جست‌وجوی استاد و پژوهشگر

Amirtham Rajagopalمشاهده پروفایل

استاد

• Damage Mechanics
• Fracture Mechanics
• Finite Element and Mesh free methods
• +۴ مورد دیگر

Amirtham Rajagopal is a Professor in the Department of Civil Engineering at the Indian Institute of Technology Hyderabad. His research focuses on advanced computational mechanics, including damage and fracture mechanics, multiscale modeling, and additive manufacturing techniques. Education : Ph.D. from IIT Madras Research Interests span critical areas in civil and computational engineering, with emphasis on numerical methods and nanoscale applications. He works in the Academic Block B, Room B-521, and can be contacted via office phone (040) 2301 - 6303.

• Automotive Engineering
• Materials Science
• Battery Safety and Lifecycle
• +۳ مورد دیگر

Florian Feist is a researcher at the Institute for Vehicle Safety (VSI) at Graz University of Technology. His work focuses on automotive materials, battery crash safety, and sustainable lightweight composites. Research Interests: Automotive engineering, crash simulation, battery lifecycle analysis, and biomechanical modeling. Recent projects include wood-steel hybrid components , Li-ion battery crash behavior , and bio-based foam for helmets . Scientific Contributions: Key themes in his publications (2024-2025) include multiscale battery modeling , stitched wood composites , and dynamic material testing . His work bridges mechanical engineering , material science , and sustainable design .

• Materials for supercapacitors
• Fuel cell materials
• Lithium battery materials
• +۱۹ مورد دیگر

Professor Kamal K Kar is a full Professor in the Department of Mechanical Engineering at Indian Institute of Technology Kanpur (IITK) . He earned his PhD from IIT Kharagpur in 1999 and has since built an internationally recognised research profile in advanced materials, energy storage and biomedical applications. Education: PhD, IIT Kharagpur, 1999 – Thesis on hysteresis loss behaviour of filled rubber vulcanizates Research Focus: Professor Kar’s work integrates fundamental materials science with applied engineering. His group synthesises and characterises nanostructured carbon allotropes (carbon nanotubes, graphene, porous carbon) and polymer-matrix nanocomposites for next-generation devices. Core application areas include: High-capacity supercapacitors and lithium-ion batteries Efficient fuel cells and solar cells Scalable water purification systems Light-weight, high-strength structural composites for aerospace and defence (e.g., Arjun battle tank road-wheels) Biocompatible bio-implants and tissue-engineering scaffolds Publications & Patents: His recent outputs reveal a strategic emphasis on patent-protected innovations (two PCT filings on carbon nanofiber coatings and hydroxyapatite-PEEK nanocomposites) alongside high-impact journals. The works span synthesis, processing, finite-element modelling and device integration, underscoring a comprehensive approach from lab-scale discovery to translational technology. Scientific Recognition: Associate Editor, Materials Express (American Scientific Publishers) Editorial Board Member, International Journal of Plastic Technology (Springer) Editorial Board Member, Journal of Recent Patents on Nanotechnology (Bentham Science) Teaching & Mentoring: At IITK he teaches core undergraduate courses such as Structure and Properties of Materials and Composite Materials , and mentors graduate students in advanced laboratories. His lab hosts interdisciplinary teams that collaborate with national defence, energy and healthcare agencies.

Vissarion Papadopoulosمشاهده پروفایل

استاد

• Structural Engineering
• Computational Mechanics
• Stochastic Analysis
• +۳ مورد دیگر

Vissarion Papadopoulos is a Professor in the Department of Structural Engineering at the School of Civil Engineering, National Technical University of Athens (NTUA). His office is located at the Statics and Aseismic Research Laboratory, with contact details including email vpapado@central.ntua.gr and phone 210 772 4158. He has maintained an active research profile since at least 2016, focusing on advanced computational methods in structural engineering. His primary research domains include: Structural Engineering and Computational Mechanics Stochastic Analysis and Uncertainty Quantification Multiscale Modeling of Composite Materials Machine Learning for Engineering Simulations Optimization of Structural Systems Thermomechanical Behavior of Advanced Materials Analysis of his recent publications reveals a decisive shift toward integrating deep learning frameworks with traditional computational mechanics. His work demonstrates consistent innovation in accelerating solutions for parametric and transient structural problems through transformer networks, Bayesian inference, and physics-informed neural networks. Key application areas include carbon nanotube reinforced composites, sustainable automotive design, and seismic-resistant structures, with emphasis on enhancing computational efficiency while maintaining accuracy. He is affiliated with NTUA's Statics and Aseismic Research Laboratory, which specializes in structural dynamics, earthquake engineering, and advanced computational methodologies for civil infrastructure analysis and design.

