Prof. Dr. Martin Kronbichler is a faculty member at the Faculty of Mathematics , Ruhr University Bochum , leading the Numerics group. His research focuses on higher-order finite element methods, multigrid techniques, and high-performance computing for complex fluid and solid mechanics problems. Key Research Areas: Higher-order finite element methods, iterative solvers, multigrid algorithms, exascale mathematical software, and computational fluid dynamics. Notable Projects: EU-funded dealii-X (exascale digital twins), BMBF PDExa (optimized PDE solvers for exascale), and DFG grants for cut-discontinuous Galerkin methods and geometric multigrid. Publications Trends: Recent works emphasize matrix-free operators for hyperelasticity, diffuse-interface models for additive manufacturing, and multigrid smoothers for higher-order elements. Scientific Awards: Recipient of the Humboldt Research Award for his contributions to numerical methods and HPC. Team: Collaborates with researchers like Dr. Shubham Kumar Goswami, Dr. Richard Schussnig, and Natalia Nebulishvili.
Vladimir Kazeev is an Assistant Professor at the Faculty of Mathematics, University of Vienna , where he has held a faculty position since 2019. He also held previous academic appointments as a Szegő Assistant Professor at Stanford University (2017–2019), a postdoctoral researcher at the University of Geneva (2015–2017), and research positions at ETH Zurich (2011–2015), Russian Academy of Sciences (2008–2011), and Moscow Institute of Physics and Technology (2009). His research focuses on adaptive, data-driven numerical methods for differential equations, nonlinear low-parametric approximation, and numerical linear algebra. His work intersects computational mathematics, tensor methods, and high-dimensional problem-solving, particularly in the context of partial differential equations (PDEs) and stochastic modeling. The 15 most recent publications reveal a strong emphasis on quantized tensor-structured methods for PDEs, low-rank approximations, and high-dimensional numerical analysis. His research spans theoretical advancements in tensor decomposition, practical applications in chemical reaction networks, and novel discretization techniques for multiscale and degenerate diffusion problems. Scientific awards include the prestigious ETH Medal for outstanding doctoral theses (2016) Russian Academy of Sciences Medal for outstanding student works in mathematics (2011) Advising and teaching activities include supervising Jason Zhu (Stanford, 2019) and Simon Etter (ETH Zurich, 2014), as well as teaching advanced courses in tensor methods, numerical analysis, and PDEs at the University of Vienna, Stanford University, and the University of Geneva. His service to the community includes peer review for 15+ journals and co-organizing minisymposia at SIAM meetings.
Olaf Steinbach is a University Professor (Univ.-Prof.) at the Institute of Applied Mathematics at Graz University of Technology. His academic career spans over three decades with continuous research activity from 1992 to the present, including publications scheduled for 2026. He serves as a project manager for several research initiatives including the Special Research Area (SFB) F90 Computational Electric Machine Laboratory, which runs from 2022 to 2026. Professor Steinbach's research interests primarily focus on Numerical Analysis and Computational Mathematics . His work centers around developing and analyzing advanced numerical methods, particularly Finite Element Methods (FEM) and Boundary Element Methods (BEM), for solving partial differential equations (PDEs) and optimal control problems. His research spans both theoretical aspects (such as error analysis, stability, and convergence) and practical applications (including electric machines, electromagnetics, and biomechanics). He has made significant contributions to space-time finite element methods, which treat time as an additional dimension in the discretization process, leading to more robust and efficient solvers for time-dependent problems. Analysis of his recent publications (2021-2026) reveals a strong focus on optimal control problems governed by partial differential equations, with particular emphasis on elliptic, parabolic, and hyperbolic PDEs. His work demonstrates a consistent pattern of developing robust numerical methods with rigorous error analysis, often incorporating regularization techniques to handle challenging constraints. The applications span computational electromagnetics (particularly electric machines), fluid dynamics, and wave propagation problems. His research increasingly incorporates advanced computational techniques including parallel computing and isogeometric analysis. Professor Steinbach has supervised numerous doctoral students and has been actively involved in organizing academic events, including summer schools on Boundary Element Methods. His collaborative network extends across multiple disciplines and institutions, reflecting the interdisciplinary nature of his work in computational mathematics. His research has been supported through multiple significant projects including DK-W1244 Doctoral Program on Partial Differential Equations, the EU CASOPT project on optimization of industrial devices, and the ongoing Special Research Area on Computational Electric Machine Laboratory. These projects demonstrate his leadership in establishing research frameworks that bridge theoretical mathematics with practical engineering applications. Professor Steinbach maintains an active research group within the Institute of Applied Mathematics, collaborating closely with researchers in computational engineering, electrical engineering, and biomechanics. His work on the Computational Electric Machine Laboratory represents a particularly strong interdisciplinary effort combining mathematical theory with electrical engineering applications.
