جستجوی استاد راهنمای دانشگاهی

Vladimir Kazeevمشاهده پروفایل

استادیار

• Numerical Analysis
• Tensor Methods
• Partial Differential Equ to the data-driven solution of PDEs
• +۳ مورد دیگر

Vladimir Kazeev is an Assistant Professor at the Faculty of Mathematics, University of Vienna , where he has held a faculty position since 2019. He also held previous academic appointments as a Szegő Assistant Professor at Stanford University (2017–2019), a postdoctoral researcher at the University of Geneva (2015–2017), and research positions at ETH Zurich (2011–2015), Russian Academy of Sciences (2008–2011), and Moscow Institute of Physics and Technology (2009). His research focuses on adaptive, data-driven numerical methods for differential equations, nonlinear low-parametric approximation, and numerical linear algebra. His work intersects computational mathematics, tensor methods, and high-dimensional problem-solving, particularly in the context of partial differential equations (PDEs) and stochastic modeling. The 15 most recent publications reveal a strong emphasis on quantized tensor-structured methods for PDEs, low-rank approximations, and high-dimensional numerical analysis. His research spans theoretical advancements in tensor decomposition, practical applications in chemical reaction networks, and novel discretization techniques for multiscale and degenerate diffusion problems. Scientific awards include the prestigious ETH Medal for outstanding doctoral theses (2016) Russian Academy of Sciences Medal for outstanding student works in mathematics (2011) Advising and teaching activities include supervising Jason Zhu (Stanford, 2019) and Simon Etter (ETH Zurich, 2014), as well as teaching advanced courses in tensor methods, numerical analysis, and PDEs at the University of Vienna, Stanford University, and the University of Geneva. His service to the community includes peer review for 15+ journals and co-organizing minisymposia at SIAM meetings.

• 3D Printing
• Ceramic Materials
• Sustainable Materials
• +۳ مورد دیگر

Julian Jauk is a Researcher at the Institute for Architecture and Media, TU Graz. His work focuses on innovative material systems, digital fabrication, and sustainable architectural design. He explores the integration of clay composites, mycelium-based materials, and knitted structures with advanced manufacturing techniques like 3D printing. Key research themes include lightweight ceramic structures, biocomposite materials, and computational design methodologies. His research emphasizes material-driven innovation, structural optimization, and environmental sustainability. Notable projects include MyCera (clay-mycelium composites) and ClayKnit (3D-printed clay-knitted hybrids). He also investigates mixed reality tools for architectural sketching and kinetic architectural prototypes. Publications from 2021–2024 highlight trends in bio-based materials, additive manufacturing, and material-property analysis. His work bridges traditional craftsmanship with cutting-edge digital fabrication, aiming to redefine sustainable building practices.

Karl Fristonمشاهده پروفایل

استاد

• Imaging neuroscience
• Computational neuroscience
• Theoretical neurobiology
• +۳ مورد دیگر

Karl Friston is a renowned neuroscientist and Professor at the Institute of Neurology, University College London . As Scientific Director of the Wellcome Trust Centre for Neuroimaging, he has pioneered transformative methodologies in brain imaging, including statistical parametric mapping (SPM) , voxel-based morphometry (VBM) , and dynamic causal modelling (DCM) . His theoretical work on the free-energy principle and active inference has reshaped understanding of brain function. Key Positions : Scientific Director (Wellcome Trust Centre), Fellowships at MRC units, Keck Foundation Fellow Research Focus : Functional integration in the human brain, computational models of neuronal interactions, schizophrenia, and Bayesian brain theory. Scientific Awards : Wiley Young Investigator Award (1996) Golden Brain Award (2003) Fellow of the Royal Society (2006) Weldon Memorial Medal (2013) EMBO Membership (2014)

