Professor Inge Hoff is affiliated with the Norwegian University of Science and Technology (NTNU) in the Department of Civil and Environmental Engineering, where he has served since 2009. Prior to this, he held roles as senior researcher and research leader at SINTEF. Research Interests : Materials for road construction, frost protection, laboratory testing, pavement dimensioning, road rehabilitation, state development modeling, ground-penetrating radar surveys, and concrete/natural stone coverings. Students : Mentors active PhD fellows Lisa Hannasvik, Arman Hamidi, Clara Weber, and Shoiab Ahmad. Teaching : Coordinates courses like TBA4204/BYGT1102 Transport Infrastructure , BYGT2204 Road and Railway Construction , and BA8600 Pavement Structure Dimensioning . Recent publications highlight his expertise in granular material behavior, asphalt durability under climate stressors, and advanced structural assessment techniques. Collaborations with international researchers and presentations at major conferences (TRB, International Conference on Bituminous Mixtures) demonstrate his ongoing contributions to road engineering.
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Noel J. Walkington is a Professor in the Department of Mathematical Sciences at Carnegie Mellon University, affiliated with the Mellon College of Science. His research focuses on developing numerical algorithms for partial differential equations, bridging mechanical engineering and mathematics. Education: M.S. and Ph.D. in Mechanical Engineering from the University of Missouri-Rolla, and a Ph.D. in Mathematics from the University of Texas at Austin. Postdoctoral appointments at both institutions. Research interests include numerical methods for multiphase flows, viscoelastic fluids, and complex fluid dynamics. His work emphasizes computational techniques for engineering and mathematical challenges. Publications span topics like porous media flow, control volume approximations, and liquid crystal dynamics, reflecting a strong focus on computational and applied mathematics.
Gaetano Miragliaمشاهده پروفایل
استادیار
Gaetano Miraglia is a Fixed-term Assistant Professor in the Department of Structural, Building and Geotechnical Engineering (DISEG) at Politecnico di Torino, where he conducts research in structural health monitoring, seismic analysis, and computational modeling. He is a member of the Interdepartmental Center R3C – Responsible Risk Resilience Centre, contributing to interdisciplinary efforts in risk mitigation and infrastructure resilience. His work spans both theoretical and applied domains, with strong emphasis on heritage preservation and sustainable urban development. His research interests include Bayesian calibration of nonlinear models, hybrid simulation, peridynamics, masonry structures, and the integration of satellite interferometric (InSAR) data with in-situ measurements for structural monitoring. He applies advanced computational and machine learning techniques to improve the accuracy and reliability of structural assessments, particularly in historical and monumental buildings. His work supports UN Sustainable Development Goals 9, 11, and 13. His recent publications demonstrate a consistent focus on data fusion, digital twinning, domain adaptation, and real-time damage detection. He frequently collaborates with researchers such as Rosario Ceravolo and Erica Lenticchia, publishing in high-impact journals like Computer-Aided Civil and Infrastructure Engineering , Structures , and Scientific Reports , as well as at major conferences including EWSHM, SAHC, and EVACES. His research is applied in projects such as the monitoring of the Vicoforte Sanctuary and the development of the CAMELOT and HY-LEARN toolboxes. Research Projects: MONITORAGGIO VICOFORTE (2024–2026) – Member of Research Group CAMELOT – PoC Transition (2023–2024) – Member of Research Group HY-LEARN – Model Calibration via Hybrid Simulation and ML (2022–2024) – Scientific Manager (PNRR Mission 4) He teaches in various programs, including as a course collaborator in PhD, Master’s, and Bachelor’s level courses such as Earthquake Engineering , Structural Consolidation , and Seismic Risk of Cultural Heritage . He is also an inventor on national and international patents and software related to the CAMELOT toolbox, highlighting the translational impact of his research. He has no listed scientific awards or formal advisees in the provided text.
