Spectral element methods Professors and Supervisors | ApplySharif

جست‌وجوی استاد و پژوهشگر

استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشی‌تان را پیدا کنید و با او ارتباط بگیرید.

نمایش ۶۷۶-۶۹۰ از ۷۴۰ استاد راهنما

اطلاعات این پروفایل‌ها از صفحات عمومی دانشگاه‌ها جمع‌آوری شده و ممکن است به‌روز نباشد.

Matthew Gieslerمشاهده پروفایل

پژوهشگر

California Institute of Technology (Caltech)United States

Matthew Giesler is a postdoctoral scholar in the TAPIR group at the California Institute of Technology (Caltech), specializing in computational and theoretical astrophysics. His research focuses on numerical relativity, particularly using the Spectral Einstein Code (SpEC) as part of the Simulating eXtreme Spacetimes (SXS) collaboration to study black holes and gravitational waves. He contributes to large-scale simulations of binary black hole mergers and neutron star collisions, emphasizing high-precision modeling and waveform analysis. His work involves advancing numerical methods like discontinuous Galerkin techniques and investigating topics such as black hole ringdown overtones, small mass-ratio corrections, and gravitational wave parameter estimation. Giesler collaborates extensively with international teams including LIGO, Virgo, and KAGRA to analyze observational data from gravitational wave detectors. Key projects include the SXS Collaboration's catalogs of binary black hole simulations and studies of extreme mass ratio systems. His research bridges theoretical predictions with observational data, contributing to tests of general relativity and cosmological parameter constraints. Despite no listed formal awards, his contributions to gravitational wave astronomy are highlighted through high-impact publications and collaborative efforts in multi-messenger astrophysics. His work supports the development of SpECTRE, a multi-physics simulation framework, and informs future gravitational wave detectors' data analysis methods.

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Martin Hallaمشاهده پروفایل

استادیار

Karlsruhe Institute of TechnologyGermany

Dr. Martin Halla is a Junior Research Group Leader at the Karlsruhe Institute of Technology (KIT), specifically within the Institute for Applied and Numerical Mathematics, which operates under the Department of Mathematics. He assumed this faculty position in 2025 after completing several prestigious postdoctoral appointments. Dr. Halla completed his PhD at TU Wien in 2019 with the exceptional honor of "Promotio sub auspiciis Praesidentis rei publicae" in 2021, a distinction reserved for outstanding doctoral achievements in Austria. His academic path included postdoctoral positions at RICAM (2024-2025), University of Göttingen (2022-2024, 2020-2021), and the Max Planck Institute for Solar System Research in Göttingen (2021-2022, 2019-2020). His research focuses on advanced mathematical techniques for wave phenomena across multiple physical domains. He specializes in the analysis and numerical methods for partial differential equations, with particular expertise in wave propagation (acoustics, elasticity, electromagnetism, plasmonics, meta materials, stellar oscillations), eigenvalue problems (holomorphic, non-selfadjoint), transparent boundary conditions (perfectly matched layers, infinite elements), compatible discretizations (T-coercivity), and target signatures in inverse scattering. His work bridges theoretical mathematical analysis with practical computational methods. Dr. Halla's recent publications reveal a strong emphasis on developing robust numerical frameworks for complex wave phenomena, particularly addressing challenges with sign-changing coefficients, anisotropic media, and dispersive materials. His research shows a consistent trajectory toward creating innovative solutions for previously intractable wave propagation problems. DFG Sonderforschungsbereich 1173 "Wave Phenomena: Analysis and Numerics" (2025-present) DFG Emmy-Noether Project "T-coercivity and Target Signatures in Computational Wave Propagation" (2025-present) DFG Sachbeihilfe Project on "Analysis of eigenvalue problems arising in qualitative methods for inverse scattering" (2022-2024) Dr. Halla actively contributes to the academic community through organizing conferences and workshops, including a minisymposium at the Conference on Mathematics of Wave Phenomena (2025), the Spring School on "Novel Imaging Techniques with Waves" (2024), and serving on the organizing committee for the 11th Applied Inverse Problems Conference (2023).