Nikolaus Hautschمشاهده پروفایل

استاد

• Econometrics
• Finance
• Market Microstructure
• +۳ مورد دیگر

Nikolaus Hautsch is a full Professor at the Faculty of Economics, Institute of Statistics and Operations Research. His work focuses on econometrics, finance, and high-frequency data analysis. Research Interests : Market microstructure, volatility modeling, transaction costs, systemic risk, and machine learning applications in finance. Publication Trends (2025–2018): 2025: High-dimensional portfolio optimization, dynamic systemic risk 2024: Blockchain asset arbitrage, DeFi, polarization metrics, jump detection 2023–2022: Microstructural noise, volatility forecasting, neural networks Scientific Awards : Fellow of the Society for Financial Econometrics (2014) Projects : Artificial Intelligence in Rowing (2022–2025) Vienna Graduate School of Finance (2018–2022) Risk management of CCPs

• Antenna Design
• Microwave Engineering
• Dielectric Materials
• +۲ مورد دیگر

Wolfgang Bösch is a Professor at Graz University of Technology's Institute of Microwave and Photonic Engineering, specializing in advanced RF components and measurement techniques. His research advances high-frequency systems through innovations in antenna technology and electromagnetic theory. Research domains include: metamaterial-based antennas, precision measurement calibration, microwave filter optimization, and 3D-printed RF components. Recent work demonstrates strong focus on millimeter-wave systems and reconfigurable antenna arrays. Publications highlight expertise in: machine learning for filter design, metasurface applications, PCB transitions for high-frequency systems, and uncertainty quantification in RF engineering. Research consistently addresses miniaturization and performance optimization challenges. Awards recognize contributions to measurement science and antenna design: Fellow of IET, Houska Prize, and best paper awards. Current laboratories investigate liquid crystal antenna systems and error calibration methodologies for next-generation wireless systems.

Sylvain Lefebvreمشاهده پروفایل

پژوهشگر

• Computer Graphics
• Texture Synthesis
• Additive Manufacturing
• +۴ مورد دیگر

Sylvain Lefebvre is a permanent researcher at INRIA (Institut National de Recherche en Informatique et en Automatique) in France, where he leads the MFX research team since 2018. Previously, he was part of the ALICE group at INRIA Nancy (2009-2018) and the REVES team in Sophia Antipolis (2006-2009). His career includes a postdoctoral position at Microsoft Research Seattle (2005) following his PhD at INRIA Rhones-Alpes under Fabrice Neyret. His educational background includes a PhD in Computer Graphics from Université Joseph Fourier (Grenoble) in 2005, preceded by a Master in Computer Graphics from INP Grenoble in 2001. His habilitation thesis focused on Runtime Texture Synthesis. Lefebvre's research centers on simplifying content creation for highly detailed patterns, structures, and shapes with applications spanning Computer Graphics to additive manufacturing. He develops fast, controllable by-example synthesis approaches that generate content while enforcing user-specified constraints. His work addresses computational challenges through novel data structures and algorithms optimized for GPUs and FPGAs, including his Silice programming language. The ERC-funded ShapeForge project (2012-2017) advanced shape generation for 3D printing, leading to the IceSL software for digital modeling and fabrication. Analysis of his 15 most recent publications reveals a strong focus on additive manufacturing optimization, with recurring themes in structural integrity, material efficiency, and geometric algorithms. His work bridges computer graphics theory with practical fabrication constraints, particularly in microstructure design, slicing techniques, and mechanical metamaterials. The interdisciplinary nature spans computer science, materials engineering, and robotics. EUROGRAPHICS Young Researcher Award (2010) ERC Starting Grant for ShapeForge project (2012) Lefebvre has advised over 25 PhD students and interns including Marco Freire, Thibault Tricard, and Jimmy Etienne. His ShapeForge project received significant ERC funding, supporting research in computational fabrication. He serves on numerous program committees including SIGGRAPH, Eurographics, and SIGGRAPH Asia, reflecting his leadership in the computer graphics community. As leader of the MFX team since 2018, Lefebvre directs research in computational fabrication, focusing on IceSL software development for 3D printing workflows. The team integrates computer graphics techniques with manufacturing constraints, developing tools that simplify complex object design and fabrication while addressing real-world challenges in material usage and structural integrity.