Glaucio H. Paulino holds the Margareta Engman Augustine Professorship in Civil and Environmental Engineering at Princeton University, where he also serves as a Professor at the Princeton Institute for the Science and Technology of Materials (PRISM). His work bridges computational mechanics, topology optimization, and materials science. Paulino leads a research group focused on advancing structural design methodologies, fracture mechanics, and functionally graded materials. His team has pioneered polygonal finite elements and multiresolution topology optimization techniques, addressing challenges in mesh bias and computational efficiency. He has published over 240 peer-reviewed articles and mentored 19 PhD and 11 MS students. Notable contributions include the PPR cohesive model for fracture analysis and adaptive mesh refinement for dynamic simulations. Paulino's research extends to practical applications such as high-rise building design and sustainable construction materials. Awards include election to the European Academy of Sciences and Arts and ASME’s Melville Medal. Current projects involve functionally graded cement-based materials, extrusion processing, and digital image correlation for material characterization. His lab collaborates with industry partners like Skidmore, Owings & Merrill LLP to translate topology optimization into real-world engineering solutions. Paulino’s interdisciplinary approach integrates computational modeling with experimental validation, fostering innovations in civil infrastructure resilience.
Dr. Fengyan Li is a Professor in the Department of Mathematical Sciences at Rensselaer Polytechnic Institute (RPI). She holds a PhD in Applied Mathematics from Brown University (2004) and previously held a postdoc at the University of South Carolina. Her research focuses on numerical analysis and scientific computing, particularly discontinuous Galerkin methods for applications in wave propagation, fluid dynamics, plasma physics, and nonlinear optics. She has received prestigious awards including the NSF-CAREER Award (2009) and Alfred P. Sloan Fellowship (2008). Dr. Li serves on editorial boards of journals like SIAM Journal of Numerical Analysis and IMA Journal of Numerical Analysis. Education: PhD in Applied Mathematics (Brown University, 2004); MS & BS in Computational Mathematics (Peking University, 2000 & 1997). Research interests emphasize multi-scale simulations, reduced-order modeling, and high-order methods. Her work addresses challenges in kinetic transport, nonlinear optics, and plasma dynamics. She has delivered plenary talks at major conferences, including ICOSAHOM (2018) and NAHOMCon (2022). Professional service includes leadership roles in the Association for Women in Mathematics (AWM), co-organizing symposiums, and mentoring. She is a 2025 AWM Fellow and advises RPI's AWM Student Chapter.
Dr. Yongjie Jessica Zhang is a Professor at Carnegie Mellon University, holding appointments in both the Department of Mechanical Engineering and the Department of Biomedical Engineering . She received her B.S. and M.S. in Engineering Mechanics from Tsinghua University, followed by an M.S. in Aerospace Engineering and a Ph.D. in Computational Engineering and Sciences from the University of Texas at Austin. After a postdoctoral fellowship at ICES, she joined CMU in 2007, advancing from assistant to full professor by 2016. Research Interests : Image-based geometric modeling, mesh generation, finite element analysis (FEA), isogeometric analysis, and applications in computational biomedicine, materials science, and computer-assisted surgery. Leadership Roles : Chair of Solid Modeling Association (2019-2020), USACM Executive Committee Member-at-Large (2017-2021), and ELATE Fellow (2017-2018). Her work addresses the critical challenge of automating high-fidelity geometric modeling and mesh generation for complex domains (e.g., human anatomy), which traditionally consumes ~80% of FEA time. Her group develops AI-driven methods for multiscale modeling (molecular to organ), with applications in neuroscience , biomechanics , and 4D printing . Notable awards include the Presidential Early Career Award (PECASE) , NSF CAREER Award , and ASME Van C. Mow Medal (2025) . Dr. Zhang’s publications span over 170 peer-reviewed articles, focusing on truncated hierarchical B-splines , polycube meshing , and neurite transport modeling . She has advised more than 40 students, including PhD candidates and postdoctoral fellows. Her editorial roles include Associate Editor of Computer Aided Geometric Design and editorial board memberships in Computer-Aided Design and Engineering with Computers .
