonlinear analysis , with applications in theoretical ecology and numerical discretization. He has held academic positions at TU Graz, TU München, and Nicolaus Copernicus University Torun, and served on editorial boards for journals like Discrete and Continuous Dynamical Systems (Series B) and Journal of Difference Equations and Applications . Research Interests: Nonautonomous hyperbolicity, bifurcation theory, invariant manifold approximation, integrodifference equations in population dynamics, and analytical discretization methods. Key Contributions: Developed Taylor approximation techniques for invariant fiber bundles, unified exponential stability criteria for time scales, and advanced nonautonomous bifurcation patterns (e.g., shovel-bifurcation). Scientific Awards: Recognized with the 'Best paper on difference equations in 2009' for work on robustness of hyperbolic solutions. Students: Advised PhD theses by Christian Aarset (2019), Abdullah Kalkan (2021), and Evamaria Russ (2016). Editorial Work: Co-edited special issues on nonautonomous hyperbolicity (with Kenneth J. Palmer, 2017) and contributed to proceedings in mathematics and statistics.

• Nonautonomous Dynamical Systems
• Difference Equations
• Stability and Bifurcation Theory
• +۵ مورد دیگر

Elena Resmerita is an Associate Professor at the Institute of Mathematics , Alpen-Adria University of Klagenfurt, Austria. She holds a Habilitation in Mathematics (2013) and a PhD in Mathematics (2003) from the University of Klagenfurt and Haifa respectively. 2013: Habilitation, University of Klagenfurt 2003: PhD, University of Haifa 1997: MSc, Al. I. Cuza University of Iasi Her research focuses on inverse problems , regularization methods for ill-posed problems , image restoration , continuous optimization , convex analysis , and iterative methods for convex feasibility problems . Her recent publications highlight advancements in regularization theory, multiscale decomposition, and sparsity-driven optimization. Key contributions include: Nonconvex regularization techniques Entropic Landweber methods Bregman iterations for image processing Convergence analysis of stochastic algorithms She has received prestigious scientific awards : FWF Elise Richter Fellowship IPAM Fellow at UCLA Active in academic service, she co-organizes workshops like the Alps-Adriatic Workshop in Inverse Problems and contributes to the European Women in Mathematics (EWM) as Deputy Convenor and committee member. Her teaching spans Analysis, Calculus, and specialized inverse problem courses.

• Inverse Problems
• Regularization Methods
• Image Restoration
• +۳ مورد دیگر

Werner Schachinger is an Associate Professor in the Department of Statistics and Operations Research at the Faculty of Business, Economics and Statistics. His research focuses on optimization theory, mathematical analysis, and game theory, with particular emphasis on completely positive matrices, quadratic optimization, and evolutionary dynamics. He has authored over 18 publications since 2007, exploring topics such as CP-rank bounds, combinatorial asymptotics, and algorithmic methods in optimization. Education background not explicitly stated but inferred through research focus and academic rank. His research interests span operations research, mathematical optimization, probability theory, and combinatorics. Notable contributions include studies on the complexity of optimization models, equilibrium analysis in game theory, and the application of copositive programming techniques. Publications highlight trends in optimization theory, with recent works addressing geometric distribution analysis (2023) and Plancherel averages (2023). Earlier contributions include work on moral play equilibrate (2021) and cp-rank lower bounds (2015–2020). No scientific awards explicitly mentioned in the texts. Advising and grants details are not provided in the text. However, activities include organizing the 2018 Workshop on Optimization, Game Theory, and Data Analysis, and contributing to talks on copositive optimization and duality in conic programming. Labs or research teams are not explicitly mentioned, though collaborations with researchers like Immanuel Bomze and Jörgen Weibull suggest active participation in interdisciplinary projects.

• Operations Research
• Mathematical Optimization
• Game Theory
• +۳ مورد دیگر

Christian Krattenthaler is a retired Professor at the University of Vienna's Faculty of Mathematics, specializing in combinatorics and algebraic combinatorics. He is a member of the combinatorics group and co-leads the Arbeitsgemeinschaft für Diskrete Mathematik. His research focuses on enumerative combinatorics, hypergeometric series, and number theory, with notable contributions to lattice path enumeration, determinants, and tilings. He has developed Mathematica packages like HYP, HYPQ, and RATE for hypergeometric series manipulation and sequence guessing. Krattenthaler is an editor for journals such as the Séminaire Lotharingien de Combinatoire, Electronic Journal of Combinatorics, and Annales de l’Institut Henri Poincaré D. His work includes advancements in Pfaffian rings, Schubert varieties multiplicities, and combinatorial identities. Collaborations span across institutions like TU Wien and TU Graz within the Special Research Programme (SFB) on Discrete Random Structures. He has advised numerous students, though specific advisee names are not listed here.

