جستجوی استاد راهنمای دانشگاهی

• Optimization and optimal control
• Inverse problems
• Mathematical imaging
• +۵ مورد دیگر

Karl Kunisch is a Professor at the Department of Mathematics and Scientific Computing at the University of Graz and serves as Scientific Director of the Radon Institute of the Austrian Academy of Sciences in Linz. With a distinguished career spanning several decades, he has established himself as a leading researcher in optimization and control theory. Prof. Kunisch completed his PhD and Habilitation at the Technical University of Graz in 1978 and 1980, respectively. His academic journey includes significant positions at Brown University's Lefschetz Center for Dynamical Systems, INRIA Rocquencourt, Universite Paris Dauphine, and he previously served as a professor of numerical mathematics at the Technical University of Berlin. Research Interests: Prof. Kunisch's research focuses on optimization and optimal control, inverse problems and mathematical imaging, numerical analysis and applications, with current emphasis on life sciences applications. His specific areas include Optimal Control of Partial Differential Equations, Nonsmooth Optimization in Function Spaces, and Applications of Optimization and Control in the Life Sciences. His work bridges theoretical mathematics with practical applications across various scientific domains. His recent publications demonstrate a continued focus on advancing the theoretical foundations of optimal control while developing practical numerical methods. Key trends include work on infinite horizon control problems, feedback stabilization techniques, applications to PDE-constrained optimization, and the integration of machine learning approaches with traditional control theory. His research group actively explores connections between theoretical developments and applications in the life sciences. Scientific Recognition: W.T. and Idalia Reid Prize 2021 SIAM Fellow (2017) European Research Council Advanced Grant (2015) Alwin Walther Medaille (2008) SIAM Outstanding Paper Prize (2006) Prof. Kunisch has made substantial contributions to the mathematical community through his editorial work, serving as editor for prestigious journals including SIAM Journal on Control and Optimization, SIAM Journal on Numerical Analysis, and the Journal of the European Mathematical Society. He leads the Research Group on Optimization and Optimal Control at the Johann Radon Institute for Computational and Applied Mathematics (RICAM) and is involved in the ERC-Project OCLOC "From Open to Closed Loop Control".

• Optimization
• Convex Analysis
• Nonlinear Analysis
• +۳ مورد دیگر

Radu Ioan Bot is a Professor and Dean of the Faculty of Mathematics at the University of Vienna, where he also serves as Head of the Department of Mathematics. His primary affiliations include the Department of Mathematics (Oskar-Morgenstern-Platz 1, 1090 Wien) and the Research Network Data Science (Währinger Straße 29, 1090 Wien). Bot's research centers on optimization theory with emphasis on convex/nonconvex optimization, monotone operators, and dynamical systems. He develops fast algorithms for variational inequalities and monotone inclusions by bridging continuous-time dynamics with discrete optimization methods. His work frequently addresses bilevel optimization, Tikhonov regularization, and second-order dynamics, yielding accelerated convergence rates for complex problems. Analysis of his 15 most recent publications (2023-2025) reveals dominant trends in time-scaling techniques, vanishing damping dynamics, and structured splitting methods. Key contributions include unifying Nesterov acceleration with Heavy Ball dynamics, developing reflected forward-backward algorithms for constrained optimization, and establishing strong convergence guarantees for monotone operator flows. These advances demonstrate consistent innovation in accelerating optimization while maintaining theoretical rigor. No scientific awards were mentioned in the provided source material. Details regarding student advising and research grants were not specified in the available information, though his leadership roles as Dean and Department Head indicate significant administrative responsibilities alongside active research. Bot participates in the University of Vienna's Research Network Data Science, suggesting interdisciplinary engagement in data-driven methodologies with potential applications in machine learning and computational mathematics.

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.

Markus Haltmeierمشاهده پروفایل

استاد

• Image Reconstruction
• Inverse Problems
• Deep Learning
• +۴ مورد دیگر

Markus Haltmeier is a Professor in the Department of Mathematics at the University of Innsbruck. His research focuses on inverse problems, image reconstruction, and deep learning with applications in medical imaging, photoacoustics, and computational mathematics. He leads a group dedicated to advancing theoretical and practical solutions for challenges in non-destructive testing and medical diagnostics. His work integrates mathematical analysis with machine learning, addressing issues such as high-resolution imaging in scattering media and automated segmentation of cardiac structures. Key research areas include regularization techniques for inverse problems, self-supervised learning approaches for limited data scenarios, and computational methods for photoacoustic tomography. His contributions span both theoretical developments (e.g., inversion formulas for Radon transforms) and applied solutions (e.g., algorithms for cylinder liner wear assessment and myocardial infarct segmentation). Publications highlight advancements in neural network-based regularization, 3D medical image synthesis, and unsupervised learning frameworks for segmentation and registration. His research emphasizes bridging the gap between mathematical theory and real-world applications in healthcare and engineering.