Mario Ohlbergerمشاهده پروفایل

استاد

• Numerical Analysis
• Machine Learning
• Scientific Computing
• +۳ مورد دیگر

Prof. Dr. Mario Ohlberger is a faculty member in the Department of Mathematics and Computer Science at the University of Münster, Germany. As a leading researcher in numerical analysis and scientific computing, he contributes to the Cluster of Excellence 2044 'Mathematics Münster: Dynamics – Geometry – Structure' and the Mathematical Research Data Initiative (MaRDI). His work integrates machine learning with classical numerical methods. University: University of Münster Research Focus: Numerical analysis for PDEs, model reduction, machine learning, multiscale methods Key Projects: EXC 2044 (subprojects C2 and C4), MaRDI His recent publications emphasize adaptive reduced basis methods, multi-fidelity learning, and surrogate modeling for parameterized PDEs, with applications in oil recovery and reactive transport. He has supervised numerous theses and taught courses on numerical analysis, scientific computing, and model reduction. Scientific awards include the Eliteförderprogramm für Postdoktoranden (2002), Ferdinand-von-Lindemann-Preis (2001), and a 1994 teaching award. Current teaching includes lectures on differential equations and seminars on advanced numerical methods.

Anthony Paul Doulgerisمشاهده پروفایل

استاد

• Remote Sensing
• Synthetic Aperture Radar (SAR) Imaging
• Sea Ice Monitoring
• +۳ مورد دیگر

Professor Anthony Paul Doulgeris at the UiT The Arctic University of Norway leads research in Earth Observation within the Department of Physics and Technology . His work focuses on Interpreting satellite radar images for Arctic sea ice studies Developing automated algorithms for large-scale environmental data Advancing SAR (Synthetic Aperture Radar) methodologies His research interests span Remote Sensing , Sea Ice Dynamics , Machine Learning Applications , and Algorithm Optimization for polar environments. Current projects include Boosting Space Business and membership in the Earth Observation research group. Recent publications analyze High-resolution sea ice concentration using Sentinel-1 deep learning models Icberg detection via multiscale CFAR algorithms in L-band SAR Multidecadal SAR sea ice type analysis in the Atlantic Arctic Incidence angle compensation techniques for cross-platform consistency with keywords spanning Arctic Climate , Microwave Remote Sensing , Operational Ice Monitoring , and Data Processing Frameworks . Collaborations include international teams from Norway, China, and Canada, with fieldwork integration in expeditions like MOSAiC and N-ICE2015. His work bridges Satellite Data and Environmental Modeling to improve Arctic navigation and climate predictions.

• Structural optimization
• Additive Manufacturing
• Vibration Engineering
• +۵ مورد دیگر

Dr. Akihiro Takezawa is a Professor in the Department of Mechanical Science and Aeronautics and Astronautics at Waseda University's School of Fundamental Science and Engineering. Previously, he held positions at Hiroshima University Graduate School of Engineering and FANUC Corporation. His academic career spans structural optimization, additive manufacturing, and vibration engineering, with particular expertise in topology optimization for advanced material design. Dr. Takezawa's research interests focus on structural optimization methodologies, additive manufacturing processes, and vibration engineering applications. His work bridges theoretical optimization techniques with practical engineering applications, particularly in designing lattice structures with tailored mechanical and thermal properties. He has made significant contributions to the field of topology optimization for additive manufacturing, developing methods to control thermal deformation, optimize lattice structures for specific mechanical properties, and design metamaterials with unique characteristics. Analysis of his recent publications reveals a strong trend toward practical applications of topology optimization in additive manufacturing, with increasing focus on multi-physics problems involving thermal, mechanical, and fluid dynamics. His research has evolved from fundamental optimization methodologies to their application in complex engineering problems such as energy-absorbing metamaterials, thermal management systems, and vibration control devices. Japan Society of Mechanical Engineers, Design Engineering and Systems Division Achievement Award (2020.11) 2016 Mechanical Mechanics and Measurement Control Division General Award from the Japan Society of Mechanical Engineers (2017.08) Minister of Education, Culture, Sports, Science and Technology Young Researcher Award (2017.04) Japan Society of Mechanical Engineers, Design Engineering and Systems Division, Frontier Achievement Award (2015.09) The 2015 JACM Award for Young Investigators in Computational Mechanics (2015.07) Dr. Takezawa has supervised numerous graduate students and has been involved in multiple research projects funded by Japanese government agencies and industry partners. His research has resulted in over 100 publications with more than 5,000 citations according to Google Scholar, demonstrating significant impact in the fields of structural optimization and additive manufacturing. His laboratory at Waseda University focuses on advancing computational methods for designing next-generation materials and structures. Dr. Takezawa leads a research group that combines computational mechanics, materials science, and manufacturing technology to develop innovative solutions for engineering challenges. His team utilizes advanced optimization algorithms, finite element analysis, and additive manufacturing techniques to create novel material architectures with tailored properties for specific applications.

