Erol Lale is a Lecturer in the Civil Engineering Department at Istanbul Technical University, specializing in Structural Mechanics, Reinforced Concrete Structures, and Numerical Modeling. He holds a PhD in Structural Engineering from the same institution, with prior academic roles including Research Assistant since 2005. His research focuses on advanced numerical techniques such as Lattice Discrete Particle Modeling (LDPM), Isogeometric Analysis, and High-Order Microplane Models to study concrete behavior under dynamic loading, size effects, and fracture mechanics. He has contributed to over 20 peer-reviewed publications, including works on reinforced concrete columns, damage localization algorithms, and multiscale analysis of geotechnical systems. Teaching responsibilities include courses like 'Reinforced Concrete II' and 'Prestressed Concrete' at the undergraduate level. His work integrates computational mechanics with experimental validation, addressing challenges in structural integrity and material failure under extreme conditions.
Malith Prasanna is a Visiting Professor at Aalto University, affiliated with the Department of Energy and Mechanical Engineering and Marine and Arctic Technology . He holds a Doctor of Science (Technology) in Mechanical Engineering (awarded 28 Aug 2023). His research focuses on ice mechanics, discrete element modeling, and offshore engineering challenges in arctic environments. Education: Doctor of Science (Technology), Aalto University (2023) Research interests include ice block failure mechanisms, numerical simulations of ice-structure interactions, and experimental studies on saline ice properties. His work contributes to sustainable development goals related to climate action and infrastructure resilience. Collaborations span international projects on arctic technology and offshore wind farm design. He has published widely on topics like DEM-CFD methods and ice rubble behavior. Labs/Teams: Engaged with Aalto's Marine and Arctic Technology group and Energy and Mechanical Engineering departments.
Professor Jian Zhao is a faculty member in the Department of Civil & Environmental Engineering at Monash University, specializing in Rock Mechanics, Geophysics, and Geothermal Energy. He holds editorial roles in journals such as the International Journal of Rock Mechanics and Mining Sciences and has led significant research projects funded by organizations like the Australian Research Council. His work focuses on rock dynamics, underground construction, and advanced material testing techniques. Notable achievements include developing novel methods for rock fracturing via microwave treatment and pioneering numerical models for rock fracture under dynamic loads. Professor Zhao is an ISRM Fellow and has conducted collaborative research with global institutions. His projects address challenges in geothermal energy extraction and tunneling safety, with a strong emphasis on sustainability and engineering innovation. Research interests span across Dynamic rock behavior under multiaxial loading, Microwave-enhanced rock breakage, Fracture mechanics in heterogeneous rock formations, Advanced numerical modeling (FDEM, DEM), Geothermal energy applications, Seismic response of rock joints. Recent studies include innovations in automated excavation frameworks, thermal-stress-pore pressure coupled testing systems, and insights into induced seismicity through photoelastic techniques. Over 373 publications and active grants reflect his impactful contributions to civil and environmental engineering.
Dr. Xilin Xia is an Assistant Professor in Resilience Engineering at the University of Birmingham's School of Engineering. He specializes in computational modeling of natural hazards and their impacts, focusing on flood risk management and infrastructure resilience. His research integrates high-performance computing, machine learning, and hydraulic/hydrological modeling. Education: BEng in Civil Engineering, Wuhan University (2010) MEng in Road and Railway Engineering, Wuhan University (2012) PhD in Water Resources, Newcastle University (2017) Research Interests: Development of open-source tools like HiPIMS for flood modeling Risk-based flood forecasting systems (e.g., FHIM-India project) GPU-based parallel computing for environmental applications Machine learning for hazard risk analytics Funding & Awards: Over £1M in grants as PI/Co-I from UKRI, Met Office, NERC Fellow of the Higher Education Academy (2020) Teaching: Leads 'Water Engineering and Management' module at University of Birmingham. Software Contributions: HiPIMS: High-Performance Integrated hydrodynamic Modelling System PyPIMS: Python interface for HiPIMS
Xiangxiong Zhang is an Associate Professor in the Department of Mathematics at Purdue University, specializing in numerical analysis, scientific computing, and applied mathematics. His research focuses on numerical methods for partial differential equations, optimization algorithms, and computational fluid dynamics. He holds a PhD and has been actively involved in teaching graduate and undergraduate courses, including numerical PDEs, optimization, and linear algebra. His work emphasizes high-order numerical methods such as discontinuous Galerkin schemes, finite element methods, and spectral element methods, with applications in fluid dynamics, plasma physics, and compressible flow simulations. Notable contributions include positivity-preserving limiters, bound-preserving schemes, and Riemannian optimization techniques for matrix constraints. Zhang collaborates with researchers in computational mathematics and has published extensively in top journals like Journal of Computational Physics and SIAM Journal on Scientific Computing . His research also addresses challenges in GPU-accelerated computing for large-scale scientific simulations.