Jennifer Culbertsonمشاهده پروفایل

دانشیار

• Experimental linguistics
• Syntax
• Morphology
• +۴ مورد دیگر

Jennifer Culbertson is an Associate Professor at the University of Edinburgh, where she has been a faculty member since 2014 when she took up a Chancellor's Fellowship, later being promoted to Reader (equivalent to Associate Professor) in 2018. She is a founding member of the Centre for Language Evolution at Edinburgh and maintains an active research program in experimental linguistics and cognitive science. Dr. Culbertson obtained her PhD in Cognitive Science from Johns Hopkins University in 2010, with her dissertation receiving the Robert J. Glushko Prize for Outstanding Dissertations in Cognitive Science in 2011. Her primary research investigates how languages are shaped by learning and use, with particular focus on grammatical structures (like word order) and morphological categories (gender and person systems). She employs experimental and computational methods to explore how typological universals arise from properties of the human cognitive system. Her work bridges theoretical linguistics, cognitive science, and language evolution, examining the cognitive constraints that influence linguistic patterns across diverse languages and learning contexts. She frequently uses artificial language learning paradigms to isolate specific cognitive mechanisms underlying language structure. Analysis of her recent publications reveals a consistent focus on cognitive biases in linguistic structure, particularly in word order and morphological systems. Her research increasingly incorporates cross-population studies (including work with autistic learners) and developmental perspectives to understand how language patterns emerge across different populations and throughout the lifespan. She examines how simplicity principles, communicative efficiency, and statistical learning shape linguistic structure. Dr. Culbertson's scientific contributions have been recognized with several prestigious awards: Robert J. Glushko Prize for Outstanding Dissertations in Cognitive Science (2011) ERC Starting Grant Young Academy of Europe membership (2019) Her research has been supported by over €2 million in funding from the ESRC and ERC. While specific advisees aren't mentioned in the provided text, her active publication record with numerous co-authors suggests she mentors graduate students and early-career researchers. Her work has significant implications for understanding language universals, language acquisition, and the cognitive foundations of linguistic structure. As a founding member of the Centre for Language Evolution at Edinburgh, Dr. Culbertson collaborates with an interdisciplinary team investigating the biological, cognitive, and cultural foundations of human language. Her research often intersects with psychology, cognitive science, and computational linguistics, contributing to a comprehensive understanding of language as both a cognitive and social phenomenon.

Klemens Fellnerمشاهده پروفایل

استاد

• Partial Differential Equations
• Reaction-Diffusion Systems
• Kinetic Equations
• +۶ مورد دیگر

Klemens Fellner is a Professor of Mathematics/Computational Sciences and Group Leader of the Applied Analysis Group at the Institute of Mathematics and Scientific Computing, University of Graz. His research focuses on the analysis of partial differential equations and mathematical modeling across physics, chemistry, and biology. Research Interests: Prof. Fellner's work spans theoretical analysis of nonlinear PDEs (reaction-diffusion, kinetic, and non-local equations) using entropy/duality methods, with applications to: Biological systems (lipolysis, protein localization, stem-cell division) Physical processes (organic photovoltaics, semiconductor modeling) Collective behavior (swarming micro-organisms, aggregation dynamics) Interdisciplinary Mathematics-Arts collaborations Publication Trends: His recent articles (2018-2021) demonstrate strong focus on: Global existence and regularity for reaction-diffusion systems Convergence to equilibrium via entropy methods Drift-diffusion models in semiconductor physics Mathematical biology applications (prion dynamics, lipolysis) Novel approaches for non-local aggregation and hysteresis phenomena Research Leadership: Currently leads the Applied Analysis Group with members including postdocs and PhD students. Key projects: Doctoral School IGDK (International Graduate School) SFB Lipid Hydrolysis (Special Research Program) Mathematics and Arts collaborations Colibri research platform Supervises PhD candidate Reymart Lagunero studying generalized reaction-diffusion systems.