• Fluid Engineering
• Computational Fluid Dynamics
• Isogeometric Analysis
• +۲ مورد دیگر

Kenji Takizawa is a Professor at the Faculty of Science and Engineering, School of Creative Science and Engineering at Waseda University. He holds a PhD from Tokyo Institute of Technology (2005) and specializes in computational mechanics with a focus on fluid-structure interaction problems. His educational background includes: PhD in Energy Sciences from Tokyo Institute of Technology (2005) Master's degree in Energy Sciences from Tokyo Institute of Technology (2002) Bachelor's degree in Mechanо-Aerospace Engineering from Tokyo Institute of Technology (2001) Takizawa's research focuses on computational fluid dynamics, isogeometric analysis, and fluid-structure interaction. His work centers on developing advanced computational methods for complex engineering problems involving moving boundaries, contact mechanics, and turbulent flows. He has pioneered space-time variational multiscale (ST-VMS) methods that enable high-fidelity simulations of challenging problems such as heart valve flows, tire aerodynamics, and wind turbine wake dynamics. His recent publications reveal a strong focus on space-time computational methods with applications spanning aerospace engineering, biomedical devices, automotive systems, and renewable energy. The research demonstrates consistent innovation in handling complex geometries, moving boundaries, and multi-scale phenomena through integrated computational frameworks that combine isogeometric analysis with topology change capabilities. His significant scientific achievements have been recognized through numerous prestigious awards: 2022 APACM Computational Mechanics Award 2018 JSPS Prize Multiple Highly Cited Researcher designations (2016-2018) Thomas J.R. Hughes Young Investigator Award (2012) Computational Mechanics Achievement Award from JSME (2014) Takizawa has made substantial contributions to computational mechanics through his development of innovative numerical methods that address previously intractable problems involving moving boundaries and interfaces. His work bridges theoretical advancements with practical applications across multiple engineering disciplines.

• Artificial Intelligence
• Robotics
• Materials Science
• +۳ مورد دیگر

Dengpeng Huang is an Assistant Professor specializing in Artificial Intelligence and Robotics within the field of Elastomer Technology and Engineering . His work bridges computational modeling with advanced materials, focusing on applications in smart materials and mechanical systems. Research Interests: Development of AI-driven models for predicting elastomer properties Multiscale analysis of rubber composites Electromechanical coupling in dielectric elastomer actuators Meshfree methods for metal cutting and chip formation Ultra-precision polishing of optical surfaces Recent Trends: His 2024–2025 publications emphasize data-driven modeling of rubber's viscoelastic behavior, multiscale analysis of composites, and CNN-based approaches for material characterization. Earlier work (2014–2022) explores tool path optimization, beam modeling, and computational machining. Scientific Recognition: Holds an h-index of 5 according to Scopus citations, with recognition as an AI and robotics expert in the service industry. Advising & Collaboration: Collaborates with researchers like Anna Blume, Evgeny Karaseva, and Tim Bor on elastomer composites. Supervised at least one academic work, though specific students are not named in the provided data. Labs & Teams: Affiliated with simulation and robotics teams in the smart materials sector, likely within an advanced materials or mechanical engineering research group.