Ana Maria Alonso Rodriguez is a Full Professor of Numerical Analysis at the Department of Mathematics, University of Trento. She holds a PhD in Applied Mathematics from Universidad Complutense de Madrid (1993) and has held academic positions across Italy and Spain since 1990. Her research focuses on numerical methods for partial differential equations, computational electromagnetism, finite element methods, and domain decomposition techniques. She has organized international workshops and minisymposia, including the 2022 Oberwolfach workshop on Hilbert Complexes and the 2018 ICOSAHOM conference session on high-order methods. Her work bridges numerical analysis, topology, and applied electromagnetism, with recent contributions to Whitney finite elements and discrete potential theory. Education: PhD in Applied Mathematics, Universidad Complutense de Madrid (1988-1993) Licenciatura en Ciencias Matematicas, same institution (1982-1987) Research emphasizes high-order discretizations for electromagnetic problems, leveraging finite element exterior calculus and graph-based decomposition techniques. Recent work (2024) advances tree-cotree methods for curl operator spectra and Whitney form interpolation. She actively collaborates with international institutions like the CI2MA in Chile and the Laboratoire J. A. Dieudonné in France. Teaching includes courses on numerical PDEs, finite elements, computational electromagnetism, and MATLAB-based numerical analysis at both undergraduate and PhD levels. She has supervised numerous courses in Italy and Spain since 2000, integrating practical software tools like FreeFem and MODULEF into instruction.
Prof. Dr.-Ing. Gerhard Müller is a Full Professor at the Chair of Structural Mechanics within the TUM School of Engineering and Design at Technical University of Munich (TUM). Since 2004, he has held this distinguished position, and since 2014, he has served as Executive Vice President for Academic and Student Affairs at TUM. His research focuses on structural dynamics and vibroacoustics, with specific expertise in dynamic soil-structure interaction, sound radiation analysis, and seismic risk assessment. Professorship: Structural Mechanics University: Technical University of Munich School: TUM School of Engineering and Design Department: Chair of Structural Mechanics in Civil Engineering Prof. Müller's research spans multiple domains, including: Structural Dynamics : Examining building and vehicle vibrations, seismic soil-structure interaction, and advanced model order reduction techniques Vibroacoustics : Investigating sound radiation from vibrating structures and developing acoustic metamaterials for noise control Computational Methods : Pioneering hybrid deterministic-statistical approaches, Wave Based Methods (WBM) for saturated elastodynamic structures, and parametric model order reduction His recent publications demonstrate expertise in: Wave propagation analysis in poroelastic media Bayesian parameter updating for structural models Acoustic metamaterials for vibration control Advanced numerical methods for seismic risk assessment Hybrid ITM-FEM approaches for soil-structure interaction Energy flow analysis in timber structures Awarded the Spindler Prize in 1984 , Prof. Müller also holds significant academic leadership roles: President of European Association for Structural Dynamics (EASD) Chairman of Bavarian-French University Center (BayFrance) Active member of ASIIN accreditation agency and Bavarian Chamber of Engineers Previously served as Dean of Civil Engineering and Surveying at TUM (2010-2014) He leads the Structural Dynamic Lab (formerly Vibroacoustics Lab) and has developed interactive web apps for engineering education. His work bridges theoretical advancements with practical applications in construction acoustics, transportation noise control, and geothermal energy infrastructure analysis.
Dr Dongbin Wei is an Associate Professor at the School of Mechanical and Mechatronic Engineering , University of Technology Sydney (UTS), with a career spanning academia and industry. He holds a PhD in Materials Processing Engineering from the University of Science and Technology Beijing (2001) and academic appointments from 2005–2012 at the University of Wollongong (Research Fellow to Lecturer) and 2013–2017 at UTS (Senior Lecturer) before his promotion to Associate Professor in 2018. His research lies at the intersection of Mechanical Engineering , Manufacturing Engineering , and Materials Processing , focusing on: Ultrasonic Additive Manufacturing (UAM) Micro Metal Forming and Size Effects Tribology and Lubrication Numerical Simulations of Material Processing Composite Material Fabrication Key contributions include: Development of the Springback Path–Displacement Adjustment (SP-DA) method for stamping accuracy Advancements in femtosecond laser texturing for silicon wettability control Studies on nanolubrication in hot rolling Optimization of micro-deep drawing parameters He has secured competitive grants from the Australian Research Council (ARC) and industry partners like Weir Minerals Australia Ltd , including projects on: Revolutionizing mineral separation via additive manufacturing Super high-speed grinding technologies Mechanics of micro composite drill fabrication As a lead supervisor, he guided the 2022 thesis 'Creation and Validation of 3D Printable Mineral Separation Spiral' . His work bridges theoretical analysis, computational modeling (FEM/FEA), and practical validation in advanced manufacturing systems.