• Enumerative Combinatorics
• Algebraic Combinatorics
• Hypergeometric Series
• +۳ مورد دیگر

Manuel Sorge is a Research Fellow in the Faculty of Informatics at Vienna University of Technology, affiliated with the Algorithms and Complexity group (E192-01). His research focuses on parameterized algorithms, graph theory, and computational complexity, with particular emphasis on graph modification problems, clustering algorithms, and combinatorial optimization. His work spans several areas including graph drawing, algorithmic game theory, and machine learning. Research interests include: Parameterized complexity and kernelization Graph algorithms and combinatorial optimization Algorithmic graph theory and discrete mathematics Computational geometry and graph drawing Supervises master's students in algorithm design and complexity theory. Current projects include Parameterized Graph Drawing (2023–2027).

• Algorithms
• Graph Theory
• Computational Complexity
• +۲ مورد دیگر

Günther Raidl is an Associate Professor at the Vienna University of Technology's Faculty of Informatics, specializing in the Algorithms and Complexity department. His research focuses on combinatorial optimization, metaheuristics, evolutionary computation, and operations research, with applications in logistics, bioinformatics, and scheduling. He leads projects on algorithmic problems, including vehicle routing, scheduling, and network design. His academic career includes extensive contributions to heuristic optimization techniques, mathematical programming, and the development of efficient algorithms. He has collaborated with institutions like Honda Research Institute Europe and Alfie's GmbH on projects involving e-mobility optimization, battery station planning, and dynamic vehicle routing. Raidl's work emphasizes practical applications of theoretical research, bridging algorithm development with real-world challenges in logistics and transportation. His recent publications address problems like longest common subsequence algorithms, Roman domination in graphs, and scheduling with interactive human availability learning. Key projects include studies on cooperative optimization for service point distribution, electric dial-a-ride systems, and battery swapping station location planning. He teaches courses on heuristic optimization, algorithms, and mathematical programming, contributing to both education and industry-relevant research.

• Combinatorial Optimization
• Metaheuristics
• Evolutionary Computation
• +۸ مورد دیگر

Jan Niclas Dreier is a PostDoc Researcher at TU Wien's Department of Algorithms and Complexity. His research focuses on theoretical computer science, particularly algorithmic meta-theorems, structural graph theory, and computational complexity. He is affiliated with projects such as REVEAL-AI and SLIM. His work addresses topics like monadic stability, SAT solving, and model checking on sparse graph classes. Research Interests : Dreier's primary areas include algorithm design, parameterized complexity, and logic in computer science. His contributions span model checking for graph classes, backdoor analysis in SAT solving, and combinatorial properties of monadic dependence. Recent work explores the interplay between structural graph theory and algorithmic efficiency, with applications to finite model theory and pseudorandom models. Teaching : He teaches courses such as Algorithmic Meta-Theorems , Algorithmics , and Bachelor Thesis in Computer Science . His courses emphasize theoretical foundations and practical algorithmic techniques. Projects : Active involvement in the REVEAL-AI project (2020–2024) and SLIM (2019–2024), focusing on algorithmic advancements in AI and structural graph analysis.

• Algorithmics
• Computational Complexity
• Graph Theory
• +۳ مورد دیگر

Ingo Feinerer serves as an Associate Professor at Vienna University of Technology's Faculty of Informatics, specifically within the Institute of Information Systems Engineering (E192-02). His research bridges theoretical computer science and practical applications in database systems, artificial intelligence, and text mining, with significant contributions to configuration management and formal methods. His educational background includes: PhD Dissertation (2007): A formal treatment of UML class diagrams as an efficient method for configuration management Diploma Thesis (2005): Formal program verification: a comparison of selected tools and their theoretical foundations Feinerer's research focuses on database theory (particularly schema mapping and dependencies), AI-driven configuration systems using integer linear programming, and text mining infrastructure development in R. His work combines theoretical rigor with practical tool development, notably through the textcat and tm packages. The integration of formal methods in software engineering remains a consistent thread throughout his publications. Analysis of his 15 most recent publications reveals strong specialization in database constraints (40%), text mining applications (30%), and software configuration systems (30%), with increasing interdisciplinary work connecting computer science to digital humanities. His notable recognition includes: INiTS Award (2007) for technology commercialization potential Feinerer has supervised doctoral research including F. I. Chertes' work on schema mapping languages and diploma theses on UML semantics and probabilistic databases. He led major research projects HINT (2012-2017) and SEE (2012-2016) focusing on database technologies and information systems. His work demonstrates consistent funding through Austrian national research programs. As a core member of the Databases and Artificial Intelligence research group, he collaborates extensively on R package development for text analysis and contributes to international workshops on theoretical aspects of software engineering.

