جستجوی استاد راهنمای دانشگاهی

Yoann Le Hénaff is a postdoctoral researcher at the Numerical Analysis Department of the University of Tübingen, Germany. He works within the CRC TRR 352's B4 project and collaborates with C. Lubich's group. His research focuses on computational mathematics and physical modeling through numerical analysis. Education: PhD in Mathematics (2024), University of Rennes, France Master's degree in Mathematics, University of Rennes, France Engineering degree in applied mathematics, INSA Rennes, France Research Interests: Specializing in partial differential equations and numerical simulations, Le Hénaff develops grid-free particle methods for the Vlasov-Poisson system and studies modulated soliton solutions for nonlinear Schrödinger equations. Key subfields include spectral concentration problems, Dirac-Frenkel variational principles, and computational complexity optimization. Publication Trends: Recent work demonstrates expertise in hybrid numerical methods combining classical PDE approaches with modern computational techniques. 2023-2025 publications show progression from particle method convergence proofs to advanced soliton-based algorithms and spectral concentration generalizations across multiple dimensions. Collaborations: Actively involved in the CRC TRR 352 consortium, participating in annual retreats and contributing to the B4 project's objectives. Regularly presents at international seminars including the NAG seminar in Tübingen and IRMAR doctoral meetings in Rennes.

• Numerical analysis
• Mathematical physics
• Partial differential equations
• +۲ مورد دیگر

Gianluca Ceruti is a researcher at the Mathematical Institute of Eberhard Karls University of Tübingen. His work focuses on numerical analysis and scientific computing, particularly in dynamical low-rank approximation and tensor networks. He is involved in projects related to wave phenomena and quantum system dynamics. Research Interests: Dynamical low-rank approximation, tensor networks, uncertainty quantification, and numerical methods for differential equations. Key Collaborations: Jonas Kusch, Christian Lubich, Lukas Einkemmer, Martin Frank. His recent publications address stability analysis, rank-adaptive integrators, and time integration of tree tensor networks. Contact: ceruti@na.uni-tuebingen.de .

• Dynamical Low-Rank Approximation
• Numerical Analysis
• Scientific Computing
• +۳ مورد دیگر

Dr. Zhixiang Chen is a Lecturer in Machine Learning at the Department of Computer Science, University of Sheffield, and an active member of both the Machine Learning and Computer Vision research groups. Previously, he held postdoctoral positions at Imperial College London and Tsinghua University. Education: PhD in Computer Science, Tsinghua University, China B.Eng. in Computer Engineering, Xi'an Jiaotong University, China His research focuses on advancing Computer Vision and Machine Learning through human analysis, object detection, and image retrieval systems. Recent work integrates deep learning for industrial applications like PCB inspection and autonomous systems, while earlier contributions pioneered video hashing techniques for efficient multimedia search. His methodology emphasizes robust feature representation and scalable algorithm design. Publication trends reveal a strategic shift from foundational hashing research (2016-2019) toward applied 3D vision and industrial automation (2020-2024), with increasing emphasis on uncertainty-aware models and sensor fusion for real-world deployment. Scientific Awards: China Society of Image and Graphics Doctoral Dissertation Award (2019) IEEE International Conference on Multimedia and Expo Best Paper Award (2018) China National Postdoctoral Program for Innovative Talents (2017) Dr. Chen currently leads the EPSRC-funded project 'VIM: towards a Vision based System for Inventory Management with Deep Learning' (2024-2026, £46,354) as Principal Investigator. He serves as a Grant Reviewer for UKRI-FLF and NSFC, Senior Program Committee Member for AAAI 2023, and regularly reviews for top-tier conferences (CVPR, ICCV, NeurIPS) and journals (IEEE T-PAMI, IEEE T-MM). As a core member of Sheffield's Machine Learning and Computer Vision research groups, he contributes to collaborative projects involving industrial partners and interdisciplinary teams focused on AI-driven solutions for healthcare, manufacturing, and autonomous systems.

