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.
Jennifer C. McIntosh is a Professor and University Distinguished Scholar in the Department of Hydrology and Atmospheric Sciences at the University of Arizona (UA), with a joint appointment in the Department of Geosciences. She is also an Adjunct Professor at the University of Saskatchewan. Her academic roles include teaching advanced hydrogeology courses and advising graduate students. She holds a BA in Geology-Chemistry from Whitman College, MS and PhD in Geology from the University of Michigan, and completed a postdoctoral fellowship at Johns Hopkins University. Her research focuses on the interplay between hydrology, geochemistry, and microbiology in the Earth’s crust, spanning micro-to-macro scales. Key projects include studying subsurface fluid dynamics, microbial methane production, and the impacts of climate and human activities on groundwater systems. She has applied these methods to critical zones, sedimentary basins, and oil/gas reservoirs, with fieldwork in the Colorado Plateau, Paradox Basin, and Western Canada. McIntosh has received numerous awards for research and teaching, including the Blitzer Award for Excellence in Teaching Physics-Related Sciences (2019) and the UA Distinguished Scholar Award (2017). She actively serves on national committees for the US EPA, National Academies, and Nuclear Waste Technical Review Board. Education: BA (Whitman College), MS/PhD (University of Michigan), Postdoc (Johns Hopkins University) Notable Awards: GSA Fellow (2019), CIFAR Earth 4D Program (2019), Morton K. Blaustein Fellowship (2004) Labs/Teams: Jemez River Basin Critical Zone Observatory, Siljan Impact Structure Research Group Future Works: Investigating anthropogenic impacts on deep groundwater systems and astrobiology of subsurface microbes
Guglielmo Scovazzi is a Professor at Duke University with appointments across multiple departments including the Department of Civil and Environmental Engineering, the Thomas Lord Department of Mechanical Engineering and Materials Science, and as Professor of Mathematics. His interdisciplinary research bridges computational mechanics, scientific computing, and engineering applications. Dr. Scovazzi earned his B.S/M.S. in aerospace engineering (summa cum laude) from Politecnico di Torino (Italy), followed by an M.S. and Ph.D. in mechanical engineering from Stanford University. Prior to joining Duke, he was a Senior Member of the Technical Staff at Sandia National Laboratories' Computer Science Research Institute. His research focuses on developing advanced numerical methods for computational mechanics, particularly finite element methods for fluid and solid mechanics. Key areas include multiphase porous media flows, computational methods for materials under extreme conditions, turbulent flow computations, and instability phenomena. His work emphasizes creating accurate computational approaches that reduce design/analysis costs for complex engineering problems involving fluid-structure interactions and transient phenomena in complex geometries. Dr. Scovazzi's most significant recent contribution is the development of the Shifted Boundary Method, an innovative computational framework that enables efficient simulations on complex geometries without requiring boundary-fitted meshes. This method has found applications in geomechanics, energy systems, and resilient infrastructure design. Kavli Fellow, National Academy of Sciences & Kavli Foundation (2018) Presidential Early Career Award for Scientists and Engineers (PECASE), White House (2017) Early Career Award, U.S. Department of Energy, Advanced Scientific Computing Research Program (2014) Dr. Scovazzi teaches multiple courses in computational mechanics including Nonlinear Finite Element Analysis and Introduction to the Finite Element Method. His research has been supported by substantial federal funding, and he actively collaborates across disciplines to address challenging problems in energy, environment, and infrastructure resilience through advanced computational methods.