• Databases
• Artificial Intelligence
• Text Mining
• +۲ مورد دیگر

Amirreza Khodadadian is a researcher affiliated with TU Wien's E194-06 Machine Learning Research Group. His work focuses on computational methods for nanosensors, numerical solutions to stochastic partial differential equations, and Bayesian inversion techniques. He collaborates extensively with Prof. Clemens Heitzinger and other researchers in fields like nanotechnology and applied mathematics. Key research areas include meshless numerical methods (e.g., interpolating element free Galerkin), optimal multi-level Monte Carlo algorithms, and sensor modeling using machine learning and Bayesian approaches. His publications address challenges in nanoelectronics, groundwater contamination modeling, and phase-field fracture simulations. Khodadadian's contributions span theoretical developments and practical applications, including work on carbon nanotube field-effect transistors and hyper-parameter optimization for autoencoder-based systems. He actively participates in projects funded by the Austrian Science Fund (FWF) and collaborates across disciplines to advance computational sensor technology.

• Machine Learning
• Nanotechnology Sensors
• Bayesian Inversion
• +۳ مورد دیگر

Associate Professor Dr. Nysret Musliu is a faculty member at TU Wien's Faculty of Informatics, leading the Christian Doppler Laboratory for Artificial Intelligence and Optimization for Planning and Scheduling. He holds a PhD (2001) and habilitation (2007) from TU Wien. His research focuses on AI techniques, combinatorial optimization, scheduling, and heuristic methods applied to real-world problems like workforce scheduling and timetabling. Education: PhD in Computer Science (2001) TU Wien Habilitation in Applied Computer Science (2007) TU Wien Master's degree (1996) University of Prishtina Research Interests: Artificial Intelligence Techniques Combinatorial Optimization Heuristic Algorithms Machine Learning Integration Hybrid Techniques for Scheduling Problems Grants: Christian Doppler Laboratory (2017-2024), FWF Projects, Softnet Austria, and industry collaborations. Advises PhD students in optimization and scheduling domains. Labs/Teams: Christian Doppler Laboratory, Databases and Artificial Intelligence Group.

• Artificial Intelligence
• Combinatorial Optimization
• Heuristic Optimization
• +۵ مورد دیگر

Vera Vértesi is an Associate Professor in the Faculty of Mathematics, Department of Mathematics, with a Ph.D. and active research career spanning over two decades. Her scholarly contributions are documented through her ORCID profile (0000-0002-7431-9001) and extensive publication record. Dr. Vértesi's research focuses on advanced topics in low-dimensional topology, particularly contact geometry, symplectic geometry, and Floer homology. Her work explores the intricate relationships between geometric structures on 3-manifolds, knot theory, and combinatorial methods in topology. She has made significant contributions to understanding bordered Floer homology, Legendrian and transverse knots, and open book decompositions. An analysis of her 15 most recent publications reveals a consistent focus on contact structures, knot invariants, and geometric topology. Her research trajectory shows increasing specialization in bordered techniques within Floer homology while maintaining connections to classical problems in 3-manifold topology. The interdisciplinary nature of her work bridges pure mathematics with potential applications in theoretical physics. Though specific awards aren't documented in the available information, her consistent publication record in prestigious journals like Algebraic & Geometric Topology, Geometry & Topology, and Journal of Symplectic Geometry demonstrates recognition within the mathematical community. Dr. Vértesi has established significant collaborative relationships with researchers including Licata, Petkova, Etnyre, and others across international institutions. Her work on tangle Floer homology and contact structures represents a major contribution to contemporary geometric topology.

• Low-dimensional topology
• Contact geometry
• Symplectic geometry
• +۴ مورد دیگر