• Computer Vision
• Machine Learning
• Human Analysis
• +۲ مورد دیگر

Salvatore Angelo Marano is a Full Professor of Mathematical Analysis at the University of Catania, affiliated with the Department of Mathematics and Computer Science since 2001. He graduated in Mathematics from the University of Catania in 1987 and has authored approximately 100 research papers in international mathematics journals. His research spans: Differential equations/inclusions and fixed point theory Critical point theory for non-smooth functions on convex sets Elliptic boundary value problems (Dirichlet, Neumann, Robin) p-Laplacian and (p,q)-Laplacian equations Fractional operators and Sobolev embeddings Variational-hemivariational inequalities Recent publications (2019-2025) focus on singular systems, fractional operators, quasilinear convection problems, and multi-solution phenomena in nonlinear PDEs. His work consistently employs variational methods, truncation techniques, and critical point theory. Awards include: Foundation 'Francesco Severi' Prize (1991) Gioenia Academy Young Researcher Prize (1989) He collaborates internationally with researchers in Poland, Portugal, France, Greece, USA, and Algeria, and serves on editorial boards of journals including Nonlinear Analysis: Real World Applications and Discussiones Mathematicae .

• Mathematical Analysis
• Differential Equations
• Partial Differential Inclusions
• +۶ مورد دیگر

Rita Tracinà is an Associate Professor of Mathematical Physics at the University of Catania , affiliated with the Faculty of Engineering and the Department of Mathematics and Computer Science . She is a member of the National Group for Mathematical Physics (GNFM) of the CNR (INDAM). Educational Qualifications : Bachelor’s, Master’s, and Doctorate in Mathematics. Positions Held : Associate Professor (2018–present), Permanent Researcher (2005–2018), Contract Lecturer in Mathematical Analysis (2001/02–2003/04). Her research focuses on equivalence transformations, differential invariants, symmetry classifications, exact solutions of PDEs, hyperbolic systems, nonlinear wave propagation, reaction-diffusion systems, semiconductor models, and conservation laws. She has organized multiple international symposia on symmetry methods at the International Conference of Numerical Analysis and Applied Mathematics. Scientific Contributions : Guest editor for special issues in Abstract and Applied Analysis , Advances in Mathematical Physics , Symmetry , and Mathematical Biosciences and Engineering . Teaching : Rational Mechanics and Mathematical Analysis at the Faculty of Engineering, with past courses in Applied Mathematics and Mathematical Physics. Collaborations : Referee for journals including Advances in Mathematical Physics , Chaos, Solitons & Fractals , and Nonlinear Analysis: Real World Applications .

• Mathematical Physics
• Equivalence Transformations
• Differential Invariants
• +۷ مورد دیگر

Carmen Perugia is an Associate Professor in the Department of Science and Technology (DST) at the University of Sannio . Her academic career spans both Mathematical Analysis and Earth Sciences , with a focus on homogenization , control theory , and paleoclimatic reconstruction using coccolithophore assemblages . Teaching: Mathematics and Computer Science for Biology, Geology, and Biotechnology students. Research: Combines partial differential equations with marine paleoceanography , linking mathematical modeling to climate change analysis. Publication Trends reveal dual expertise: 1) mathematical analysis of degenerate elliptic equations , Bingham flows , and Ginzburg-Landau models , and 2) paleoclimatic studies using coccolithophore proxies to analyze North Atlantic and Mediterranean Sea dynamics over the last 30 ka. Her homogenization research addresses imperfect interfaces and oscillating boundaries , while her control theory work derives observability inequalities for hyperbolic equations . Collaborations include international researchers from Finland , Germany , India , and Portugal . Her teaching emphasizes mathematical foundations for biological and geological applications , with office hours by appointment on Tuesdays and Thursdays .