Dirk Praetorius is a Professor of Numerics of Partial Differential Equations (PDEs) at the Technische Universität Wien (TU Wien) , affiliated with the Institute for Analysis and Scientific Computing (ASC) within the Faculty of Mathematics and Geoinformation . He leads the research group on Numerics of PDEs and has held various leadership roles, including Institute Director (since 2020) and head of the Numerics research area. His work focuses on numerical methods for PDEs, including Finite Element Methods (FEM), Boundary Element Methods (BEM), adaptive algorithms, and computational micromagnetics. Education and Career: Praetorius earned his Diplom in Mathematics (2000) and PhD in Applied Mathematics (2003) from TU Wien, followed by a Habilitation in Numerical Analysis (2005). He has been a faculty member at TU Wien since 2005, progressing from Assistant Professor to full Professor in 2017. He has also held visiting positions at institutions such as the University of Jyväskylä and RICAM (Linz). Research Interests: His research spans numerical analysis, adaptive FEM/BEM, a-posteriori error estimation, matrix compression, and computational micromagnetics. He has contributed to modeling spin dynamics, magnetic skyrmions, and multiscale systems. His work emphasizes efficient algorithms for large-scale problems and optimal computational complexity. Awards and Editorial Roles: Praetorius received the TU Best Teacher Award (2021) and TU Best Lecture Award (2019). He serves as Senior Editor for Computational Methods in Applied Mathematics (CMAM) and on the editorial board of Applied Numerical Mathematics (APNUM) . He co-founded the outreach initiative TUForMath to promote mathematics education. Grants and Projects: He leads or co-leads several research projects funded by the Austrian Science Fund (FWF), including the collaborative SFB "Taming Complexity in Partial Differential Systems" (2017–2025) and international collaborations with Germany. His work addresses topics like functional error estimates, nonlinear PDEs, and computational design of magnetic devices. Labs and Teams: He contributes to the ASC Institute and coordinates interdisciplinary projects involving computational physics and engineering. His team develops software tools like MooAFEM and Commics for micromagnetic simulations.
Jonas Faleskog is a Professor in the Department of Materials and Structural Mechanics at KTH Royal Institute of Technology. His research focuses on mathematical modeling of material deformation and failure mechanisms, particularly in metallic and polymeric materials. Key areas include ductile and brittle fracture analysis, fracture mechanics, and computational modeling of material behavior under various stress conditions. He leads a research group collaborating internationally to develop models describing material failure at microscopic scales. Faleskog teaches courses such as Fracture Mechanics (SE2139) and Modeling in FEM (SE2860), emphasizing practical applications of theoretical models. His work spans experimental and numerical methods, addressing challenges in material heterogeneity, porosity effects, and environmental degradation. Notable contributions include advancements in weakest-link modeling for brittle failure, probabilistic fracture models, and strain gradient plasticity analysis. His research bridges material science, applied mechanics, and numerical methods to optimize material utilization in engineering systems like reactor tanks, aircraft, and vehicles. Key collaborations involve international teams exploring microstructural influences on fracture behavior. While no specific awards are listed, his extensive publication record reflects sustained contributions to mechanical and materials engineering.
Stephane Cotin is a Research Director at Inria and leader of the MIMESIS team, specializing in real-time physics-based medical simulations. His work focuses on surgical training, planning, and image-guided therapy, with over 200 scientific articles and the development of the open-source SOFA framework. He co-founded InSimo, Twinical, and EVE, and previously held roles at Harvard Medical School and Mitsubishi Electric Research Lab. Cotin’s research bridges imaging, robotics, and medicine to improve healthcare outcomes, emphasizing patient-specific biophysical modeling and real-time computation. His awards include the Academy of Sciences Award (2018) and Dirk Bartz Medical Prize (2015). He has advised numerous PhD students and led projects like MediTwin and PREMYOM, advancing digital twin technologies for precision medicine.