Bruño Fraga is an Assistant Professor in the Department of Civil Engineering at the University of Birmingham, part of the School of Engineering. He specializes in Computational Fluid Dynamics (CFD) with a focus on turbulent and multiphase flows, particularly in applications like indoor air quality, water treatment, and airborne pathogen transport. His research group develops models such as Multiflow3D, addressing challenges in multiphase flow dynamics and environmental engineering. Education: MEng in Environmental Engineering (University of Santiago de Compostela, 1st class honors), MSc in Applied Math and Numerical Simulation (University of A Coruña), PhD in Civil Engineering (Universities of A Coruña and Chalmers). Research Interests: CFD modeling, bubble-induced turbulence, indoor air quality, water treatment technologies, and multiphase flow dynamics. Dr. Fraga leads major projects such as Fusion Forest (£1m, UKRI) and the IAQ-EMS initiative (£1m, Met Office), focusing on indoor air quality and pathogen transmission modeling. His work includes collaborations with organizations like Deltares Institute and Severn Trent, addressing wastewater treatment and environmental challenges. He is co-leader of the Fluids Research Group and the Water Technology stream at the University of Birmingham’s Water Centre. Scientific Awards: National Outstanding Graduate Prize (2011). Advising & Grants: Supervises graduate students in CFD and multiphase flow research. Oversees grants totaling over £2.1M, including fusion forest and buildair projects. Focuses on translating CFD expertise into real-world solutions for public health and environmental sustainability. Labs & Teams: Leads the Multiflow3D development team and collaborates with the Fluids Research Group and Water Technology stream.
Faez Ahmed is an Associate Professor at the Department of Mechanical Engineering, Massachusetts Institute of Technology (MIT), where he serves as the Doherty Chair in Ocean Utilization. He leads the Design Computation and Digital Engineering (DeCoDE) Lab, focusing on integrating machine learning and optimization with engineering design to enhance human-AI collaboration and accelerate design processes. Ph.D., Mechanical Engineering, University of Maryland College Park (2019) B.Tech.-M.Tech., Mechanical Engineering, Indian Institute of Technology Kanpur (2012) His research interests include generative design methodologies, AI-driven optimization techniques, and the development of algorithms that facilitate collaboration between human designers and artificial intelligence systems. This interdisciplinary work spans applications in automotive design , ship hull synthesis , and wind turbine optimization , with a strong emphasis on creating open-source tools and datasets for the engineering community. Recent publications demonstrate his lab's leadership in fields such as 3D CAD generation , multimodal design datasets , and constraint-aware generative models . These works often address challenges in design space exploration , performance prediction , and data-driven design frameworks . Scientific Awards NSF CAREER Award (2025) ASME Young Investigator Award (2024) Google Research Scholar Award (2024) 3M Non-Tenured Faculty Award (2022) University of Maryland Alumni Research Award (2022) Faez Ahmed's lab has trained numerous Ph.D. candidates and postdoctoral researchers, fostering a collaborative research environment that bridges mechanical engineering , artificial intelligence , and computational methods . The DeCoDE Lab actively engages with industry partners and academic institutions, contributing to large-scale datasets and benchmarks that power the next generation of engineering design research.
Ali Mani is an Associate Professor of Mechanical Engineering at Stanford University and a faculty affiliate at the Institute for Computational and Mathematical Engineering. He earned his PhD in Mechanical Engineering from Stanford in 2009, following an M.S. (2004) and B.S. (2002) from Stanford and Sharif University of Technology, respectively. His research focuses on fluid mechanics, turbulence, and numerical simulations, with applications in multiphase flows, electrokinetic systems, and applied mathematics. His group develops high-fidelity simulation tools and reduced-order models to understand transport processes in turbulent and chaotic systems. Research interests include turbulence modeling, two-phase flow dynamics, and electrochemical transport. Recent work explores eddy viscosity operators, nonlocal transport phenomena, and computational methods for multiphase systems. The group's studies often bridge experimental validation and numerical analysis to improve predictive engineering models. Key contributions span electrokinetic transport in porous media, superhydrophobic surface slip effects, and phase field modeling. His lab’s work is supported by grants focusing on fluid dynamics, renewable energy systems, and advanced simulation frameworks.
Dr. Igor V. Pivkin is a Full Professor at the Institute of Computing within the Faculty of Informatics at the Università della Svizzera italiana (USI) in Lugano, Switzerland. His academic journey includes degrees from Novosibirsk State University (B.Sc./M.Sc. Mathematics), Brown University (M.Sc. Computer Science and Ph.D. Applied Mathematics), and postdoctoral research at MIT's Department of Materials Science and Engineering. His research focuses on multiscale/multiphysics modeling , numerical methods , and large-scale simulations of biological and physical systems. Key areas include biophysics, cellular/molecular biomechanics, stochastic modeling, and coarse-grained molecular simulations. He leverages high-performance computing (HPC) and particle-based methods to address complex biological phenomena. His work spans diverse applications, from understanding cellular mechanosensitivity and biofilm engineering to modeling cancer cell behavior and red blood cell dynamics in the spleen. His contributions bridge computational science, biotechnology, and biomedical research. He has published extensively in top-tier journals, with recent work advancing automated biofilm analysis, deep learning for microbial classification, and systems biology approaches to metal bioleaching. His lab collaborates on interdisciplinary projects, emphasizing computational innovation for real-world biological challenges.