• Mathematical Analysis
• Applied Mathematics
• Homogenization
• +۴ مورد دیگر

Prof. Dr. Nicolas R. Gauger is Full Professor and Chairholder for Scientific Computing at the University of Kaiserslautern-Landau (RPTU), holding dual appointments in the Department of Mathematics and Department of Computer Science. He directs the university's Computing Center (RHRZ) and leads the SciComp research team, with prior roles at DLR Braunschweig, Humboldt University Berlin, RWTH Aachen University, and MIT. His academic background includes a Master in Mathematics (Dipl.-Math.) from Leibniz University Hannover (1998) and a Ph.D. in Applied Mathematics (Dr.rer.nat.) from Braunschweig University of Technology (2003). 1998-2010: Research Scientist, Numerical Methods for Aerodynamics at DLR Braunschweig 2005-2010: Assistant Professor (W1), Department of Mathematics, Humboldt University Berlin 2010-2014: Associate Professor (W2), RWTH Aachen University 2014: Visiting Professor, Massachusetts Institute of Technology Prof. Gauger's research centers on optimization under uncertainty for complex physical systems. His work integrates Algorithmic Differentiation with Machine Learning to advance Computational Fluid Dynamics, Aeroacoustics, and Structural Mechanics. Recent projects focus on medical applications like proton computed tomography (pCT) for cancer treatment through SIVERT and AI Care initiatives, alongside aerodynamic design for noise reduction and flow control. His 2025 publications reveal a dominant trend in end-to-end differentiable programming for physics-based optimization, particularly in fundamental particle physics experiments and medical imaging. Key subfields include diffusion models for detector design, reinforcement learning for particle tracking, and robust optimization frameworks applied to turbulence modeling and proton therapy. Scientific recognition includes: Associate Fellow of the American Institute of Aeronautics and Astronautics (AIAA), 2018 Teaching Award from RPTU, June 2025 He has advised doctoral students including award-winning researcher Max Aehle (2025 Freundeskreis RPTU Outstanding Dissertation Award). Major grants include leadership of the Excellence Initiative-funded AICES Graduate School (2010-2019), the Center for Mathematical and Computational Modelling (CM) 2 (2014-2019), and the MathApp (2019-2024) and MSO (2024-present) research initiatives. Current projects like SIVERT and AI Care apply AI to cancer therapy. Prof. Gauger co-leads the Fraunhofer Performance Center's R&D Lab for Data Analysis and AI, serves on the Managing Board of ERCOFTAC (European Research Community on Flow, Turbulence and Combustion), and chairs the Steering Committee of ERCOFTAC's Special Interest Group on Design Optimization. His team develops critical AD tools including CoDiPack and OpDiLib within the NHR South-West high-performance computing consortium.

• Nonlinear Optimization
• Numerical Optimization
• Optimization and Control with PDEs
• +۱۲ مورد دیگر

Professor Wolfgang Schief is a faculty member at the University of New South Wales (UNSW), affiliated with the School of Mathematics & Statistics . His research bridges integrable systems , nonlinear physics , and geometric analysis , with a focus on differential and discrete differential geometry and their applications in continuum mechanics , general relativity , and soliton theory . Research Interests His work centers on the interplay between integrable systems and geometric structures , particularly in nonlinear partial differential equations and their discrete analogs. Key areas include: Integrable discretizations of classical and modern geometric problems Backlund and Darboux transformations for physical systems Nonlinear elasticity and magnetohydrodynamics Self-dual Einstein spaces and heavenly equations Log-aesthetic curves and geometric design Recent Publications Recent studies highlight multi-dimensional integrability in affine manifolds, canonical reductions of TED equations, and geometric frameworks for fiber-reinforced fluids and relativistic systems. His work often reveals connections between soliton theory , Lagrangian mechanics , and discrete geometry . Scientific Awards Queen Elizabeth II Research Fellow (UNSW, 1999–2004) Academic Leadership Currently Professor at UNSW (since 2010), Schief has held roles including Senior Lecturer , Associate Professor (2005–2006), and Professor at TU Berlin (2006–2010). His career spans 2+1-dimensional integrable systems and geometric applications in physics and mechanics.

• Integrable Systems
• Soliton Theory
• Differential Geometry
• +۱۱ مورد دیگر

Shrish Parmeshwar is a Research Fellow at CY Cergy Paris University , focusing on Nonlinear PDEs and Mathematical Fluid Mechanics . He works under the supervision of Prof. Philippe Gravejat , with prior postdoctoral experience at Imperial College London , University of Warwick , and University of Bath (under Prof. Monica Musso ). His doctoral research at King’s College London was advised by Prof. Mahir Hadžić and centered on compressible fluid dynamics and singularity formation in PDEs. His research program explores Free Boundary Problems , Vortex Dynamics , and Singular Limits in fluid mechanics, particularly through collaborations with experts like Juan Dávila , Manuel del Pino , and Monica Musso . Recent publications in J. Differential Equations and Quart. Appl. Math. analyze self-similar vortex configurations and global existence criteria for nonlinear systems. As an educator, he has served as a Tutor for advanced mathematics courses at University of Bath (Vector Calculus, Analysis 2A) and King’s College London (Fourier Analysis, PDEs and Complex Variables). His teaching emphasizes analytical methods and their applications to fluid dynamics.