• hp-Finite Element Method (hp-FEM)
• Fractional Diffusion Equations
• Boundary Element Method (BEM)
• +۳ مورد دیگر

Prof. Jens Markus Melenk is a Professor at TU Wien's Faculty of Mathematics and Geoinformation, leading the Computational Mathematics Research Group (E101-02-1). His research focuses on advanced numerical methods for partial differential equations, with a strong emphasis on hp-FEM (hp-Finite Element Method), fractional diffusion equations, and wave propagation problems. He has contributed significantly to the development of robust and efficient algorithms for complex domains and heterogeneous media. Key research interests include the application of hp-FEM to fractional operators (e.g., integral fractional Laplacian), boundary element methods (BEM), and the analysis of wavenumber-explicit convergence for Maxwell's equations and elastic wave equations. His work bridges theoretical analysis and computational implementation, addressing challenges in multiscale problems and singular perturbations. Notable contributions: Exponential convergence of hp-FEM for fractional Laplacian problems, wavenumber-explicit error estimates for wave equations in heterogeneous media. Collaborations: Active involvement with researchers like Markus Faustmann, Christoph Schwab, and Dirk Praetorius. Supervised theses: Includes works on hp-FEM for fractional operators, RBF interpolation, and error estimators for elliptic PDEs. His research group develops and analyzes numerical schemes for challenging PDE scenarios, with applications in electromagnetism, acoustics, and computational mechanics.

• Archaeological prospection
• Geophysics
• Ground-penetrating radar
• +۶ مورد دیگر

Immo Trinks is Associate Professor (Privatdozent) at the University of Vienna and Head of the Vienna Institute for Archaeological Science . He coordinates a comprehensive teaching programme in archaeological prospection, archaeometry and scientific documentation, and leads large-scale geophysical projects across Europe. Education & qualifications: Dipl.-Geophys. (Diploma in Geophysics) PhD (awarded) Habilitation (Privatdozent, Austrian post-doctoral lecturing qualification) Research interests revolve around non-destructive mapping of buried archaeological landscapes . He specialises in ground-penetrating radar , magnetometry and multi-sensor robotic platforms , developing workflows that fuse high-resolution geophysical data with 3D archaeological interpretation. Coastal wetlands, Roman towns, Viking harbours and prehistoric pile dwellings serve as key study areas. Recent publications demonstrate a clear trend toward automated, large-coverage surveys and multi-method data fusion . Papers in 2022-2025 report motorised GPR arrays on snow-covered fields, semi-autonomous driverless systems, and integrated interpretation frameworks that combine magnetics, GPR and remote sensing to reveal Roman military compounds, Etruscan cities, Swedish war camps and Neolithic monumental landscapes. Scientific awards & honours: No specific awards are listed in the supplied text; however, his continuous funding and invited keynote contributions (e.g., ArchaeoProspection conference series) indicate international recognition. Teaching & student supervision: Regular courses: Introduction to Archaeological Prospection, Archaeometry, Magnetic Prospection, GPR Practical, Underwater Prospection, Human Evolution & Archaeological Science, LaTeX for Archaeologists Excursions: 2-day field schools at Alpine pile-dwelling sites and around Vienna Thesis seminars: continuous Master Thesis Topic Search & Exposé and final thesis colloquia every semester Labs & facilities: Trinks heads the Vienna Institute for Archaeological Science (VIAS), operating several motorized multi-channel GPR systems, high-resolution magnetometer arrays, electromagnetic induction sensors, underwater sonar and multi-spectral cameras. The institute maintains dedicated GIS/visualisation labs and field vehicles for pan-European surveys within the international ArchPro and Stonehenge Hidden Landscapes initiatives.

Lucrezia Reichlinمشاهده پروفایل

استاد

• Monetary Policy
• Applied Macroeconomics
• Econometrics (Time Series)
• +۳ مورد دیگر

Lucrezia Reichlin is a Professor of Economics at the London Business School , where her research bridges macroeconomic policy and advanced econometric techniques. She holds key advisory roles as a non-executive director for major financial institutions like UniCredit Banking Group and Eurobank Ergasias SA, and chairs the Scientific Council at the Brussels-based think-tank Bruegel . Previously, she served as Director General of Research at the European Central Bank (2005-2008) and held academic positions at the Université Libre de Bruxelles and Columbia University. Education: Ph.D. in Economics, New York University Reichlin is a pioneer in now-casting and high-dimensional time series analysis , developing econometric models to process real-time economic data. Her work has been adopted by central banks and private investors globally, focusing on monetary policy evaluation , business cycle dynamics , and forecasting methodologies . She co-founded the firm Now-Casting Economics Ltd in 2011 to commercialize these techniques. Scientific Awards & Honors: 2016 Birgit Grodal Award of the European Economic Association 2016 Isaac Kerstenetzky Scholarly Achievement Award International Economics Award, Chamber of Commerce of Genoa (2015) Grand Ufficiale dell'Ordine della Stella d'Italia (2015) Fellow, British Academy Fellow, European Economic Association Distinguished Fellow, CEPR As a columnist for Corriere della Sera and member of the Commission Economique de la Nation (France), she influences public and policy debates. She also founded the Ortygia Foundation , promoting female education in southern Italy. Her methodological innovations in dynamic factor models , Bayesian VARs , and shrinkage techniques have reshaped modern macroeconomic analysis.