Yuri Bazilevs is the E. Paul Sorensen Professor of Engineering at Brown University's School of Engineering and Co-Director of the Mechanics of Undersea Science and Engineering Center. His research focuses on computational mechanics, isogeometric analysis, fluid-structure interaction, and high-performance computing. Prior to Brown, he held positions at UC San Diego, where he advanced to Full Professor in 2014 after a rapid tenure. He earned his PhD in 2006 and postdoc training in computational engineering at UT Austin's ICES. Research interests span computational fluid dynamics, solid mechanics, and advanced discretization methods like isogeometric analysis (IGA) and meshfree approaches. He has developed novel formulations for complex phenomena such as underwater explosions, composite material failure, and hypersonic flow dynamics. His work integrates cutting-edge numerical methods with practical engineering applications in aerospace, energy, and biomedical systems. Recent publications highlight advancements in IGA for architected materials, RKPM-based crack modeling, and stabilized formulations for compressible flows. His contributions bridge theoretical mechanics with computational innovation, addressing challenges in multiphysics coupling and large-scale simulations. Collaborations span academia and industry, emphasizing practical validation and real-world impact. Bazilevs' expertise includes variational multiscale methods, peridynamics for fracture mechanics, and immersive particle methods for fluid-structure interaction. His work has been applied to wind turbine aerodynamics, gas turbine optimization, and cardiovascular flow analysis. He actively contributes to computational infrastructure development, such as the tIGAr software framework for IGA automation.
Dr. Alain Bonneville is a Lab Fellow and Geophysicist at Pacific Northwest National Laboratory (PNNL) and holds a Courtesy Professor appointment at Oregon State University's College of Earth, Ocean, and Atmospheric Sciences. With extensive experience in geological storage of CO2, geothermal energy, and geophysical monitoring techniques, Dr. Bonneville leads diverse research projects that bridge fundamental science and practical applications for energy and environmental challenges. Dr. Bonneville's educational background includes: PhD in Geophysics from the University of Montpellier, France MS in Petroleum Geophysics from IFP-School, Paris, France BS in Geology from the University of Lyon, France Dr. Bonneville's research spans several critical areas in Earth sciences and energy systems. His work on geothermal energy focuses on super-hot enhanced geothermal systems (EGS), site characterization, monitoring, and stimulation fluids. In geological CO2 storage, he investigates project management, site characterization, numerical modeling, and monitoring methods using potential fields and remote sensing. His expertise in geophysical methods includes heat flow measurements, gravity surveys, muon tomography development for borehole deployment, and remote sensing applications. Additional research areas encompass marine heat flow instrumentation development, thermal monitoring of active volcanoes, and intraplate volcanism studies in the Indian and Pacific Oceans. Dr. Bonneville has received significant recognition for his contributions to science, including: Membership in the Washington State Academy of Sciences Lab Fellow position at Pacific Northwest National Laboratory Executive Committee membership on the U.S. National Risk Assessment Partnership Scientific Committee membership at IFP-Energies Nouvelles, France He also holds two U.S. patents related to electrophilic acid gas-reactive fluids for enhanced fracturing and recovery of energy producing materials. Throughout his career, Dr. Bonneville has led significant research initiatives, including the PNNL Carbon Sequestration Initiative (2009-2013) and the European Marie Curie Research Training Network on Greenhouse Gas Removal (GRASP), which involved 14 academic and industrial institutions across 7 countries and supported 35 PhD students and post-docs. His work on the FutureGen 2.0 project demonstrates his leadership in large-scale carbon storage site characterization and monitoring program design. Dr. Bonneville maintains active collaborations with research teams at PNNL's Environmental Molecular Sciences Laboratory and works closely with Oregon State University's geoscience researchers. His laboratory work focuses on developing novel instrumentation for geophysical monitoring, particularly in the areas of muon tomography for subsurface characterization and thermal monitoring systems for geothermal and carbon storage applications.