Christopher Hulme is an Associate Professor of Powder Metallurgy and Rapid Solidification at the Department of Materials Science and Engineering, KTH Royal Institute of Technology. His research focuses on understanding the physical mechanisms of metal powder atomization, including droplet formation and solidification, and linking production conditions to powder properties. He employs computational fluid dynamics, stochastic modelling, and thermodynamic analysis, supported by experimental techniques like shadowgraphy and water modelling. His work also examines powder behavior, developing new testing methods for flow and spreading properties, and explores sustainability and equality in engineering education. Key research areas include atomization process optimization, powder flow dynamics, additive manufacturing feedstock development, and X-ray source innovation. His teaching responsibilities span courses such as Casting Processing, Material Selection, and Metal Powder Characterization, emphasizing practical methods and ethical engineering practices. He has contributed to over 50 peer-reviewed publications, with recent work addressing rotating anode X-ray erosion, nickel silicide alloy optimization, and humidity effects on steel powder flowability. Teaching Roles: Course responsible for Metal Powder Production, Materials Processes I, and Material Selection Research Themes: Atomization Science, Powder Behavior Modelling, Sustainable Manufacturing
Prof. Duc Nguyen is a Professor in the Department of Civil & Environmental Engineering at Old Dominion University (ODU), affiliated with the Batten College of Engineering and Technology. His expertise spans Computational Mechanics, Finite Element Analysis (FEA), Structural Dynamics, and Parallel Computing. He has held numerous prestigious roles, including NASA-ASEE Fellowships and the 2010 ODU Shining Star Award. Nguyen holds a Ph.D. from the University of Iowa (1982), M.S. from the University of California (1976), and B.S. from Northeastern University (1974). Research focuses on large-scale algorithms for parallel supercomputing, design sensitivity analysis, sparse linear solvers, and multiphysics CAD-based optimization. He has led grants totaling over $2 million, including projects on numerical methods, engineering education, and structural analysis. Notable publications address parallel finite element methods, structural/acoustic coupling, and optimization using genetic algorithms. Awarded honors include recognition for citation impact (2004), teaching excellence (2001), and computational performance (1989). His work bridges computational efficiency with engineering applications, emphasizing interdisciplinary collaboration. Current research explores MPI-enabled algorithms, multi-hazard risk assessment, and coastal infrastructure resilience.
Emanuel Gull is an Assistant Professor in the Department of Physics at the University of Michigan, Ann Arbor. His research focuses on quantum many-body theory, strongly correlated electron systems, and computational methods for condensed matter physics. He has held academic positions including a postdoc at Columbia University and a junior group leader role at the Max Planck Institute. His work emphasizes numerical methods like quantum Monte Carlo, dynamical mean-field theory (DMFT), and tensor network approaches. Education: PhD in Theoretical Physics from ETH Zurich (2008), undergraduate studies at ETH Zurich (2005). His research interests include Hubbard model simulations, analytic continuation of Green's functions, and developing computational frameworks like Green/WeakCoupling for ab initio many-body calculations. Key achievements include the 2013 Nevill Mott SCES Prize for contributions to correlated electron systems, a DOE Early Career Award (2013), and a Sloan Fellowship (2014). He has pioneered methods for non-equilibrium dynamics, steady-state quantum systems, and integrating high-performance computing into materials science. Grants include NSF-BSF funding for tensor train methods in quantum impurity solvers. His work often involves collaborations on frameworks like TRIQS and Elements for embedding theories. Current research explores quantum-centric supercomputing, excitonic phenomena in van der Waals magnets, and symmetry-adapted algorithms for large-scale simulations.