Enrique Sentanaمشاهده پروفایل

استاد

• Econometrics
• Asset Pricing
• Financial Economics

Enrique Sentana is a Professor of Economics at CEMFI (Centro de Estudios Monetarios y Financieros) in Madrid, Spain. He is also a Research Fellow at the CEPR Financial Economics Programme and a Senior Research Associate at the LSE Financial Markets Group. His academic career spans prestigious institutions including the London School of Economics and the University of Alicante. Degrees: PhD in Economics (LSE, 1991), MSc in Econometrics and Mathematical Economics (LSE, 1987), Licenciado en Ciencias Económicas y Empresariales (University of Alicante, 1985) Dr. Sentana specializes in Econometrics , with a focus on Asset Pricing , Financial Economics , and VIX Derivatives . His methodological contributions include work on ARCH models, indirect estimation, and identification issues in econometrics, advancing volatility modeling and financial risk assessment. His research trends highlight innovations in empirical asset pricing , nonlinear time series , and financial market linkages . Notable achievements include the Rey Jaime I Prize in Economics (2014) , Fellowships at the Econometric Society and Journal of Econometrics , and prestigious prizes from the University of London and LSE. Scientific Awards: Rey Jaime I Prize in Economics (2014) Fellow of the Econometric Society (2012) Fellow of the Journal of Econometrics (2010) Sayers Prize, University of London (1992) Ely Devons Prize, London School of Economics (1987) Dr. Sentana has advised 10 PhD students at CEMFI and held editorial roles including Managing Editor of the Review of Economic Studies and Co-Editor of the Journal of Financial Econometrics . He has also served as Executive Vice-President of the Econometric Society and Treasurer of its European Standing Committee.

Joost-Pieter Katoenمشاهده پروفایل

استاد

• Model Checking
• Formal Verification
• Probabilistic Models
• +۵ مورد دیگر

Joost-Pieter Katoen is a full Professor at RWTH Aachen University and Head of its Computer Science Department since 2012. He also holds a part-time (20%) Professorship at the University of Twente . His research focuses on model checking , probabilistic verification , formal semantics , and software verification , with applications in aerospace systems. His work has led to significant tools like MRMC (probabilistic model checker), COMPASS (AADL analysis tool-set), and libalf (learning automata library). He has authored over 18 international projects (total €5.2 million) and graduated 12 PhD students. Scientific Awards : Member, German National Academy of Sciences (Leopoldina), 2024 ACM Fellow, 2020 ERC Advanced Grant, 2018 Honorary doctorate, Aalborg University, 2017 Teaching Award, RWTH Aachen, 2010 Philips Early Career Development Award, 1988 Research Trends (from articles): His recent work spans probabilistic program verification , quantitative game theory , Markov chain analysis , and parameter synthesis for stochastic systems, with applications in AI, quantum computing, and fault tree analysis. Leadership & Service : Katoen co-founded the QEST conference , chairs ETAPS steering committee, and has led numerous program committees (CONCUR, TACAS, QEST). He has served on editorial boards and organized conferences/seminars globally.

Sara van de Geerمشاهده پروفایل

استاد

• Mathematics for machine learning
• High-Dimensional statistics
• Empirical processes
• +۲ مورد دیگر

Sara van de Geer is a Full Professor at the Seminar for Statistics within the Department of Mathematics at ETH Zürich since 2005. She previously held academic positions at the University of Leiden, Université Paul Sabatier (Toulouse), and others. She earned a Master's (1982) and Ph.D. (1987) in Mathematics from Leiden University. Her research focuses on high-dimensional statistics, empirical processes, and mathematical foundations of machine learning. Van de Geer has received prestigious recognitions including the Van Wijngaarden Award (2016), Knight in the Order of Orange-Nassau (2015), and membership in Leopoldina (2013). She served as President of the Bernoulli Society (2015–2017) and Chair of the Seminar for Statistics at ETH Zürich. Her contributions include landmark works on statistical learning theory and high-dimensional inference, with key publications in top journals like Annals of Statistics and SIAM/ASA Journal on Uncertainty Quantification. Her academic leadership includes organizing Saint Flour Lectures, Wald Lectures (2016), and delivering plenary lectures globally. Her research bridges theoretical statistics with applied methodologies, emphasizing rigorous mathematical frameworks for modern data analysis challenges.