Brett Sanders is a Professor in the Department of Civil and Environmental Engineering at the Samueli School of Engineering, University of California, Irvine. His research focuses on developing innovative algorithms for flow and transport in river and coastal systems and integrating information technologies to create more accurate and efficient simulation tools for flood hazard assessment. His primary research interests include: Flooding and erosion hazards, particularly coastal flooding and urban flooding Surface water quality Low impact development impacts on hydrology Dam-break flooding Aerial and terrestrial lidar scanning Geographical information systems High performance computing for simulation tools Social dimensions of flood risk and adaptation behaviors Dr. Sanders' recent publications (2024-2025) reveal a comprehensive research program addressing both technical and social aspects of flood risk. His work spans computational hydrodynamics, flood hazard mapping, infrastructure vulnerability assessment, and the socioeconomic dimensions of flood risk. He has made significant contributions to understanding multi-grid modeling of urban flooding, post-fire flood hazards, satellite-based monitoring of land motion, and social inequalities in flood exposure. His research demonstrates how flood dynamics are more complex than simple bath-tub filling models suggest, with important implications for urban planning and climate adaptation. Dr. Sanders has received recognition as a Chancellor's Professor at UC Irvine, indicating distinguished scholarly achievement. His educational background includes: Ph.D. in Civil Engineering from the University of Michigan (1997) M.S. in Civil Engineering from the University of Michigan (1994) B.S. in Civil Engineering from the University of California, Berkeley (1993)
Pascale Biron is a Professor in the Department of Geography, Urban Planning and Environment at Concordia University, Montreal. She holds a Ph.D. in Geography from Université de Montréal (1995) and has been with Concordia since 1998. Her research focuses on river dynamics, stream restoration for fish habitat, flood modeling, and climate change impacts. She specializes in hydrogeomorphology, river management in agricultural watersheds, and numerical modeling of fluvial processes. Research Interests: Her work includes river restoration strategies, flood risk assessment using LiDAR technology, and the 'river freedom' concept promoting ecosystem resilience. She collaborates closely with government agencies to translate research into practical river management policies. Professional Affiliations: Canadian Geomorphology Research Group, Canadian Association of Geographers, American Geophysical Union, GRIL (Limnology Research Group), and RIISQ (Quebec Flood Risk Network). Publications & Research: Recent studies address global salmonid biomass patterns, fluvial hazard detection via machine learning, and large-scale flood modeling. She supervises 19 graduate students in Ph.D./M.Sc. programs in Geography and Environmental Studies, focusing on topics like river confluence hydraulics and agricultural stream restoration. Grants & Funding: Active projects include river dynamics in fish habitats, flood modeling for road infrastructure vulnerability, and computational fluid dynamics simulations of river flows. She also leads research on societal dimensions of river restoration and policy frameworks for flood resilience.
Prof. Dr.-Ing. Lars Linsen is a full Professor of Computer Science at the Westfälische Wilhelms-Universität (WWU) Münster, leading the VISualization & graphIX (VISIX) group. His primary affiliation is the Institute of Computer Science within the Faculty of Mathematics and Computer Science. He holds adjunct professorships at Jacobs University, Bremen, and has held previous academic roles including Full Professor at Jacobs University (2012–2017) and Associate/Assistant Professor roles in Germany and the U.S. His research focuses on interactive visual analysis, medical visualization, and scientific visualization, with applications in life sciences and engineering. Education: PhD (Dr.-Ing.) in Computer Science from Universität Karlsruhe (2001), M.Sc. (Diplom) in Computer Science (1997), B.Sc. (Vordiplom) in Computer Science (1994). Awards: IEEE Visualization Design Contest Winner (2008, 2022, 2018), Preis des Fördervereins des Forschungszentrum Informatik (2002). Research Highlights: Develops visualization tools for medical imaging (e.g., mass spectrometry imaging, MRI data analysis) and physical simulations (e.g., wildfire spread analysis, asteroid impact modeling). Active in EU-funded projects like Pig-Pro-QuO (surface coatings) and cells-in-motion initiatives. Supervised over 20 PhD/MS advisees, including notable graduates in medical visualization and simulation ensemble analysis. Publications: Over 100 peer-reviewed articles in top venues like IEEE Transactions on Visualization and Computer Graphics, Computers & Graphics, and EuroVis. Key works include SciVis contest-winning wildfire analysis frameworks and medical visualization tools for stenosis detection. Teaching: Offers courses on visualization, computer graphics, and computational science. Actively involved in thesis supervision and curriculum development at both WWU Münster and Jacobs University. Grants & Collaborations: Principal investigator on DFG-funded projects (e.g., hemodynamics simulations, ensemble visualization) and industry collaborations (e.g., Tascon GmbH for coating quality analysis). Member of the Cells-in-Motion Interfaculty Centre and CDH board at WWU.