Karin Leidermanمشاهده پروفایل

دانشیار

• Blood Coagulation
• Mathematical Biology
• Computational Biofluid Dynamics
• +۳ مورد دیگر

Karin Leiderman, PhD, is an Associate Professor in the Department of Mathematics and a member of the UNC Lineberger Comprehensive Cancer Center. She also holds appointments in the Department of Biochemistry and Biophysics and the Computational Medicine Program at the University of North Carolina at Chapel Hill. Her research integrates mathematical modeling, computational simulations, and experimental approaches to study biochemical and biophysical mechanisms in blood coagulation, clot formation, and bleeding disorders with applications in hemophilia and cancer-associated thrombosis. She leads the Leiderman Research Group, which develops open-source software frameworks like clotFoam for simulating thrombus formation under flow. Recent publications highlight her work on: Mathematical analysis of anticoagulant drugs (emicizumab, concizumab) and their impact on coagulation Computational modeling of lipid surface enzyme kinetics and HIV-1 Env protein binding Development of multiscale models for hemostasis and thrombosis Scientific awards include: NSF CAREER Award (2020) Colorado School of Mines Faculty Excellence Award (2021) W.M. Keck Graduate Student Mentorship Award (2020) Invited State-of-the-Art Speaker at ISTH (2022) Dr. Leiderman has mentored numerous graduate and undergraduate students, including Jamie Madrigal (PhD, UNC), Kenji Miyazawa (PhD, UNC), and Nicholas Danes (PhD, Colorado School of Mines). Her research is supported by NIH R01 funding and focuses on contextualizing findings across mathematical and biological communities.

Sebastian Brandstäterمشاهده پروفایل

مدرس

• Scientific Machine Learning
• Inverse analysis & Bayesian Inference
• Uncertainty Quantification
• +۵ مورد دیگر

Dr. Sebastian Brandstäter serves as Lecturer at the Institute for Mathematics and Computer-Based Simulation, Bundeswehr University Munich since 2022. His academic trajectory includes research associate positions at Hamburg University of Technology (2021) and Technical University of Munich (2016-2021). His research focuses on: Scientific Machine Learning for biomechanical systems Uncertainty Quantification and Bayesian Inference Global Sensitivity Analysis of complex models Multi-Physics & Multi-Scale Modeling of biological tissues Open-source scientific software development Dr. Brandstäter's work centers on gastrointestinal biomechanics, particularly computational modeling of gastric electromechanics and motility. He has pioneered applications of Gaussian-process metamodelling for sensitivity analysis in vascular and gastric systems, and develops open-source frameworks (QUEENS, 4C) that enable efficient multi-query analysis of large-scale models. He actively supervises student theses on patient-specific modeling and computational biomechanics, teaches advanced numerical methods courses, and contributes to the scientific community through conference organization, peer review, and international collaborations. His recent work demonstrates increasing emphasis on data-driven surrogate modeling and solver-independent computational frameworks for biomedical applications.

• Nonsmooth elliptic and parabolic problems involving multiple scales
• Variational problems and geometric partial differential equations
• Subspace correction methods
• +۸ مورد دیگر

Prof. Dr. Ralf Kornhuber is a faculty member at the Freie Universität Berlin , affiliated with the Department of Mathematics and Computer Science and the Numerical Analysis of Partial Differential Equations institute. His research focuses on advanced numerical methods for multiscale problems and applications in geosciences, biomechanics, and materials science. Education: Dr. rer. nat. in Mathematics (1986) and Diploma in Mathematics (1979), both from TU Berlin. Academic Career: Senior Professor at Freie Universität Berlin (since 2023), Full Professor (C4) at the same institution (1998-2022), and prior roles at University of Stuttgart, WIAS Berlin, and TU Berlin. Research Interests: He specializes in adaptive finite element methods, subspace correction techniques, and multiscale modeling of partial differential equations (PDEs). His work addresses nonsmooth elliptic/parabolic problems, geometric PDEs, and domain decomposition strategies, with applications spanning geoscience simulations, biomechanics, and material science. Scientific Boards & Committees: Chair of CRC 1114 Scaling Cascades in Complex Systems (2021-2022), leadership roles in MATH+, Berlin Mathematical School, and Helmholtz Research School GeoSim, alongside editorial positions at journals like SIAM Journal on Multiscale Modeling and Simulation . Recognition: Awarded the International Multigrid Prize in 2022 for collaborative contributions to multigrid methods.

