جست‌وجوی استاد و پژوهشگر

• Human-Computer Interaction
• Information Visualization
• Web Usability
• +۴ مورد دیگر

Keith Andrews is an Associate Professor at the Graz University of Technology , affiliated with the Department of Human-Centred Computing. His research spans Human-Computer Interaction (HCI), Information Visualization, and Web Usability, with a focus on improving interactive tools, responsive design, and accessibility in data visualization. Andrews' work emphasizes practical applications, including the development of responsive SVG chart libraries and pedagogical strategies for teaching HCI to large undergraduate cohorts. His research integrates principles from Computer Science, User Experience (UX), and Software Engineering. Scientific Awards Best Paper Award at IWAIT 2019 Certificate of Appreciation 2006 Heinz Zemanek Preis 1998 Steirische Vielfalt visualisiert 2016 Recent publications highlight trends in Information Visualization , Responsive Web Design , and Active Learning algorithms. His projects, such as DYONIPOS and UX Day Graz, demonstrate a commitment to interdisciplinary collaboration and real-world impact.

• Quantum Physics
• Quantum Computing
• Quantum Information
• +۳ مورد دیگر

Refik Mansuroglu is a researcher affiliated with the University of Vienna. His work spans quantum computing, quantum information, and computational physics, with a focus on quantum simulation and algorithm development. University: University of Vienna Research Areas: Quantum Physics, Quantum Computing, Quantum Information Research Interests: Refik Mansuroglu specializes in quantum algorithms, Hamiltonian simulation, and quantum state optimization. His research explores classical-quantum hybrid methods, noise reduction in quantum systems, and applications of variational techniques to translational invariant and periodically driven systems. Additionally, he has contributed to foundational studies in loop quantum gravity, particularly in spin matter fields and discrete spacetime models. Article Trends: His recent work emphasizes variational algorithms for quantum simulation, error mitigation in near-term quantum devices, and classical optimization strategies for quantum circuits. Earlier publications delve into quantum gravity and photonic simulations, reflecting a multidisciplinary approach across quantum mechanics and computational physics. Advising & Collaborations: No specific students or advising roles are mentioned in the provided data.

• Algorithms
• Sparse Matrices
• Parallel Computing
• +۳ مورد دیگر

Robert Ernstbrunner is a researcher affiliated with the Faculty of Computer Science , contributing to algorithm development and parallel computing. His work focuses on low-rank approximations and fault-tolerant strategies in linear algebra methods. Research Interests: His research spans computational efficiency, numerical linear algebra, and fault tolerance in high-performance computing environments. Key areas include sparse matrix operations and resilience mechanisms for iterative algorithms. Publications: He has published two peer-reviewed papers: (1) a 2022 study on precision-cost trade-offs in low-rank matrix approximations, and (2) a 2020 framework for node-failure resilience in iterative linear algebra methods. Academic Activities: Robert has presented at international conferences, including the 2022 IEEE IPDPS and the 2020 FTXS workshop.

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

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.

• Quantum Physics
• Quantum Computing
• Optimization
• +۳ مورد دیگر

Gabriele Uchida is a Professor in the Research Group Education, Didactics and Entertainment Computing at the Faculty of Computer Science. Their work spans quantum physics, optimization theory, and education technology. Notable contributions include studies on entanglement in quantum systems and copositive optimization. Uchida has organized academic events like the Informatiktag series and contributed to conferences on mathematical optimization. Research interests focus on quantum entanglement mechanisms, algorithmic optimization, and integrating IT into educational practices. Their publications highlight interdisciplinary approaches, blending theoretical physics with computer science. Publications analyze quantum dots, copositive matrices, and blended learning strategies, with citations in top journals. Activities include academic event organization and peer-reviewed presentations on topics like conic optimization.

Masana Castrillo, Marcمشاهده پروفایل

پژوهشگر

• Deep Learning
• Continual Learning
• Computer Vision
• +۳ مورد دیگر

Herr Marc Masana Castrillo is a Researcher at the Institute of Computer Graphics and Vision within Graz University of Technology (College of Engineering). Holding a PhD in Computer Vision (cum laude) from Universitat Autònoma de Barcelona (2020), he specializes in Deep Learning , Continual Learning , and Neural Network Compression . His work addresses catastrophic forgetting in sequential tasks, out-of-distribution detection, and domain adaptation. PhD Thesis: "Lifelong Learning of Neural Networks: Detecting Novelty and Adapting to New Domains without Forgetting" MSc in Computer Vision (with Honours, 2015) BSc in Mathematics and Computer Science (2014) His research spans continual learning frameworks , feature disentanglement , and multimodal translation . Publications in top-tier venues like TPAMI , BMVC , and ICCV highlight his contributions. He co-developed Avalanche , an open-source PyTorch-based library for reproducible continual learning research. Scientific recognition includes the Best Master Thesis Project at UAB (2015) and the Business Track Award at Accenture Datathon (2016). His email addresses are mmasana@tugraz.at and marc.masana@icg.tugraz.at . He has reviewed for journals like TPAMI and conferences including CVPR and ICCV .