Sunday Oyadijiمشاهده پروفایل
دانشیار
Sunday Oyadiji is an Associate Professor in the Department of Mechanical and Aerospace Engineering at The University of Manchester. He holds a BSc (First Class) and PhD in Mechanical Engineering from the same institution (1979 and 1983). Before joining the University of Manchester in 1991, he served as a Lecturer at Obafemi Awolowo University, Nigeria, and conducted postdoctoral research at Heriot-Watt University and the University of Manchester. His research focuses on viscoelasticity, smart materials for vibration isolation, structural fault identification, and composite materials. Key areas include fracture mechanics, multibody dynamics, and biomechanics. He contributes to the Aerospace Research Institute and Digital Futures platforms, advancing aerospace engineering and structural fire safety. Recent work involves stress-intensity factor analysis using 3D-DIC and finite element methods, constitutive modeling of elastomeric foams, and graphene-based energy storage systems. His publications span high-impact journals like Engineering Fracture Mechanics and Polymer .
Ali Kashaniمشاهده پروفایل
مدرس ارشد
Dr. Ali Kashani is a Senior Lecturer at the University of New South Wales (UNSW) within the School of Civil and Environmental Engineering. His research focuses on sustainable and low-carbon concrete materials, robot-aided construction (particularly 3D printing), and Circular Economy-aligned applications. Leadership in cementitious materials innovation Expertise in 3D printing for construction Advocate for waste valorisation and carbon capture Dr. Kashani has secured approximately $7 million in research funding and holds a patent in lightweight concrete foam. His work spans 70+ publications with 9,000+ citations, including media coverage in the Sydney Morning Herald and The Fifth Estate. He actively contributes to professional organizations such as MECLA, RILEM, and ASTM. Recent research trends include AI and optimization algorithms for sustainable concrete mix design, chloride diffusion modeling, and 3D printing performance analysis. His publications often address waste material integration, durability assessment, and eco-friendly construction practices. Scientific Awards: National and NSW Awards for 'Excellence in Concrete' (Technology and Innovation) from the Concrete Institute of Australia Churchill Fellowship for Digital Construction and 3D Printing sponsored by AVJennings Dr. Kashani serves as Co-Chair of the cement and concrete working group at MECLA and contributes to RILEM and ASTM committees. His email is ali.kashani@unsw.edu.au , and his office is located in the Civil Engineering Building (H20), Level 2, Room CE204, UNSW.
Robert Dodds Jr.مشاهده پروفایل
استاد پژوهش
Robert Dodds Jr. is a Research Professor in the Department of Civil and Environmental Engineering at the University of Tennessee, Knoxville, within the Tickle College of Engineering. His work is centered on fracture mechanics, computational modeling of crack growth, and material failure in advanced alloys and functionally graded materials. His research interests include: Fracture and failure analysis in ductile and brittle materials Cohesive zone modeling and delamination in aluminum-lithium alloys 3D finite element modeling of crack propagation under small-scale yielding Thermomechanical and cyclic plasticity modeling Fracture in functionally graded materials with mixed-mode loading The analysis of his publications from 2002 to 2018 reveals a strong focus on computational fracture mechanics, particularly on cohesive models, T-stress effects, and delamination in aerospace-grade materials. His work bridges experimental validation with high-fidelity simulations, emphasizing engineering applications in structural integrity. His scientific awards include: National Academy of Engineering George R. Irwin Medal (ASTM) Fracture Mechanics Medal (ASTM) Nathan M. Newmark Medal (ASCE) Walter L. Huber Award (ASCE) Fellow, Engineering Mechanics Institute (ASCE) Dr. Dodds has collaborated extensively with researchers such as C. Ruggieri, M. Messner, A. Beaudoin, J. Sobotka, and G. Paulino. While no formal list of advisees is provided, his mentorship is evident through co-authored student-level research. He has not mentioned specific grants or funding sources in the provided text. His research likely involves a computational mechanics lab or research group focusing on fracture simulation and material modeling, though no lab name is specified.