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Tobias Jahnkeمشاهده پروفایل

استاد

Karlsruhe Institute of TechnologyGermany

Prof. Dr. Tobias Jahnke is a faculty member at the Karlsruhe Institute of Technology (KIT) in the Faculty of Mathematics , affiliated with the Institute for Applied and Numerical Mathematics and Research Group 3: Scientific Computing . His office is located at Kollegiengebäude Mathematik (20.30), Room 3.042 , and he offers individual appointments via email at tobias.jahnke@kit.edu . His research focuses on Numerical Analysis and Scientific Computing , particularly for highly oscillatory differential equations , partial differential equations , and stochastic reaction systems . Recent work includes methods for nonlinear Dirac equations , Maxwell equations in heterogeneous media , and dispersion-managed optical systems . Courses taught cover Mathematical Finance , Splitting Methods , and Wavelet Applications . Recent publications emphasize error bounds , high-frequency wave propagation , and ADI schemes . Collaborations include projects on frequency combs and quantum dynamics . He leads seminars and lectures on Scientific Computing , Numerical Methods , and Wavelet Analysis .

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Andreas Kirschمشاهده پروفایل

استاد

Karlsruhe Institute of TechnologyGermany

Professor Andreas Kirsch is a faculty member at the Karlsruhe Institute of Technology (KIT) , affiliated with the Department of Mathematics and the Institute for Applied and Numerical Mathematics . He leads research in Inverse Problems and Scattering Theory , focusing on Time-Harmonic Waves , Maxwell's Equations , and Numerical Methods for solving direct and inverse scattering problems. Research Interests : Inverse Problems, Scattering Theory, Numerical Analysis, Partial Differential Equations, Electromagnetic Theory, Wave Propagation, Computational Physics. His recent publications highlight advancements in time-harmonic scattering for periodic and anisotropic structures, Maxwell's equations in waveguides, and radiation/absorption principles for modeling wave propagation. Collaborative work includes contributions to seismology , viscoelasticity , and electromagnetic chirality with colleagues like G. Hu, B. Schweizer, and A. Rieder. He is associated with the KIT's Research Group 4: Inverse Problems , which develops computational techniques for applications in acoustics , electromagnetics , and seismic tomography . His extensive publications include monographs on the Factorization Method and Mathematical Theory of Inverse Problems , establishing him as a leading expert in these domains.

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Jennifer Pestanaمشاهده پروفایل

مدرس ارشد

University of StrathclydeUnited Kingdom

Dr Jennifer Pestana is a Senior Lecturer in the Department of Mathematics and Statistics at the University of Strathclyde, Faculty of Science. She has been a faculty member since 2015 and is actively involved in research and academic leadership. She is a principal investigator on multiple grants and serves as an editor for SIAM publications. Education: DPhil, University of Oxford, 2012 Postdoctoral positions: University of Manchester, University of Oxford Her research centers on numerical linear algebra and its applications in scientific computing . She investigates the convergence of Krylov subspace methods , develops preconditioners for specific applications, and explores the use of tropical algebra for matrix pre-scaling. Current projects involve fast solvers for fractional diffusion and analysis in broadband signal processing . Her work bridges theoretical numerical analysis with practical computational challenges. The recent publications reflect a strong focus on iterative methods, matrix analysis, and signal processing. Common themes include Toeplitz matrices , eigenvalue decomposition , preconditioning , and covariance estimation , demonstrating her expertise in both algorithmic development and application-driven numerical methods. Scientific Awards: Best Student Paper Award (2018) Dr Pestana actively supervises students and leads research projects, including EPSRC-SFI and Strathclyde ISP Joint PhD initiatives. She has secured significant funding for work on Krylov methods and efficient solvers. Her professional service includes organizing major conferences such as the Biennial Conference on Numerical Analysis and serving on program committees, including for the International Linear Algebra Society. She is also an invited speaker and visiting researcher, demonstrating national and international recognition. She is involved with research teams focused on numerical analysis and scientific computing, contributing to collaborative efforts in developing novel preconditioned iterative solvers. Her lab and project groups work on both theoretical and applied aspects of linear algebra in PDEs and signal processing.