Stefan Neumannمشاهده پروفایل

استادیار

• Machine Learning
• Social Network Analysis
• Graph Algorithms
• +۴ مورد دیگر

Stefan Neumann is an Assistant Professor at TU Wien, funded by a WWTF VRG grant, and an associate faculty member at the Complexity Science Hub. His research focuses on algorithms for data science and social network analysis, including opinion dynamics, graph algorithms, and scalable algorithms with provable guarantees. He coordinates the Machine Learning curriculum for the Master's program at TU Wien. Education: Ph.D. from the University of Vienna (advised by Monika Henzinger), postdoc at Brown University with Eli Upfal, and WASP assistant professor at KTH Royal Institute of Technology. He won the Heinz Zemanek Award and an Award of Excellence from the Austrian federal government. Research interests include: Foundations of data science: Practical algorithms with theoretical guarantees Social network analysis: Impact of timeline algorithms on polarization Graph algorithms and dynamic data structures Projects include Towards Trustworthy Recommendation Systems for Online Social Networks (2023–2031, funded by Vienna Science and Technology Fund). Teaching: Courses on machine learning, algorithms, and research writing. Advises PhD students like Sebastian Lüderssen and manages a team of student assistants. Labs/Teams: Active in TU Wien's Machine Learning Research Unit and collaborates with the Complexity Science Hub on interdisciplinary projects.

• Theoretical Computer Science
• Graph Algorithms
• Computational Geometry
• +۳ مورد دیگر

Sara Di Bartolomeo is a Researcher in the Algorithms and Complexity group at the University of Technology Vienna , Faculty of Informatics. Her work focuses on advanced graph visualization techniques and network analysis. Projects: Simultaneous Multiprojection Graph Visualization (FWF-funded), ArtVis (2022–2027), SANE (2024–2027), SMGV-Esprit (2024–2027) Contact: sara.bartolomeo@tuwien.ac.at Her research emphasizes graph algorithms , computational geometry , and data visualization , particularly in handling uncertainty and physicalization of networks. Recent publications explore animated node-link diagrams, game-based network analysis, and BioFabric pattern optimization. Contact: sara.bartolomeo@tuwien.ac.at

Regino Criadoمشاهده پروفایل

استاد

• Complex Networks
• Discrete Mathematics
• Cybersecurity
• +۴ مورد دیگر

Dr. Regino Criado is Full Professor of Applied Mathematics at Rey Juan Carlos University (URJC), where he has held academic positions since June 2000. He currently serves as Academic Director of the Data, Complex Networks and Cybersecurity Sciences Institute (since March 2017) and was elected to the Academia Europaea in May 2023. His career spans European research projects (ESPRIT II/III) and interdisciplinary collaborations at the intersection of mathematics, computer science, and cybersecurity. His research focuses on Complex Networks , including hyper-networks, multiplex networks, and mesoscale structures, with applications to cybersecurity, intentional risk management, and synchronization phenomena. Key innovations include: A game theory-based intentional risk model integrating accessibility, anonymity, and value metrics Hybrid network mining algorithms for credit card fraud detection PageRank extensions to multiplex networks Framework for discrete resilience analysis in technological systems His work on the 2014 Physics Reports monograph The structure and dynamics of multilayer networks (3,500+ citations) established foundational concepts in multilayer network theory. Current research explores linguistic pattern analysis through multilayer hypergraphs for automatic text summarization. Member of Academia Europaea (2023) Chaos Journal Best Paper Award (2011) Academic Entrepeneurs Prize (2002) EUROPA-1992 Prize (1992) As director of the DCNC Institute (2017-present) and BBVA-URJC Chair (2017-2018), he has led major academic-industry collaborations. His 180+ publications (6,500+ citations) demonstrate sustained impact across network science, applied mathematics, and cybersecurity.

• Bioinformatics
• Genomics
• Cancer Research
• +۵ مورد دیگر

Leila Taher is a researcher at the Institute of Biomedical Informatics, TU Graz. Her work focuses on integrating computational methods with genomic data to study cancer biology, epigenetic regulation, and comparative oncology. She has developed tools like T3E and DNA-DDA for analyzing transposable elements and 3D chromatin structure. Her research spans canine and feline cancer models, immune mechanisms, and functional genomics. Key projects include designing targeted NGS panels for canine lymphoma and exploring synergistic drug combinations for B-cell lymphoma. Her interdisciplinary approach bridges bioinformatics, veterinary medicine, and human health. Education and affiliations are not explicitly detailed in the text, but her long-term contributions to genomics (publications span 2003–2024) suggest advanced academic training. Collaborations involve molecular biology, computational biology, and clinical oncology teams. She leads research in areas such as chromatin architecture prediction, enhancer function, and immune cell regulation. Her lab's tools have been applied to study autoimmune diseases, developmental biology, and translational medicine. Research themes include: (1) Developing algorithms for genomic analysis, (2) Investigating epigenetic mechanisms in cancer, (3) Translating canine models to human oncology, and (4) Exploring gene regulatory networks in development. Recent work emphasizes reproducibility in NGS pipelines and the role of repetitive elements in functional genomics.