Alireza Yaseri serves as an Adjunct Assistant Professor in the Department of Civil Engineering within Smith Engineering at Queen's University. He maintains a dual affiliation with the GeoEngineering Centre, a leading research institute at Queen's specializing in geotechnical and geoenvironmental challenges, where he contributes to advanced computational modeling initiatives. Education: PhD in Geotechnical Engineering, Université Laval (2021) MSc in Geotechnical Engineering, Shiraz University (2012) Dr. Yaseri's research program centers on computational geomechanics with emphases on seismic soil-structure interaction, railway-induced vibrations, and constitutive modeling of granular materials. His work bridges theoretical mechanics and practical infrastructure challenges through advanced numerical techniques, particularly hybrid FEM-SBFEM implementations for dynamic analysis of earth dams, canyon systems, and transportation corridors. He investigates nonlinear soil behavior under monotonic/cyclic loading and develops predictive models for vibration propagation in complex geological settings. Analysis of his publication trajectory (2014-2024) reveals consistent innovation in computational geotechnics, with recent work focusing on 2.5D/3D modeling of train-induced vibrations and sophisticated sand constitutive frameworks. His 2024 publications demonstrate dual expertise in railway vibration prediction methodologies and critical-state soil mechanics, while his earth dam-canyon system analyses from 2020-2022 established foundational approaches for seismic amplification in flexible geological formations. As an active member of Queen's GeoEngineering Centre, Dr. Yaseri collaborates on interdisciplinary projects addressing infrastructure resilience, with particular relevance to dam safety and transportation geotechnics in seismic zones. His technical leadership in scaled boundary methods contributes to the center's reputation for computational innovation in geomechanics.
Tiina Salmi is an Academy Research Fellow specializing in superconductivity and high-field magnet systems. She holds a Doctor of Science (Technology) in Electrical Engineering (2015) and a Master of Science in the same field (2009). Her research focuses on quench protection systems, superconducting magnet design for particle accelerators (e.g., Future Circular Collider, Muon Collider, and LHC upgrades), and material behavior under extreme conditions. Affiliations: Academy of Finland, collaborating with institutions like CERN and LARP. Key Projects: FCC dipole development, Muon Collider storage ring magnets, and HTS tape mechanical analysis. Editorial Roles: Editorial board member for IEEE Transactions on Applied Superconductivity (2020–present). Research Interests Her work addresses critical challenges in superconducting magnet technology, including quench dynamics, thermal management, and high-field stability. She employs computational models (e.g., FEM simulations) and AI-driven approaches to optimize magnet performance and safety. Recent focus areas include: Superconducting materials (Nb 3 Sn, ReBCO, HTS) under mechanical/thermal stress CLIQ protection systems for FCC-hh dipoles Surrogate models for predicting heater delays Mechanical behavior of 2G HTS tapes Grants & Activities Active in international collaborations like the Muon Collider Project and the LARP (LHC Accelerator Research Program). Conducted over 80 peer-reviewed publications (2011–2025) and presented at conferences since 2013. Her work aligns with SDGs 9 (Industry, Innovation) and 12 (Sustainable Consumption). Future Work Ongoing projects include optimizing superconducting magnets for next-gen colliders and advancing AI applications in magnet design. Exploring sustainable materials and cost-effective high-field magnet solutions for future accelerators.
Professor Mohan Lal Kolhe is a distinguished academic at the University of Agder , serving as a Full Professor in Smart Grid and Renewable Energy within the Faculty of Engineering and Science and the Department of Engineering Sciences . With over three decades of international academic experience, he has held positions at prestigious institutions including University College London, University of Dundee, and Hydrogen Research Institute in Canada. His career spans technical innovation, policy development (e.g., as a member of South Australia’s Renewable Energy Board), and extensive research leadership in sustainable energy systems. Research Leadership : Focus on Smart Grid integration, Electric Vehicles, Hydrogen Energy, Solar/Wind Systems, and Techno-Economic Energy Analysis. Global Recognition : Listed in the top 2% of scientists worldwide (2020-2023) by Stanford University, with 10 publications averaging 200+ citations. Recent publications emphasize advanced optimization techniques for renewable integration, EV charging infrastructure, hydrogen production, and power system stability. His work has secured competitive funding from entities like the Norwegian Research Council and EU programs. Awards and Expert Roles : Top 2% Global Scientist (Stanford, 2020-2023) Highly Cited Researcher (Top 10 publications, 200+ avg. citations) Expert evaluator for European Commission, Royal Society London, EPSRC, and Cyprus Research Foundation He actively contributes to international conferences as keynote speaker and editorial board member, with leadership roles in research groups like Autonomous and Cyber-Physical Systems and Energy Systems .