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Florentina Toneمشاهده پروفایل

استاد

University of West FloridaUnited States

Dr. Florentina Tone is a Professor in the Department of Mathematics and Statistics at the University of West Florida, part of the Hal Marcus College of Science and Engineering. She has been a faculty member since 2006, contributing to both undergraduate and graduate education through classroom and online instruction. Her academic background includes a Ph.D. in Mathematics from Indiana University and both a Master’s and Bachelor’s degree in Mathematics from the University of Bucharest, Romania. Dr. Tone's research is centered on numerical analysis of partial differential equations , with a focus on convergence, stability, and error estimation of numerical schemes. Her work applies to fluid dynamics, phase field models, and coupled physical systems. She has published in leading journals such as SIAM Journal on Numerical Analysis and Numerische Mathematik , and has presented at numerous national and international conferences. The analysis of her recent publications reveals a consistent focus on rigorous mathematical validation of numerical methods, particularly finite element and finite difference schemes for time-dependent PDEs. Her work spans applications in fluid mechanics, heat transfer, chemotaxis, and electromagnetics, demonstrating strong interdisciplinary reach within applied mathematics. She has been recognized for her contributions with the Distinguished Research and Creative Activities Award from UWF. This honor reflects her sustained excellence in scholarly output. Dr. Tone actively supervises student research projects and teaches courses such as Complex Analysis, Numerical Analysis, Linear Algebra, and Calculus. While specific grant details are not listed, her sustained publication record and award suggest active research funding. She has mentored students through research advising, contributing to academic development within the department. She is affiliated with the Department of Mathematics and Statistics, which supports research through seminars, colloquia, and student associations such as the Math Association. The department also hosts technical reports and research labs, including the CSDA Lab, which may support data-intensive computational work.

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Jia Liuمشاهده پروفایل

استاد

University of West FloridaUnited States

Dr. Jia Liu is a Professor and Chair of the Department of Mathematics and Statistics at the University of West Florida, within the Hal Marcus College of Science and Engineering. She has been a key academic figure at UWF since 2006, leading both research and departmental initiatives in computational and applied mathematics. Her educational background includes a Ph.D. in Mathematics from Emory University, funded by the National Science Foundation, focusing on preconditioned Krylov subspace methods for incompressible flow problems. She earned her M.S. and B.A. in Mathematics from Central China Normal University, where her bachelor's thesis received the highest honor. Dr. Liu's research lies at the intersection of numerical linear algebra, scientific computing, and interdisciplinary applications. Her primary interests include: Numerical solvers for large sparse linear systems Krylov subspace iterative methods Preconditioning techniques Applications to Navier-Stokes and optimization problems Geometric and topological analysis of ellipsoids Complex networks and community detection via spectral clustering Machine learning for disease prediction and biological modeling The trends in her publications reflect a consistent focus on robust numerical algorithms with applications across fluid dynamics, network science, and biomedical modeling. Her work emphasizes both theoretical development and practical implementation in high-performance computing environments. Dr. Liu has served as an editor and editorial board member for several peer-reviewed journals and regularly reviews submissions. While specific awards are not listed, her sustained publication record in prestigious venues such as SIAM Journal on Scientific Computing and Journal of Biological Dynamics underscores her scholarly impact. As department chair and professor, she plays a central role in academic advising, curriculum development, and research mentorship. She teaches core courses including Differential Equations, Numerical Analysis, and Real Analysis, contributing significantly to both undergraduate and graduate education. Her leadership extends to managing research grants and fostering collaborations across disciplines. Though no formal lab name is mentioned, her research activities suggest involvement with computational modeling groups, likely associated with applied mathematics and data science initiatives at UWF. Her ongoing work continues to advance numerical methods for complex systems in science and engineering.