• Environmental Microbiology
• Molecular Diagnostics
• Water Quality
• +۳ مورد دیگر

Prof. Andreas Farnleitner is a Professor at TU Wien, affiliated with the Environmental Microbiology and Molecular Diagnostics Research Group. His research focuses on microbial water quality, molecular diagnostics, and environmental microbiology. Key areas include PCR-based methods for fecal pollution tracking, antimicrobial resistance in aquatic environments, and climate change impacts on waterborne pathogens. He has contributed to advancements in DNA aptamer technology for rapid water quality monitoring and employs machine learning for predictive modeling in hydrology. His work spans collaborations across Europe, addressing One Health challenges and wastewater-based epidemiology. Recent projects include studies on Vibrio cholerae in Austrian bathing waters and the biostability of drinking water resources. Prof. Farnleitner leads interdisciplinary initiatives to improve water safety and environmental management. Publications highlight his expertise in microbial source tracking, climate change effects on infection risks, and antibiotic resistance patterns. His team develops innovative diagnostic tools and models for environmental monitoring, with applications in both academic and applied settings. Current projects emphasize the integration of molecular biology and engineering to address global water quality challenges.

• Diophantine Approximation
• Geometry of Numbers
• Parametric Approximation
• +۴ مورد دیگر

Leonhard Summerer is an Associate Professor at the Faculty of Mathematics, Department of Mathematics . His research primarily focuses on Diophantine Approximation , Geometry of Numbers , and Parametric Approximation . His work explores the Approximation Property in parametric settings, Lattice Theory , and Linear Dependence in number theory. Recent publications include studies on Jarník’s identity, simultaneous approximation to multiple reals, and geometric interpretations of number-theoretic problems. He has authored numerous peer-reviewed articles and contributed chapters to educational books such as 77-mal Mathematik für Zwischendurch , emphasizing mathematical outreach and pedagogical innovation . Active in academic discourse, he has delivered talks on topics like Packings and Tilings in Z and Simultane Approximation m reeller Zahlen since 2006.

• Sustainable Structural Engineering
• Additive Manufacturing in Construction
• Biobased Materials
• +۳ مورد دیگر

Benjamin Kromoser is a Professor for Resource Efficient Structural Engineering at the Institute of Green Civil Engineering (BOKU Vienna). He leads research projects on sustainable construction methods, including additive manufacturing of biobased materials, timber-concrete composites, and topology optimization of structural elements. His work bridges digital fabrication, circular economy principles, and industry 4.0 in civil engineering. Head of Institute of Green Civil Engineering (2022–present) Speaker of Doctoral School Build.Nature (2021–2022) University Professor for Biobased Design (2018–2022) His research focuses on reducing environmental impacts through automated design, 3D printing of concrete, and non-metallic reinforcement. Recent projects include 3DP Biowalls (biobased recyclable walls) and prestressed carbon-UHPC elements. Scientific awards include the fib Achievement Award (2019) , Inits Award (2016) , and Bundespreis für Ecodesign (2016) .