Stefano Berrone is a Full Professor in the Department of Mathematical Sciences "G.L. Lagrange" (DISMA) at the Polytechnic University of Turin, where he also holds key administrative roles as Vice-Rector for Quality and President of the University Quality Assurance Committee. He is a member of the Interdepartmental Center SmartData@PoliTO and the University Committee for Research, Technology Transfer and Services to the Territory. Department of Mathematical Sciences "G.L. Lagrange" (DISMA), Polytechnic University of Turin Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory Scientific leadership in EU, national, and commercial research projects Teaching assignment at Turin Polytechnic University in Tashkent (2012–2014) His research lies at the intersection of numerical analysis, scientific computing, and machine learning, with a strong emphasis on the development and analysis of advanced numerical methods. He specializes in the Virtual Element Method (VEM), mesh adaptivity and generation, high-performance computing (HPC), physics-informed neural networks, and deep learning for engineering problems. His work contributes to computational engineering, data science, and sustainable development (aligned with SDGs 4, 9, and 13). He leads multiple research groups and projects focused on numerical optimization, PDE discretization on polygonal meshes, and simulation of complex physical systems. The recent publications (2023–2025) reveal a strong trend toward hybrid computational methodologies, combining classical numerical techniques like VEM with machine learning, particularly physics-informed and neural-approximated models. There is a clear focus on stabilization-free formulations, mesh optimization, and applications in energetic materials, fluid dynamics, and subsurface modeling. The work spans high-impact journals in scientific computing, computational mechanics, and algorithms. Scientific Participations and Memberships: Full Member, SIAM (Society for Industrial and Applied Mathematics) (2020–present) Full Member, Italian Society of Applied and Industrial Mathematics (2020–present) Full Member, Italian Mathematical Union (2020–present) Full Member, National Institute of Higher Mathematics - National Group for Scientific Computing (1999–present) Research Leadership and Grants: Scientific Responsible, In-Deep (EU Horizon Europe, 2024–2028) Scientific Responsible, PYGEOM (PRIN, 2023–2026) Scientific Director of Structure, SHIMMER (Clean Hydrogen JTI, 2023–2026) Scientific Director of Structure, HPC-Spoke 6 (PNRR, 2022–2025) Scientific Responsible, AdPolyMP (PRIN, 2022–2025) Scientific Responsible, Virtual Element Methods: Analysis and Applications (PRIN, 2019–2022) Scientific Responsible, IDEA (PRIN, 2013–2015) Scientific Responsible, AIRTOLYMI (Regional, 2007–2011) Scientific Responsible, Engine Health Monitoring (Commercial, 2024–2025) Advising and Doctoral Supervision: Supervising multiple PhD students in Pure and Applied Mathematics and Mathematical Sciences Member of Doctoral Colleges in Pure and Applied Mathematics at Politecnico di Torino and University of Turin (2013–2023) Key advisor in research areas including energetic materials, computational fluid dynamics, and numerical PDEs Laboratories and Research Groups: Numerical Analysis and Scientific Computing (DISMA) Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory Lead in developing computational tools like HEMSim for energetic materials simulation
Alexander Rieder is a Research Fellow and University Assistant in Computational Mathematics at TU Wien's Institute of Analysis and Scientific Computing. His work focuses on numerical methods for partial differential equations, particularly boundary element methods (BEM), finite element methods (FEM), and their applications in wave propagation and fractional calculus. He holds a PhD from TU Wien (2017) and has held postdoctoral positions at TU Wien and the University of Vienna. Notable achievements include the TU Best Paper Award 2020 for his contributions to numerical analysis. Education: Bachelor of Science (BSc), Mathematics, TU Wien (1989) Diploma in Mathematics, TU Wien (2011) Doctorate (Dr.techn.), TU Wien (2017) Research Interests: Alexander specializes in fractional differential operators , hp-adaptive FEM/BEM , and time-domain boundary integral equations . His projects include developing open-source libraries for advanced BEM simulations and studying wave propagation in composite media. Recent work emphasizes convolution quadrature for semigroups and nonlinear wave equations. Teaching: Current courses include Numerics of Partial Differential Equations and Numerical Computation . He oversees seminars on differential equations and computational mathematics, emphasizing practical implementation and theoretical rigor. Projects: Leading the Advanced BEM for Wave Propagation initiative, he designs algorithms to reduce computational effort while improving accuracy in wave simulations. The project also develops an open-source software library for broader academic use.