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Akil Narayanمشاهده پروفایل

استاد

University of UtahUnited States

Akil Narayan is a Professor in the Department of Mathematics and a member of the Scientific Computing and Imaging (SCI) Institute at the University of Utah. His office is located in WEB 4666 (SCI) and LCB 116 (Math). He has previously held positions as Assistant Professor at the University of Massachusetts Dartmouth (2012-2015) and Visiting Assistant Professor at Purdue University (2009-2012). His educational background includes: Ph.D. in Applied Mathematics from Brown University (2009) M.Sc. in Applied Mathematics from Brown University (2004) B.S. in Engineering Sciences and Applied Mathematics from Northwestern University (2003) B.S. in Electrical Engineering from Northwestern University (2003) Akil Narayan's primary research interests lie in numerical analysis, scientific computing, and approximation algorithms. His work spans multiple domains including uncertainty quantification, multifidelity modeling, optimization, and computational methods for partial differential equations. He has made significant contributions to the development of numerical methods for solving complex computational problems across various scientific and engineering disciplines. His research often bridges theoretical mathematics with practical applications in fields such as biomedical engineering, ecology, and power systems. Analysis of his recent publications reveals a strong focus on uncertainty quantification, multifidelity methods, and scientific machine learning. His work increasingly integrates traditional numerical methods with modern machine learning techniques, particularly in the development of physics-informed neural networks. There's also a notable emphasis on structure-preserving numerical methods and optimization techniques for computational models. His research has significant applications in biomedical imaging, particularly in electrocardiographic imaging and cardiac modeling. While specific scientific awards are not detailed in the available information, his extensive publication record in top-tier journals demonstrates recognition in his field. His work appears regularly in prestigious journals such as SIAM Journal on Scientific Computing, Journal of Computational Physics, and SIAM Review. Professor Narayan has advised numerous graduate students through the Department of Mathematics and the School of Computing at the University of Utah. His current advisees include Filip Belik, Haoyu Chen, John Turnage, and Yinqian Yu, working on topics ranging from numerical methods for PDEs to operator learning and uncertainty quantification. His former students have gone on to positions at institutions including General Motors, Amazon, Intel Corporation, and various academic institutions. He has also secured research funding supporting his work in computational mathematics and scientific computing, though specific grant details are not provided in the available text. He is actively involved with the Scientific Computing and Imaging (SCI) Institute at the University of Utah, where he collaborates with researchers across disciplines. His work through the UncertainSCI project focuses on uncertainty quantification for computational models in biomedicine and bioengineering, particularly in cardiac applications. He frequently collaborates with researchers in the Department of Mathematics, School of Computing, and the SCI Institute on interdisciplinary projects that combine mathematical theory with practical computational applications.

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Dinesh K. Paiمشاهده پروفایل

استاد

University of British ColumbiaCanada

Dinesh K. Pai is a Professor and Tier 1 Canada Research Chair in the Department of Computer Science at the University of British Columbia, where he directs the Sensorimotor Systems Laboratory. He holds cross-appointments at UBC’s Institute for Computing, Information and Cognitive Systems (ICICS), Institute of Applied Mathematics, Graduate Program in Neuroscience, ICORD International Collaboration on Repair Discoveries, and Brain Research Centre. His educational background includes a Ph.D. from Cornell University and a B.Tech. from the Indian Institute of Technology, Madras. His research spans sensorimotor computation with applications in computer graphics, robotics, biomechanics, haptics, and neurobiology. Recent work focuses on human body modeling, garment simulation, soft tissue dynamics, and friction measurement, leveraging machine learning and physics-based simulation techniques. Pai’s publication trends reveal a strong interdisciplinary focus on human-centered computational models, with increasing integration of machine learning for 3D pattern adjustment, body shape generation, and cloth simulation. His work bridges computer graphics with biomechanics and neuroscience through sensorimotor computation. UBC’s 2012 Killam Research Prize CHCCS 2020 Achievement Award Tier 1 Canada Research Chair His research has been supported by significant grants including NSERC Discovery and Idea-to-Innovation grants, a Major Thematic Grant from the Peter Wall Institute for Advanced Studies, and a Human Frontier Science Program grant for studying CNS modularity. As leader of ICICS’ Human Sensorimotor Systems theme, he directs a multidisciplinary team exploring computational models of human sensorimotor function. The Sensorimotor Systems Laboratory operates state-of-the-art facilities featuring a Vicon MX motion capture system, LMI HDI body scanner, eye trackers, skin measurement instruments, EMG systems, haptic interfaces, and robotic platforms for advancing human-computer interaction research.