• Mathematical Physics
• Partial Differential Equations
• Computational Mathematics
• +۷ مورد دیگر

Norbert Mauser is a full Professor in the Department of Mathematics at the University of Vienna, where he has been affiliated since 1999. His research bridges mathematical analysis, computational physics, and applied mathematics with a focus on developing and analyzing numerical methods for complex physical systems. Mauser's research interests center on mathematical physics, particularly partial differential equations arising in quantum mechanics and magnetism. His work spans Schrödinger-type equations, many-body quantum systems, micromagnetics, and more recently, the integration of machine learning techniques with physics-based modeling. He has made significant contributions to the mathematical analysis of quantum systems, numerical methods for micromagnetics, and computational approaches to Bose-Einstein condensates. His recent publications (2023-2025) reveal a growing emphasis on machine learning applications in micromagnetics, with multiple papers on physics-informed machine learning for magnetic energy minimization and spin wave dynamics. This represents an evolution from his earlier foundational work on Schrödinger equations and quantum systems toward more applied computational approaches that integrate AI with physical modeling. His research consistently demonstrates strong mathematical rigor combined with practical computational implementations. Mauser leads or participates in multiple significant research projects including 'Adaptive Splitting for Magneto-Hydrodynamics in Astrophysics' (2022-2026), 'Taming Complexity in Partial Differential Systems' (2017-2026), and 'Numerical simulation of A-type and white dwarf stars' (2021-2023). He has an extensive collaboration network across Europe, frequently working with researchers in computational physics and applied mathematics. His academic activities include organizing conferences such as 'Inverse-Design Magnonics' (2024) and presenting invited talks on absorbing boundary conditions for quantum wave equations. With over 80 publications spanning more than two decades, Mauser maintains an active research program that continues to evolve with contemporary challenges in computational mathematical physics.

• Architectural Geometry
• Digital Design
• Sustainable Materials
• +۴ مورد دیگر

Milena Stavric is an Associate Professor at TU Graz's Institute for Architecture and Media. Her research focuses on architectural geometry, digital design, and sustainable materials. She integrates computational methods and digital fabrication techniques into architectural design, emphasizing eco-friendly materials like mycelium composites, alginate-based materials, and clay ceramics. Her work bridges theoretical research with practical applications, such as BIM integration for salvage materials and parametric modeling for freeform structures. She teaches courses in architectural geometry and digital design, contributing to advanced computational workflows from concept to fabrication. Her projects often explore the interplay between material properties and structural form, aiming to advance sustainable construction practices. Research interests include: sustainable building materials (e.g., mycelium-based insulation, alginate xerogels), parametric design strategies, and digital fabrication methods for lightweight ceramics. She explores novel fabrication techniques like coextrusion of clay composites and robotic fabrication of modular formwork. Her work frequently addresses environmental impacts through life cycle assessments and biogenic carbon analysis. Key projects involve material innovation (e.g., MyCera: clay-mycelium composites), digital tools development for early design phases, and educational initiatives like interactive math learning environments. Her contributions span academic publications and applied research, with a focus on integrating geometry, computation, and sustainability in architectural practice.

• Numerics of Partial Differential Equations
• Computational Micromagnetism
• Optimal Mesh Refinement
• +۳ مورد دیگر

Michael Feischl is a Univ. Prof. at TU Wien's Institute for Analysis and Scientific Computing (E101). He specializes in numerical methods for partial differential equations, computational micromagnetism, and optimal adaptivity. Feischl leads the ERC Consolidator Project 'New Frontiers in Optimal Adaptivity' and has held academic positions at TU Wien, University of Bonn, and Karlsruhe Institute of Technology. His research interests span stochastic perturbations, finite element methods, and machine learning applications in computational mathematics. Feischl's work includes groundbreaking contributions to adaptive finite element methods, optimal mesh refinement strategies, and the numerical analysis of the Landau-Lifshitz-Gilbert equation in micromagnetics. His recent publications focus on advancing computational techniques for PDEs, neural operator networks, and stochastic collocation methods. He has developed algorithms with guaranteed convergence properties and optimal complexity, contributing to both theoretical and applied aspects of computational science. Education: Dipl.-Ing. Dr.techn. (PhD in Technical Mathematics) from TU Wien Awards: ERC Consolidator Grant 2022 Labs/Teams: Heads the 'Computational PDEs' research group at TU Wien's Institute for Analysis and Scientific Computing