Tom Henzingerمشاهده پروفایل

استاد

• Formal Methods
• Software Engineering
• Computer Science
• +۵ مورد دیگر

Tom Henzinger is a Professor at the Institute of Science and Technology Austria (ISTA), leading the Tom Henzinger Group. His research focuses on formal methods to enhance software quality, addressing challenges in concurrent systems, real-time and embedded systems, quantum computing, neural networks, and biochemical reaction networks. He has advised numerous PhD students and postdoctoral researchers, contributing to advancements in these fields. His work emphasizes mathematical rigor in software analysis and verification. Current projects include VAMOS (Middleware for best-effort third-party monitoring) and SPyCoDe (Semantic and Cryptographic Foundations of Security and Privacy by Compositional Design). Past projects involved model checking and runtime verification techniques. Research interests span concurrent software synthesis, quantitative modeling of reactive systems, predictability of real-time systems, and formal methods applied to quantum computation and neural networks. He is also engaged in exploring hardware-optimal solutions for quantum algorithms. Administrative Assistant Ksenja Harpprecht supports the group. Courses taught include 'Formalisms Every Computer Scientist Should Know,' focusing on logics, automata, and semantics. The group hosts regular seminars, such as the Tuesday group seminar and the Wednesday joint formal methods seminar with TU Wien's FORSYTE group.

• Mathematics
• Representation Theory
• Number Theory
• +۳ مورد دیگر

Dr. Alberto Mínguez Espallargas is a University Professor at the Faculty of Mathematics , affiliated with the Institute of Mathematics . His research focuses on representation theory of reductive groups over local fields, automorphic forms, and number theory, particularly exploring connections between geometric methods and categorification in p-adic groups. Key research areas: Representation Theory, Automorphic Forms, p-adic Groups Recent work: Co-tempered A-packets, congruences mod ℓ, geometric irreducibility Scientific Activities: Regular lecturer on advanced mathematical topics, active in international collaborations, and peer-reviewed journal contributor.

• Mathematical Analysis
• Partial Differential Equations
• Generalized Functions
• +۵ مورد دیگر

Günther Hörmann is an Associate Professor at the Faculty of Mathematics, Department of Mathematics, University of Vienna. With an academic career spanning from 1995 to present, he has established himself as a prominent researcher in mathematical analysis with particular expertise in generalized functions, microlocal analysis, and partial differential equations. His research interests span several interconnected areas of mathematical analysis and its applications: Generalized functions and Colombeau algebras Microlocal analysis and wavefront sets Partial differential equations, particularly wave equations Mathematical physics applications in quantum field theory Geophysical modeling and earth deformation Non-smooth geometry and regularization techniques Hörmann's scholarly output demonstrates a consistent focus on developing rigorous mathematical frameworks for analyzing differential equations with singular coefficients or data. His work often bridges pure mathematical theory with applications in physics, particularly in quantum mechanics, relativity, and geophysics. A distinctive feature of his research is the application of generalized function theory to problems that involve singularities or low regularity conditions. His publication record shows remarkable productivity across nearly three decades, with significant contributions in both theoretical mathematics and its applications. The interdisciplinary nature of his work is evident in collaborations across mathematics, physics, and even biomedical research as seen in his 2023 prostate cancer study.

Antonio M. Echavarrenمشاهده پروفایل

استاد

• Organic synthesis
• Organic chemistry
• Organometallic chemistry
• +۵ مورد دیگر