Alec Jacobson is an Associate Professor in the Department of Computer Science at the University of Toronto, with a courtesy appointment in Mathematics. He holds the Canada Research Chair in Geometry Processing and serves as a Senior Research Scientist at Adobe Research Toronto. Located at the Bahen Centre, he leads research in computer graphics and geometry processing as part of the Dynamic Graphics Project lab. His research focuses on Geometry Processing , Discrete Differential Geometry , and Computer Graphics , with applications in 3D reconstruction, computational fabrication, and neural representations. Key areas include mesh processing algorithms, physics-based simulation, and differentiable rendering techniques that bridge theoretical foundations with practical implementations. Recent publications demonstrate strong trends in neural field optimizations, robust 3D reconstruction, and physics simulation. His team frequently combines machine learning with geometric methods to solve challenging inverse problems in computer vision and graphics, with consistent innovation in computational efficiency and mathematical foundations. Scientific Awards: Canada Research Chair in Geometry Processing AXL Faculty Fellow Best Paper Honourable Mention (SGP 2024) Best Paper Award (SIGGRAPH 2022) Test of Time Award (SIGGRAPH 2024) He leads the Third Space research group advising numerous graduate students and postdocs. Current research infrastructure includes collaborations with the Vector Institute and Adobe Research, supported by grants focused on geometric algorithms and neural representations.
Francesco Mirko Massaro serves as an Associate Professor in the Department of Structural Engineering at the Norwegian University of Science and Technology (NTNU), Faculty of Engineering. His academic role encompasses advanced research in timber structural systems and dedicated teaching in timber engineering disciplines. His research program centers on wood mechanics and structural performance, with specialized expertise in compression perpendicular to grain, long-term behavior of timber elements, and innovative timber bridge systems. Key investigation areas include glued-laminated timber (GLT), cross-laminated timber (CLT), stress-laminated decks, and connection mechanics, employing rigorous experimental testing combined with finite element modeling to advance structural understanding. Analysis of his 15 most recent publications reveals significant focus on structural serviceability (2022-2023), compression behavior characterization (2023-2024), and next-generation timber systems for multistorey construction (2025). Critical research trajectories include Eurocode 5 fatigue rule development, geometric effects on timber performance, and pre-stressing mechanics for bridge applications, demonstrating consistent progression toward practical implementation of timber engineering solutions.
Ying Cai is a prolific researcher with significant contributions across diverse domains of computer science, mathematics, and biomedical applications. Their work spans artificial intelligence, medical imaging, cybersecurity, and computational methods, as evidenced by recent publications in journals like Engineering Applications of Artificial Intelligence and IEEE Transactions on Medical Imaging . Key research areas include lung cancer detection algorithms, distributed filtering under cyber-attacks, and cryptographic protocols. 2025: 9 publications 2024: 18 publications 2023: 8 publications Notable collaborations include work with Yang Zhao, Zeyu Zhang, and Daji Ergu on medical AI applications and computational techniques. Their recent articles demonstrate expertise in: Medical imaging and diagnostic automation Deep learning optimization Secure communication protocols Computational mathematical models Ying Cai's research bridges theoretical rigor with practical implementation across domains like health informatics, network security, and educational technology.
Patrick Joly is a Researcher at ENSTA Paris, affiliated with the Applied Mathematics Unit (UMA). His work focuses on mathematical modeling, numerical analysis, and computational methods for wave propagation in complex media, including electromagnetics, acoustics, and elastodynamics. Current affiliations: ENSTA Paris, Applied Mathematics Unit (UMA), INRIA Research areas: Wave propagation, hyperbolic PDEs, finite element methods, fractal structures, domain decomposition Joly’s recent publications (2025–2024) address stability of time-stepping methods, transparent boundary conditions for fractal trees, and wave behavior in dissipative Lorentz materials. His work combines rigorous mathematical analysis with practical computational techniques. Scientific awards and student advisement details are not explicitly mentioned in the provided data. Joly’s contributions span theoretical frameworks and numerical implementations, particularly in transient wave simulations and scattering problems.
Erik Hulthén is a Professor of Product Development at the Department of Industrial and Materials Science , Chalmers University of Technology. He serves as the Dean of Education at Chalmers' School of EDITI (Electrical Engineering, Medical Engineering, Computer Science Engineering, IT Engineering, and Industrial Economy). His research focuses on mineral processing, process optimization, and environmental engineering within rock material production. 2008 – Young Author award, XXIV International Mineral Processing Congress (IMPC) 2010 – Present: Member of Swedish Aggregate Producers Association (SBMI) Technical Board Recent work explores the environmental impact of quarrying through lifecycle analysis, crushing-screening optimization using Design of Experiments, and implementation of CDIO educational frameworks in raw materials programs. Collaborations span European Commission initiatives like DigiEcoQuarry and industry partnerships with VINNOVA and EIT RawMaterials. His projects include: EPD Berg 3 (Lifecycle EPD tool for aggregates, 2024-2025, VINNOVA) DigiEcoQuarry (Digital sustainable aggregates solutions, 2021-2025, EC) CDIO implementation in European raw materials education (2016-2017, EIT RawMaterials)