• Nonlinear PDEs
• Mathematical Fluid Mechanics
• Free Boundary Problems
• +۲ مورد دیگر

Andreas Paul Eberhard Kloeckner is an Associate Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign (UIUC), where he has been serving since 2013 (promoted to Associate Professor in 2019). He also holds an affiliate faculty appointment in the Department of Electrical and Computer Engineering since 2016. His academic journey includes a PhD in Applied Mathematics from Brown University (2010), an MSc from Brown University (2006), and a Diplom in Applied Mathematics from Universität Karlsruhe (2005). Prior to joining UIUC, he was a Courant Instructor at the Courant Institute of Mathematical Sciences at New York University. Dr. Kloeckner's research focuses on high-order accurate integral equation methods, fast algorithms for elliptic boundary value problems, and code transformation for high-performance scientific computing. His work bridges mathematical theory with practical implementation, with particular emphasis on GPU computing and parallel architectures. He has made significant contributions to the development of open-source scientific software, most notably PyCUDA and PyOpenCL, which have become widely used tools in the scientific computing community. His publication record shows a consistent focus on advancing numerical methods for scientific computing, with recent work emphasizing code generation techniques, fast integral equation solvers, and optimization of algorithms for modern hardware architectures. The trajectory of his publications reveals a progression from foundational work on GPU-based discontinuous Galerkin methods toward increasingly sophisticated approaches for integral equation methods and automatic code generation. Among his notable recognitions is the 2017 National Science Foundation CAREER Award, which supports his work on general-purpose, high-order integral equation methods for computer simulation in engineering. His research has been published in prestigious venues including SIAM Journal on Scientific Computing and has influenced both academic research and practical applications in scientific computing. Dr. Kloeckner has advised numerous graduate students through completion of their PhD and MS degrees, with alumni moving to positions at Apple, NVIDIA, Rice University, and other leading institutions. His research group maintains an active portfolio of open-source software projects that advance the state of scientific computing infrastructure.

• Scientific Computing
• Parallel Computing
• Numerical Techniques
• +۷ مورد دیگر

Julie Valein is a Lecturer at the University of Lorraine, affiliated with Polytech Nancy and the Institut Élie Cartan de Lorraine (IECL). She serves as an HDR (Habilitation à Diriger des Recherches) lecturer and is an active member of the SPHINX project team at Inria Nancy-Grand Est under Takéo Takahashi. Education 2020: Accreditation to Direct Research (HDR) from University of Lorraine 2008: Doctorate in Applied Mathematics from University of Valenciennes and Hainaut-Cambrésis (supervised by Serge Nicaise) 2004: Mathematics Aggregation Research Focus Her work centers on control theory , stabilization , and inverse problems for partial differential equations, with specialized expertise in systems placed on networks and those incorporating time delays. She develops theoretical frameworks for stability analysis and constructs numerical algorithms for observer design and control implementation. Her research bridges abstract mathematical analysis with practical engineering applications, particularly in networked PDE systems where discontinuous coefficients or complex topologies pose significant challenges. Publication Trends Analysis of her 2019-2025 publications reveals three dominant research threads: (1) Stability and control of KdV equations on networks with time delays, (2) Carleman estimate applications for inverse problems and observers in wave/heat equations, and (3) Numerical stabilization techniques for parabolic systems with input delays. Her work consistently integrates theoretical proofs with computational validation, demonstrating growing emphasis on time-varying delay systems and network topologies since 2020. Research Leadership Valein actively contributes to major collaborative projects including ANR TRECOS (2020-2024), MATH-AmSud SCIPinPDEs (2023-2024), and COST Action Mat-Dyn-Net. She previously participated in ANR ISDEEC, ODISSE, and MATH-AmSud ACIPDE. As co-responsible for the IECL EDP seminar (2018-2022) and member of CNU 26 since 2023, she shapes research discourse in her field. Academic Service Elected member of UL AM2I scientific center council (2022-present) Educational manager of PIVE at Polytech Nancy (2019-present) Member of IECL parity committee (2023-present) Former head of Polytech Nancy mathematics department (2010-2017) Former member of Polytech Nancy Board of Directors (2013-2021) Teaching Profile She designs and delivers advanced mathematics courses including analysis for 1A students and digital analysis for 3A work-study engineers. Her citizen project tutoring at A. Camus college demonstrates commitment to educational outreach. Current responsibilities include optimization courses for work-study students and mathematics refresher programs.

• Partial Differential Equations
• Control Theory
• Stabilization
• +۳ 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

Corban Harwood is a Professor of Mathematics and Chair of the Department of Mathematics at George Fox University. He teaches courses such as Calculus, Differential Equations, Numerical Methods, and Advanced Linear Algebra, integrating his research on numerical partial differential equations into pedagogy. His research focuses on developing and analyzing numerically stable algorithms for solving nonlinear and parabolic partial differential equations, with applications in chemical reaction-diffusion, wave propagation, and environmental modeling (e.g., algal blooms, disease spread). His work emphasizes minimizing computational errors and time while ensuring solution reliability. Key trends in his publications include interdisciplinary applications of mathematics, algorithm stability analysis, and pedagogical frameworks for project-based learning. He has also collaborated on models for battery design and ecological systems.