Michael J. Neilan is a Professor and Director of Graduate Studies in the Department of Mathematics at the University of Pittsburgh, part of the Dietrich School of Arts and Sciences. His research focuses on computational and applied mathematics, with emphasis on the finite element method, numerical approximations for nonlinear PDEs, and structure-preserving discretizations for incompressible fluid models and surface PDEs. Education: PhD in Mathematics, University of Tennessee, 2009 Research Interests: Computational PDEs, finite element methods, structure-preserving discretizations, incompressible fluid dynamics, surface PDEs, fully nonlinear PDEs (e.g., Monge-Ampère equations, optimal transport), and discontinuous Galerkin methods. Publications Trends: His work bridges theoretical analysis and computational implementation, with key contributions to mixed finite element methods, divergence-free formulations, and numerical techniques for nonlinear PDEs. Recent focus includes Monge-Ampère equations and stability analyses for fluid flow models. Editorial Roles: Managing Editor, Mathematics of Computation Associate Editor, IMA Journal of Numerical Analysis Associate Editor, Calcolo Associate Editor, Journal of Numerical Mathematics Professional Activities: Co-organizer of the Finite Element Circus, a leading conference in finite element theory and applications.
Christian Engwer is a full Professor at the University of Muenster in the Institute for Applied Mathematics, specializing in Analysis and Numerics. He leads the Engwer Group focused on Applications of Partial Differential Equations and is actively involved in the Cells in Motion initiative as a supervisor in the CiM-IMPRS Graduate Programme. His research centers on developing numerical methods for partial differential equations, particularly addressing challenges in complex geometries and multi-physics applications. He specializes in Unfitted Discontinuous Galerkin methods, which allow simulations on complex geometries without requiring domain-fitted meshes. His work spans porous media modeling, biological systems, and bioelectromagnetism applications, with significant contributions to EEG/MEG forward modeling in neuroscience. Analysis of his recent publications reveals a strong focus on model order reduction techniques, stabilized numerical schemes for cut-cell meshes, and applications in bioelectromagnetism. His work demonstrates a consistent trajectory toward developing robust, efficient numerical methods applicable to real-world problems in medical imaging and biological modeling, with increasing emphasis on high-performance computing implementations. Professor Engwer actively supervises doctoral students, with recent completions including Lukas Renelt (2025), Michael Wenske (2021), and Maria Carla Piastra (2019), among others working on topics related to numerical methods and biomedical applications. He leads several major research projects including BrainStorm: Highly Extensible Software for Advanced Electrophysiology and MEG/EEG Imaging (NIH-funded since 2019), multiple EXC 2044 Cluster of Excellence projects through 2025, and the InterKI interdisciplinary teaching program on machine learning and artificial intelligence. His group develops several important software packages including DUNE (Distributed and Unified Numerics Environment), duneuro (for bioelectromagnetism applications), and TPMC (Topology Preserving Marching Cubes). These tools support research in numerical methods and their applications to complex scientific problems.