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Evangelos Miliordosمشاهده پروفایل

دانشیار

Auburn UniversityUnited States

Evangelos Miliordos is an Associate Professor in the Department of Chemistry and Biochemistry at Auburn University. His academic journey includes a Ph.D. and M.Sc. from the National and Kapodistrian University of Athens, Greece. He has held postdoctoral positions at the University of Delaware, Pacific Northwest National Laboratory, and Michigan State University before joining Auburn in 2016 as an Assistant Professor. Research Interests : Miliordos' research focuses on theoretical and computational chemistry, particularly in transition metal chemistry, solvated electron precursors (SEPs), and catalytic processes. His group explores novel materials, methane-to-methanol conversion, CO₂ capture, and electronic structure analysis of metal complexes. Key projects include predicting SEP-based materials and understanding reaction mechanisms involving excited states. Awards : He has received notable awards such as the NSF CAREER Award (2020), OpenEye Junior Faculty Award (2021), and Young Investigator Scholar Award (2024). His work has been supported by grants from the NSF, DoE, and Auburn University. Teaching : Miliordos teaches courses like Computational Chemistry, Physical Chemistry, and Advanced Physical Chemistry. He has mentored numerous students, including PhD candidates Shahriar Khan, Isuru Ariyarathna, and Benjamin Jackson, who have published extensively under his guidance. Labs/Teams : His research group collaborates with experimentalists like Drs. Ming Chen and Christian Goldsmith, advancing areas such as lanthanide/actinide chemistry and catalytic mechanisms. Ongoing projects include SEPs' applications in quantum computing and CO₂ utilization.

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Sorin Micuمشاهده پروفایل

استاد

University of CraiovaRomania

Sorin Micu is a Professor in the Department of Mathematics at the Faculty of Mathematics and Natural Sciences, University of Craiova, Romania. He is actively involved in research and teaching, with a strong focus on partial differential equations and their control. University: University of Craiova School: Faculty of Mathematics and Natural Sciences Department: Department of Mathematics Email: sd_micu@yahoo.com Office: Room 309, Central Building, AI Cuza 13, 200585 Craiova, Romania Research Interests: His primary research areas include the control of partial differential equations (PDEs), numerical analysis of PDEs, and mathematical modeling. He investigates controllability properties of various PDEs such as the heat, wave, Schrödinger, and Korteweg-de Vries equations, often using tools like Carleman estimates, duality methods, and finite element approximations. His work bridges theoretical analysis with numerical simulation, particularly in the context of semidiscretized and discrete systems. Publication Trends: The articles span from 1995 to 2017, showing sustained contributions in control theory for PDEs. The research evolves from classical equations (heat, wave) to more complex models (nonlocal, degenerate, nonlinear), with increasing focus on numerical approximation and discrete controllability. Keywords consistently revolve around controllability , stabilization , numerical methods , and nonlinear dynamics . Scientific Projects: Bilateral Contract Romania-France (2009–2010), Capacities Program, Module III Bilateral Project Romania-France (English version) Project PN-II-ID-PCE-2011-3-0257 Teaching and Advising: Professor Micu teaches courses such as Numerical Analysis, Algorithmics and Numerical Simulation in C++, Modeling and Simulation, and Finite Element Methods at both undergraduate and master’s levels. While formal advisees are not listed, his teaching and research supervision likely involve mentoring graduate students. He offers consultations every Thursday from 15:00 to 16:00 in Room 309. Laboratories and Teams: He is affiliated with research groups working on PDE control and numerical analysis at the University of Craiova. His collaboration with French institutions indicates participation in international research networks focused on applied mathematics and control theory.