Antonio M. Echavarren is Professor of Organic Chemistry at Universidad Autónoma de Madrid and Research Professor at Consejo Superior de Investigaciones Científicas (CSIC). Since 2004, he has been Group Leader at the Institute of Chemical Research of Catalonia (ICIQ) in Tarragona, Spain. He is currently President of the Spanish Royal Society of Chemistry (RSEQ) and Scientific Director of the Severo Ochoa program (Excellence Accreditation, 2020-2023). Professor Echavarren received his PhD from Universidad Autónoma de Madrid in 1982, followed by postdoctoral research at Boston College and a NATO fellowship at Colorado State University. His academic career includes positions as Assistant Professor at UAM (1984-1986), Researcher at CSIC's Institute of Organic Chemistry (1988-1992), and Professor of Organic Chemistry at UAM (1992-present). His research focuses on developing novel synthetic methods using electrophilic metal complexes of gold and other transition metals. The group works on creating new strategies for constructing complex biologically active molecules and large polyarenes for material science applications. Their work centers on generating highly reactive gold species under ordinary conditions with potential applications in activating important molecules like methane. Professor Echavarren has authored over 295 scientific publications, including 26 in the Journal of the American Chemical Society and 41 in Angewandte Chemie International Edition. His recent work demonstrates expertise in gold catalysis, asymmetric synthesis, and the development of novel catalytic methods with applications in natural product synthesis and materials science. Scientific Awards: 2015 Arthur C. Cope Scholar Award, ACS 2013 and 2019 ERC Advanced Grants (CATGOLD and FOLDMETCAT) 2012 Fellow of the Royal Society of Chemistry 2010 Gold Medal of the Spanish Royal Society of Chemistry 2004 Janssen-Cilag Organic Chemistry Award Professor Echavarren has supervised 56 PhD students, 45 Master's students, and 63 postdoctoral associates. Currently, he oversees a research group of 15 PhD students, 6 postdoctoral researchers, and 2 Master's students. He serves on the editorial boards of several prestigious journals including Chem. Soc. Rev., Adv. Synth. Catal., and ChemCatChem, and was Associate Editor of Chem. Comm. from 2011-2020. The research group actively participates in outreach activities to promote chemical research awareness and maintains strong team cohesion through regular group-building events.

Aad van der Vaartمشاهده پروفایل

استاد

• High-dimensional statistics
• Nonparametric Bayesian statistics
• Statistical genetics
• +۵ مورد دیگر

Aad van der Vaart is a distinguished Professor of Statistics at Delft University of Technology (since 2021). Previously, he held Full Professorships at Leiden University (2012–2021) and Vrije Universiteit Amsterdam (1996–2012). His research focuses on foundational statistical theory and applications, including high-dimensional statistics, Bayesian methods, inverse problems, and genomics. He has made seminal contributions to nonparametric Bayesian inference, empirical processes, and semiparametric theory. Van der Vaart has authored influential textbooks such as Asymptotic Statistics (1998) and Fundamentals of Nonparametric Bayesian Inference (2017, with S. Ghosal). His work bridges theoretical rigor and practical applications, with over 34,830 citations (Google Scholar, 2023) and an H-index of 60. Key honors include the Spinoza Prize (2015, Netherlands’ highest science award), DeGroot Prize (2020), and membership in the Royal Netherlands Academy of Sciences. His academic journey includes roles such as Miller Fellow at UC Berkeley (2000), visiting positions at leading universities, and leadership in statistical societies. His research group actively explores modern challenges in statistical theory and methodology, including causal inference, adaptive estimation, and large-scale data analysis. Notable grants include an ERC Advanced Grant (2012) for Bayesian inverse problems. Collaborations span academia and industry, emphasizing interdisciplinary impact. While specific lab affiliations are not explicitly stated, his work is rooted in foundational mathematical statistics with broad applicability.

Benedikt Löweمشاهده پروفایل

استاد

• Foundations of mathematics
• Set theory
• Mathematical logic
• +۶ مورد دیگر

Dr. Benedikt Löwe is a Professor at the University of Hamburg since 2009, holding the CIPSH Chair 'Diversity of Mathematical Research Cultures & Practices'. He maintains affiliations with the Universiteit van Amsterdam (2003–2023) and the University of Cambridge (since 2012). His roles include research group leadership at Hamburg, editorial leadership at 'Mathematical Logic Quarterly', and governance positions in international academic organizations. Education : Master's in Mathematics (Tübingen, 1996), PhD in Mathematics (Berlin, 2001), Habilitation (Bonn, 2004), M.A. and Sc.D. from Cambridge His research bridges mathematical logic with philosophy, narratology, AI, and social sciences, with a focus on foundational questions and interdisciplinary modeling. His work has pioneered algebra-valued set theory, modal logic of forcing, and empirical approaches to modeling mathematical practices. Key contributions include the concept of 'quasigenerics' in set theory, the development of paraconsistent algebra-valued models, and the application of logic to folktale morphology. He has edited multiple journals and served on editorial boards, including as Managing Editor of 'Mathematical Logic Quarterly' (2011–2022). Scientific Awards : Fellow of the International Science Council (2023) Ordinary member of the Hamburg Academy of Sciences (2023) Simons Foundation Research Fellowship (2015) Felix-Hausdorff-Gedächtnispreis (2001) As a leader in academic governance, he has chaired the Deutsche Vereinigung für Mathematische Logik (DVMLG) and served as Secretary General of the International Union of History and Philosophy of Science and Technology's logic division (DLMPST/IUHPST).