• Fractal Geometry
• Number Systems
• Dynamical Systems
• +۳ مورد دیگر

Thuswaldner Jörg is a Professor and Chair of Mathematics, Statistics, and Geometry at TU Graz’s Faculty of Mathematics, Physics, and Geodesy. His research focuses on fractal geometry, number systems, dynamical systems, and tiling theory. He has supervised 8 doctoral and master’s theses, notably on topics like Rauzy fractals, solidification microstructure modeling, and self-affine tiles. Key research trends include exploring the topology of self-affine tiles, properties of number systems (e.g., continued fractions, Ostrowski representations), and applications of fractal theory. His work bridges pure mathematics (e.g., algebraic geometry) with applied areas like material science (e.g., fatigue strength analysis of alloys). He has advised students such as Loridant, Surer, and Rossi, and contributed to 80+ publications. His research often intersects with computational geometry and discrete mathematics, with recent focus on fractal dimension theory and Lyapunov exponents in dynamical systems.

• Fractal Geometry
• Number Theory
• Dynamical Systems
• +۳ مورد دیگر

Jörg Thuswaldner is a Professor at the Chair of Mathematics, Statistics and Geometry at Montanuniversität Leoben. His research focuses on fractal geometry, number theory, dynamical systems, and combinatorics, with a particular emphasis on topics such as self-affine tiles, continued fraction algorithms, and digit systems. He has published extensively in top-tier journals such as Advances in Mathematics and Journal of Number Theory , contributing to the understanding of fractal structures, metric number theory, and symbolic dynamics. His editorial roles include serving on the boards of Lithuanian Mathematical Journal and Combinatorics and Number Theory , highlighting his influence in academic publishing. He actively collaborates internationally, hosting visiting scholars and participating in conferences to advance interdisciplinary research. Recent work explores applications of fractal geometry to permeable sets and the analysis of Weyl sums with digital restrictions. Thuswaldner’s research spans over two decades, with publications ranging from foundational studies in tiling theory to cutting-edge analyses of non-standard digit systems. His contributions bridge pure mathematics with applications in algebraic geometry and ergodic theory, making him a leading figure in modern mathematical research.

• Numerical Analysis
• Partial Differential Equations
• Computational Mathematics
• +۳ مورد دیگر

Othmar Koch is a Professor at TU Wien's Institute of Analysis and Scientific Computing, part of the Faculty of Mathematics and Geoinformation. His research focuses on numerical analysis, computational methods for differential equations, and quantum mechanics simulations. He has contributed to adaptive integrators, exponential time propagation methods, and software development for boundary value problems (e.g., bvpsuite2.0). Education and affiliations: Primary affiliation is TU Wien's Institute of Analysis and Scientific Computing. Collaborations include projects on solar cell modeling, Bose-Einstein condensates, and nonlinear wave equations. Research interests emphasize numerical stability, adaptive algorithms, and computational techniques for stiff equations and quantum systems. His work bridges theoretical analysis with practical software tools for solving complex mathematical models. Key contributions include adaptive exponential integrators, Magnus-type methods for quantum systems, and continuation methods for parameter-dependent boundary value problems. He has advised students on topics like collocation methods (Merlin Fallahpour), singular BVPs (Amir Saboor Bagherzadeh), and semi-infinite interval eigenvalue problems (Christa Simon). The Network Lab may be associated with his research activities.

• Transportation Engineering
• Simulation Modeling
• Urban Mobility Analysis
• +۲ مورد دیگر

Franz-Xaver Rupprecht is a researcher at the Institute of Transport Studies , part of the Department of Landscape, Water and Infrastructure at the University of Natural Resources and Life Sciences, Vienna (BOKU) . His work focuses on transportation modeling and simulation. Research interests include: Dynamic transportation network modeling Origin-destination matrix disaggregation Stochastic trip synthesis algorithms Urban mobility simulation He has presented at international conferences like the MATSim User Meeting and hEART Symposium , showcasing work on all-day round-trip synthesis and transportation behavior analysis.

• Mathematics
• Applied Mathematics
• Harmonic Analysis
• +۳ مورد دیگر

Norbert Kaiblinger is an Associate Professor at the Institute of Mathematics, BOKU University, Vienna, Austria. His research focuses on applied mathematics, harmonic analysis, and numerical methods, with applications in fluid mechanics, statistics, and chemical engineering. He holds a habilitation in Mathematics from the University of Vienna, granting him teaching authorization in the field. His work bridges theoretical mathematics with practical computational problems, particularly in adsorption modeling and fluid dynamics. Key research interests include multicomponent batch adsorption models, dynamics of subaqueous systems, analysis of variance (ANOVA) methodologies, and special functions. Recent publications (2023–2025) highlight advancements in equilibrium composition calculations and statistical experimental design. His earlier work (2007–2019) explores Fourier analysis, operator theory, and algebraic structures like cyclotomic rings and circulant matrices. While no formal advising relationships or grants are listed, his collaborative research involves co-authors from diverse fields such as chemical engineering and fluid mechanics. Kaiblinger’s work is disseminated through journals like Adsorption, Journal of Fluid Mechanics, and Transactions of the American Mathematical Society.