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Marko Lindnerمشاهده پروفایل

استاد

Hamburg University of TechnologyGermany

Marko Lindner is a Professor at the Institute of Mathematics, Hamburg University of Technology (TUHH), where he holds the Chair of Applied Analysis. His research lies at the intersection of functional analysis and numerical analysis, particularly focusing on the spectral and Fredholm theory of infinite matrices and linear operators. He has led significant research projects funded by the European Union through Marie-Curie grants and has collaborated with institutions and industries including BAE Systems, UK Met Office, and Schlumberger Ltd. Hamburg University of Technology (TUHH), Institute of Mathematics Chair of Applied Analysis Email: lindner@tuhh.de Office: Room 3,094, Building E, Am Schwarzenberg-Campus 3, D-21073 Hamburg His research interests include operator theory, spectral theory, pseudospectra, finite section methods, discrete Schrödinger operators, and applications in mathematical physics and wave scattering. He investigates the stability and convergence of numerical approximation schemes for infinite-dimensional operators, with deep theoretical contributions to limit operator theory and collective compactness. The recent publications highlight a strong trend in spectral approximation of non-selfadjoint operators, particularly Schrödinger-type operators with periodic, aperiodic, and random potentials. His work combines rigorous functional analytic foundations with computational insights, often involving pseudospectra, condition number asymptotics, and subword-based approximation techniques. The integration of numerical methods with spectral theory is a consistent theme, especially in the context of wave propagation and scattering problems. Scientific awards include: Individual Marie-Curie Fellowship (EU, 2005–2007) Individual Marie-Curie Grant (EU, 2008–2011) Marko Lindner has supervised various research projects, particularly in the areas of wave scattering in unbounded domains and the spectral analysis of infinite matrices. His collaborations span applied mathematics, mathematical physics, and engineering, with funding from both public and private sectors. He is actively involved in the academic community, organizing events such as the Operator Theory Workshop and participating in SIAM & GAMM Chapter activities. He leads and contributes to research teams working on applied operator theory, with a focus on developing stable and efficient numerical methods for complex physical systems. His work bridges theoretical operator algebras and practical computational techniques.

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Gregory Sheardمشاهده پروفایل

استاد

Monash UniversityAustralia

Gregory Sheard is a Professor in the Department of Mechanical and Aerospace Engineering at Monash University, where he leads the Sheard Lab. He has been a permanent faculty member since 2006 and is actively involved in research, teaching, and PhD supervision. His work is centered on computational fluid dynamics, with applications in natural convection, heat transfer, and magnetohydrodynamics. Research Interests: His research spans fluid mechanics , heat transfer , magnetohydrodynamics (MHD) , flow stability , and rotating flows . He develops advanced numerical codes based on spectral-element methods to simulate incompressible flows, including linear stability and transient growth analyses. His work contributes to UN Sustainable Development Goals related to clean energy and sustainable infrastructure. Publication Trends: His recent publications (2023–2025) show a growing interdisciplinary focus, combining fluid dynamics with renewable energy systems, particularly in hydrogen production , microgrids , and techno-economic analysis . Earlier works emphasize fundamental fluid mechanics, including quasi-2D flows , wake dynamics , and thermal convection . The integration of computational modeling with real-world energy applications marks a significant evolution in his research trajectory. Faculty of Engineering Kenneth Hunt Medal Monash University Mollie Holman Doctoral Medal Young Researcher Fellowship Award for Exemplary Research in Fluid Mechanics Advising and Grants: Dr. Sheard has supervised 8 PhD students to completion and examined 9 PhD theses and over 150 journal manuscripts. He has secured over $2.2 million in nationally competitive grant funding and maintains continuous access to high-performance computing facilities worth over $100,000 annually. He is actively accepting new PhD students for research in natural convection, MHD, bluff-body flows, and rotating flows. Laboratory and Professional Engagement: He founded and maintains The Sheard Lab , which specializes in high-fidelity numerical simulations of fluid flows. He has organized major conferences, including the 9th Australasian Natural Convection Workshop (2015) and the International Conference on Computational Fluid Dynamics in the Minerals and Process Industries (2006, 2009, 2012). He has chaired numerous technical sessions and advised on international conference committees.