• Numerical Analysis
• Scientific Computing
• Partial Differential Equations
• +۳ مورد دیگر

Herbert Egger is a Professor of Numerical Analysis and Scientific Computing at Johannes Kepler University (JKU) Linz and heads the Institute of Numerical Mathematics. He is also a Group Leader at RICAM (Johann Radon Institute for Computational and Applied Mathematics) and Scientific Director at the Austrian Academy of Sciences. His research focuses on advanced numerical methods for partial differential equations, including structure-preserving discretizations, inverse problems, and computational electromagnetics. Current projects include SFB F90-N (CREATOR) for electric machine co-simulation, SPP 2256 for phase-field modeling in additive manufacturing, and TRR 146 on multiscale soft matter systems. Key research areas: mixed/hybrid finite element methods, energy-based modeling, model order reduction, radiative transfer, and inverse problem stabilization. His recent work emphasizes nonlinear magnetostatics, phase separation models, and efficient solvers for time-dependent systems. Egger collaborates internationally with institutions like TU Eindhoven and TU Darmstadt.

Thierry Augerمشاهده پروفایل

پژوهشگر ارشد

• Liquid metal embrittlement
• Metallurgy
• Plasticity and fracture
• +۴ مورد دیگر

Thierry Auger is a Research Fellow at the PIMM laboratory (Arts et Métiers Sciences et Technologies) since October 2017, where he leads research in the CoMet team focusing on Behavior and Microstructure of Metals. His extensive academic career spans over two decades with previous positions at the Laboratory of Mechanics of Structures, Soils and Materials (Ecole CentraleSupélec/MSSMAT, 2008-2017) and the Laboratory Centre for the Study of Metallurgical Chemistry (CNRS/CECM, 2001-2008). Dr. Auger's research centers on liquid metal embrittlement phenomena, metallurgy, and fracture mechanics. His work investigates how liquid metals interact with structural materials causing embrittlement, with particular focus on nuclear materials exposed to liquid sodium, lead, and lead-bismuth eutectic. His expertise spans from fundamental understanding of embrittlement mechanisms to practical applications in nuclear engineering systems. His recent publications (2021-2025) demonstrate a strong focus on high-entropy alloys exposed to liquid metals, advanced characterization of embrittlement mechanisms, and multi-scale modeling approaches. These works appear in leading journals including Corrosion Science, Scripta Materialia, and Journal of Nuclear Materials, reflecting his significant contributions to understanding material degradation in extreme environments. Dr. Auger actively contributes to nuclear materials research through multiple collaborative projects including ANR Gauguin and Meso3D, and maintains strong connections with national and international research institutions working on advanced nuclear systems and liquid metal technologies. His teaching portfolio includes Structural Integrity and Continuum Mechanics courses at ENSAM for Energy Engineering students, bridging his research expertise with educational responsibilities in materials science and mechanical engineering.

Wylie Strobergمشاهده پروفایل

استادیار

• Biomechanics
• Biomedical Engineering
• Biomaterials
• +۸ مورد دیگر

Wylie Stroberg is an Assistant Professor in the Department of Mechanical Engineering within the Faculty of Engineering at the University of Alberta. He leads the Computational BioSystems Lab, where he conducts research at the interface between cell biology, physiology and engineering using a range of computational and theoretical techniques. His research interests span multiple areas including: Biomechanics and Biomedical Engineering Biomaterials Mechanics and Materials Composites and Polymers Nano and Micro Materials Computational Mechanics Systems Biology of Proteostasis and the Unfolded Protein Response Reactions in Crowded Cellular Compartments Wetting Phenomena of Nanoscale Structures Dr. Stroberg's research focuses on developing new quantitative techniques for studying complex biological systems across disparate length and time scales. His work has significant implications for understanding cellular physiology, protein homeostasis, and developing new therapeutic approaches for age-associated and protein folding diseases. He employs advanced computational methods including multiscale modeling, machine learning, and theoretical analysis to investigate biological phenomena from the molecular to cellular level. His research group has published extensively in mathematical biology and computational mechanics, with a consistent focus on enzyme kinetics, cellular stress responses, and computational modeling of biological processes. The publications demonstrate a strong interdisciplinary approach combining techniques from mechanical engineering, computational science, and molecular biology. Dr. Stroberg has received recognition for his work in mathematical biology and systems biology, with publications in journals such as the Journal of Theoretical Biology, Biophysical Journal, and Mathematical Biosciences. He currently advises several graduate students working on diverse projects including multiscale modeling of enzymatic nanosensors, protein-based modulation of endoplasmic reticulum shape, development of machine learning-based coarse grained models for high-entropy alloys, and simulation of high-entropy alloys for thermal-spray deposition. His lab has trained undergraduate and master's students who have gone on to further academic pursuits. The Computational BioSystems Lab maintains active collaborations with other researchers at the University of Alberta and beyond, working at the intersection of engineering, biology, and computational science.