Maria Garlock is the Daniel Tsui Professor in Engineering at Princeton University, serving as Co-Director of the Program in Architecture and Engineering and Head of Forbes College. Her roles also include membership in the Executive Committee of the Council on Science and Technology, Associated Faculty in the School of Architecture, and Associated Faculty in the Program in Latin American Studies. Garlock holds a PhD in Structural Engineering (Lehigh University, 2002), an MS in Civil Engineering (Cornell University, 1993), and a BS in Civil and Environmental Engineering (Lehigh University, 1991). Her research focuses on resilient structural design for extreme hazards like fires, earthquakes, and storm surges. She explores both isolated and cascading multi-hazard scenarios while also analyzing historical structural designs (e.g., Félix Candela’s thin-shell concrete umbrellas) and improving STEM education for non-technical majors through innovative teaching methods, including MOOCs and scale model exhibitions. Recent work emphasizes coastal defense systems using hyperbolic-paraboloid forms and steel-concrete girder performance under shear stress. Garlock has received notable honors including the ASCE SEI Fellowship (2016 T.R. Higgins Lectureship), President’s Award for Distinguished Teaching (2012), and the Emerson Electric Co. Faculty Advancement Award (2006). In education and grants, she teaches courses like Structures and the Urban Environment and Advanced Design of Steel/Concrete Structures , and has secured government funding for STEM literacy initiatives. Her research collaborations include the BRITE Pivot project and studies on Cuba’s historic National School of Ballet domes. She also leads efforts in deploying kinetic umbrellas as flood barriers and advancing probabilistic models for fire fragility in multi-hazard contexts. Garlock’s work bridges engineering and art, exemplified by her preservation studies of Candela’s architectural masterpieces and pedagogical innovations that emphasize creativity in structural design.
Yves Bourgault is a Full Professor in the Department of Mathematics and Statistics at the University of Ottawa. He holds a MSc and PhD from Laval University. His research focuses on computational fluid dynamics, numerical methods, finite element techniques, and continuum mechanics modeling, with applications in cardiac electrophysiology and ecological systems. Dr. Bourgault has supervised several graduate students, including Edward Boey (co-supervised), Sana Keita, Saint-Cyr Koyagurebo-Ime, and Kak Choon Loy. His work integrates advanced numerical techniques to address complex problems in biomedical engineering, environmental science, and mathematical physics. Key methodologies include finite element methods, deferred correction schemes, and anisotropic mesh adaptation. His research group is part of the Applied Mathematics division at the University of Ottawa, emphasizing interdisciplinary applications. Recent work explores climate change impacts on ecological systems, cardiac tissue modeling using high-resolution MRI data, and robust numerical methods for reaction-diffusion equations. Publications span topics such as bidomain models for cardiac electrophysiology, fluid-structure interaction in heart mechanics, and mathematical modeling of fuel cells. His contributions bridge theoretical numerical analysis with real-world biomedical and environmental challenges.
Stefan Hallström is an Associate Professor in Lightweight Structures at KTH Royal Institute of Technology's Aeronautical and Vehicle Engineering School, affiliated with the MATERIAL AND STRUCTURAL MECHANICS department. He specializes in composite materials, structural mechanics, and lightweight design, focusing on aerospace and automotive applications. His research explores advanced composites, sandwich structures, and material behavior under various loading conditions. Hallström teaches courses including Lightweight Design (SD2432), Lightweight Structures and FEM (SD2411), and supervises degree projects in Lightweight Structures and Solid Mechanics. He has published extensively on topics like 3D-woven composites, damage tolerance, and mechanical reinforcement strategies, with over 90 peer-reviewed articles. His work emphasizes material characterization, finite element modeling, and practical applications in structural engineering. Key research trends include optimizing composite joint performance using metal inserts, analyzing moisture effects on composite laminates, and developing frameworks for modeling 3D textile architectures. His contributions address challenges in aerospace materials, energy absorption in beams, and improving simulation accuracy for molded composites. Hallström collaborates on projects involving novel instrumented test rigs for polymer composites and advanced manufacturing techniques for structural reliability. His expertise bridges theoretical mechanics with practical engineering solutions, influencing both academic research and industrial applications.