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Jack HALEمشاهده پروفایل

پژوهشگر

University of LuxembourgLuxembourg

Jack HALE is a Research Scientist at the University of Luxembourg's Faculty of Science, Technology and Medicine (FSTM), Department of Engineering. He joined Prof. Stéphane Bordas' team in 2013, focusing on computational mechanics and numerical methods. His work integrates advanced techniques like meshfree methods, XFEM, and isogeometric analysis to address challenges in solid mechanics and high-performance computing. Education : PhD in Aeronautics, Imperial College London (2009-2013), supervised by Dr. Pedro M. Baiz Villafranca. MEng in Engineering, University of Bristol (2004-2008). Research exchange at Rice University (2006-2007) on cross-flow filtration processes. Research Interests : Implicit boundary methods for medical image-based simulations. Development of scalable meshfree/XFEM/isogeometric analysis frameworks. Mixed variational methods to resolve locking phenomena in solid mechanics. High-performance computing for distributed parallel systems. Publications & Software : His 50+ publications emphasize open-access research via ORBilu, with a focus on FEniCSx-based tools (e.g., DOLFINx, FEniCS-shells). Recent work addresses Bayesian model selection, melt instability identification, and SAR data assimilation in aquifer modeling. Collaborations : Open to academic/industrial partnerships in computational mechanics, material science, and biomedical engineering.

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Gullu Kızıltaş Şendurمشاهده پروفایل

دانشیار

Sabanci UniversityTurkey

Dr. Gullu Kızıltaş Şendur is an Associate Professor in the Mechatronics Engineering Department at Sabancı University's Faculty of Engineering and Natural Sciences in Istanbul, Turkey. She received her B.S. and M.S. degrees in Mechanical Engineering from Middle East Technical University in Ankara, Turkey in 1995 and 1998, respectively, and completed her Ph.D. in Mechanical Engineering at the University of Michigan, Ann Arbor in 2003. Her research spans multiple interdisciplinary fields with a focus on: Design Optimization of mechanical, biomedical and electromagnetic systems Material Design and Fabrication using topology optimization and advanced 3D fabrication techniques Computational Mechanics including advanced micro-material modeling and Finite Element Methods Electromagnetics applications for miniature antennas and RF devices Tissue Engineering for artificial tissues and organs Dr. Kızıltaş Şendur's recent work demonstrates a strong trend toward additive manufacturing, multi-material design, and computational methods for creating functionally graded structures. Her research integrates computational design with experimental validation across mechanical engineering, biomedical applications, and electromagnetic systems. She has developed novel optimization frameworks that bridge multiple disciplines to solve complex engineering problems. Her scientific achievements have been recognized with prestigious awards including: 2008 Graduating Class Teaching Award from Sabancı University 2008 TUBA-GEBIP (Young Scientist Award) from the Turkish Academy of Sciences Dr. Kızıltaş Şendur has successfully advised numerous graduate students through their M.Sc. and Ph.D. programs, with many continuing to academic and research careers at institutions worldwide. She leads the 3D Systems Design and Realization Research Laboratory at Sabancı University's Nanotechnology Research and Application Center (SUNUM), which provides state-of-the-art facilities for multi-disciplinary research. Her laboratory focuses on the modeling and fabrication of multi-functional micro/nanostructures, with applications spanning mechanical engineering, biomedical devices, and electromagnetic systems. The group maintains strong collaborations with international research institutions and industry partners to advance the frontiers of computational design and advanced manufacturing.

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