• Numerical Partial Differential Equations
• Mathematical Modeling
• Applied Mathematics
• +۵ مورد دیگر

Ronny Bergmann is an Associate Professor (Førsteamanuensis) at the Department of Mathematical Sciences at the Norwegian University of Science and Technology (NTNU) in Trondheim, Norway, where he has been employed since March 2021. Previously, he served as a postdoctoral researcher and deputy head of the Numerical Analysis of Partial Differential Equations group at Chemnitz University of Technology, Germany, and earlier worked within the Image Processing Group at Kaiserslautern University of Technology where he completed his habilitation in early 2018. His doctoral research was conducted at the University of Lübeck under supervision of Jürgen Prestin. Bergmann's research primarily focuses on nonsmooth optimization on manifolds , with particular emphasis on proximal methods and their applications in manifold-valued image processing. His work extends to optimization methods on manifolds and high-dimensional power manifolds, graph-based approaches for manifold-valued data processing that combine local and nonlocal methods, and anisotropic periodic translation invariant spaces with Fourier-based algorithms. His research bridges theoretical mathematics with practical computational applications in image processing and data analysis. His recent publications demonstrate significant contributions to manifold optimization theory and applications, with a strong emphasis on developing computationally efficient algorithms for manifold-valued data. The publications span topics including Riemannian proximal gradient methods, Newton's methods on manifolds, total variation techniques for mesh processing, and geometric approaches to Kalman filtering. His work often involves developing practical implementations, such as the Manopt.jl and Manifolds.jl packages in Julia, which have demonstrated substantial performance improvements over existing tools. Bergmann's research has been published in top-tier journals including SIAM Journal on Scientific Computing, Journal of Optimization Theory and Applications, and SIAM Journal on Optimization, reflecting the high quality and impact of his contributions to the field of manifold optimization and its applications. As both a theoretical mathematician and computational scientist, Bergmann has made significant contributions to advancing the state-of-the-art in optimization on manifolds, particularly in developing methods that maintain intrinsic geometric properties while achieving computational efficiency. His work has applications across multiple domains including image processing, computer graphics, robotics, and data science.

• Nonsmooth Optimization on Manifolds
• Proximal Methods
• Manifold-Valued Image Processing
• +۷ مورد دیگر

Mark Gockenbach serves as Professor and Department Chair of the Department of Mathematical Sciences within the College of Arts & Sciences at the University of Delaware. He joined UD in 2020 after spending 21 years at Michigan Technological University, where he served as department chair for the final 14 years of his tenure. His academic career demonstrates a strong commitment to both administrative leadership and scholarly research in mathematical sciences. Professor Gockenbach's research primarily focuses on numerical analysis with special emphasis on inverse problems. His scholarly work spans singular value expansions, Tikhonov regularization techniques, elastography inverse problems, and numerical methods for partial differential equations. His publication record shows consistent productivity from 2010 through 2020, with particular concentration on mathematical approaches to inverse problems with applications in medical imaging and elasticity. His work bridges theoretical mathematics with practical applications in scientific computing and medical diagnostics. The analysis of his recent publications reveals a strong thematic focus on developing and analyzing numerical methods for solving inverse problems. His work frequently addresses stability issues, error estimation, and parameter selection in regularization techniques. The research shows progression from theoretical foundations of singular value decompositions to practical applications in medical imaging, particularly in tumor identification through elastography techniques. His scholarly output demonstrates both depth in mathematical theory and relevance to real-world applications. While specific awards are not mentioned in the available information, Professor Gockenbach's sustained research productivity and leadership roles indicate significant professional recognition. His extensive publication record in reputable journals reflects standing within the mathematical community. As Department Chair, Professor Gockenbach oversees all departmental operations while maintaining his research program. Though his administrative duties have reduced his teaching load, he previously taught a wide range of courses including calculus, linear algebra, differential equations, complex variables, and numerical methods for partial differential equations. His textbook publications suggest a strong commitment to mathematical education alongside his research activities.

• Numerical Analysis
• Inverse Problems
• Partial Differential Equations
• +۳ مورد دیگر