Philip Cardiff is a Professor in Computational Mechanics at the School of Mechanical and Materials Engineering, University College Dublin. He holds a BE (2008) and PhD (2012) in Mechanical Engineering from UCD. His research focuses on computational mechanics, machine learning, and their integration, with expertise in finite volume methods, fluid-solid interaction, and biomechanics. He leads the Bekaert University Technology Centre and contributes to editorial roles in the Journal of Open Source Software and OpenFOAM Journal . Cardiff has secured grants from ERC, I-Form, and the UCD Energy Institute, addressing challenges in offshore energy, advanced manufacturing, and cardiac xenotransplantation. Education: BE in Mechanical Engineering, University College Dublin (2008) PhD in Development of the Finite Volume Method for Hip Joint Analysis, University College Dublin (2012) Professional Diploma in University Teaching & Learning, University College Dublin Research Interests: Computational mechanics, finite volume methods, and machine learning integration Fluid-solid interaction, biomechanics, and materials science Applications in additive manufacturing, energy systems, and biomedical engineering Grants & Awards: ERC Consolidator Grant (2020–2025) Funded Investigator in I-Form and UCD Energy Institute Principal Investigator in UCD Centre for Biomedical Engineering Teaching & Leadership: Programme Director for MEngSc in Materials Science and Engineering (2018–2023) Coordinates modules in computational mechanics and advanced materials processing Advocates constructivist teaching approaches with active learning strategies Labs & Collaborations: UCD Centre for Mechanics Bekaert University Technology Centre MaREI and I-Form Research Centres
- Numerical Simulation of PDEs
- Summation-by-Parts Methods
- Continuous and Discontinuous Galerkin Schemes
- +۲ مورد دیگر
David Del Rey Fernández is Assistant Professor and Pratt & Whitney Canada Chair in Industrial Artificial Intelligence in the Department of Applied Mathematics at University of Waterloo. His research develops efficient numerical algorithms for solving partial differential equations on high-performance systems. He holds a PhD from University of Toronto and previously worked at NASA Langley Research Center. Research focuses on robust numerical methods, mesh adaptation, and machine learning acceleration. His work includes entropy-stable schemes, summation-by-parts methods, and discretizations for compressible flows. Recent publications address Lyapunov-consistent discretizations and scalable reduced-order modeling.
- Numerical Approximation of Partial Differential Equations
- A Posteriori Error Estimation
- High Order Finite Element Methods
- +۵ مورد دیگر
Mark Ainsworth is a Francis Wayland Professor of Applied Mathematics at Brown University and holds a joint faculty appointment with Oak Ridge National Laboratory. He obtained his PhD from Durham University (1989) and has held prominent roles such as Director of the Centre for Numerical Algorithms and Intelligent Software (2011-2012). His research focuses on numerical analysis, particularly finite element methods for partial differential equations, a posteriori error estimation, and high-performance computing challenges like resiliency on exascale systems. Education: PhD in Mathematics, Durham University, 1989 BSc in Mathematics, Durham University, 1986 Research Interests: Numerical approximation of PDEs A posteriori error estimation and adaptive methods High order finite element methods Resiliency of numerical algorithms on emerging architectures Fractional PDEs and scientific data compression Awards: SIAM Fellow (2014) FIMA (2010) Whitehead Prize (2004) J.L. Lions Prize (2004) Fellow of Royal Society of Edinburgh (2003) Grants & Leadership: Co-PI for ARO MURI on fractional PDEs (2015-2020) Directed NAIS center (2011-2012), a £5M multi-institutional initiative Organized major international conferences on computational mathematics Labs/Teams: Collaborations include Oak Ridge National Lab and international research networks in numerical analysis and scientific computing.
Prof. Joachim Schöberl is a faculty member at TU Wien's Faculty of Mathematics and Geoinformation, leading the Scientific Computing and Modelling research group. His academic career includes roles as a university professor (Univ.Prof.) with engineering and technical doctorates (Dipl.-Ing., Dr.techn.). Research focuses on advanced numerical methods, including finite element methods, computational fluid dynamics, and partial differential equations. He has pioneered high-order schemes for fluid-structure interaction, shell mechanics, and electromagnetic simulations. Notable contributions include the NGSolve finite element library and innovative approaches to curvature approximation in discrete geometry. Recent work emphasizes nonlinear elasticity modeling, fractional diffusion problems, and shape optimization for biomembranes. His team collaborates on projects like metascreen upscaling, micromorphic continuum models, and eddy current simulations in laminated materials. Prof. Schöberl advises PhD students researching mixed finite element methods, fractional operators, and computational mechanics. His lab develops open-source tools for high-performance scientific computing.