Prof. Dr. Markus Bachmayr is a full professor at the Institute for Geometry and Practical Mathematics, RWTH Aachen University, holding the chair for Applied Mathematics. His research focuses on nonlinear approximation, high-dimensional partial differential equations (PDEs), uncertainty quantification, and numerical methods in quantum chemistry. He leads the ERC Consolidator Grant project Computational Complexity of Highly Nonlinear Approximations (COCOA) and contributes to CRC 1481 Sparsity and Singular Structures, and RTG 2326 Energy, Entropy, and Dissipative Dynamics. His recent work emphasizes adaptive low-rank and sparse approximation techniques for parametric and stochastic PDEs, including applications in radiative transfer and poroviscoelastic flow modeling. He serves as Editor-in-Chief of Foundations of Computational Mathematics and Associate Editor for multiple journals. Scientific Awards: John Todd Award 2013 Borchers Plakette 2014 Erwin Wenzl Preis 2007 He has taught courses such as Numerische Analysis I/II, Numerische Mathematik für Elektrotechniker, and seminars on numerical methods and approximation theory.
Xiaocheng Shang is an Associate Professor in Mathematical Optimisation and Data Science at the University of Birmingham's School of Mathematics. His research focuses on numerical methods for stochastic differential equations, with applications in computational mathematics, statistics, physics, and data science. He is affiliated with the Optimisation and Numerical Analysis Group, Statistics and Data Science Group, and the Institute for Data and AI. Shang holds a PhD in Applied and Computational Mathematics from the University of Edinburgh (2016) and completed postdocs at the University of Edinburgh, Brown University, and ETH Zurich before joining Birmingham in 2019. His academic achievements include fellowships from The Alan Turing Institute, the LMS Emmy Noether Fellowship, and the EUniWell Leadership Fellowship. He has secured funding from EPSRC, the Royal Society, and the Isaac Newton Institute. Shang is actively involved in supervising PhD students and co-organizing research initiatives such as the Data Science and Computational Statistics Seminar. Research interests include structure-preserving integrators, Bayesian sampling techniques, and machine learning applications in dynamical systems. His work bridges numerical analysis, probability theory, and multiscale modeling in materials science. Recent projects involve neural networks for complex dynamical systems and numerical algorithms for deterministic/stochastic systems.
Eduardo Pereyra is a Professor in the McDougall School of Petroleum Engineering at The University of Tulsa, where he serves as Associate Director for the Tulsa Fluid Flow Projects (TUFFP) and the Horizontal Wells Artificial Lift Project (TUHWALP) . His academic career spans theoretical and applied research in multiphase flow, flow assurance, artificial lift systems, and separation technologies. Education: Ph.D. and M.Sc. in Petroleum Engineering from The University of Tulsa; Dual B.S. in Mechanical Engineering and Systems Engineering from the University of Los Andes, Venezuela Pereyra’s research focuses on multiphase flow dynamics , particularly in gas-liquid and oil-water systems. His work addresses critical challenges such as slug flow mitigation , downhole separator efficiency , and ESP motor cooling , leveraging computational fluid dynamics (CFD) and experimental validation. Recent publications emphasize inclined pipe flows , severe slugging mitigation , and plunger lift optimization . Pereyra has received multiple accolades, including the 2023 SPE Production and Operations Award and the 2022 Kermit Brown Outstanding Teacher Award . His contributions to multiphase flow modeling have been recognized through the 2021 Zelimir Schmidt Outstanding Researcher Award . He actively collaborates with industry partners through TUFFP and TUHWALP, directing projects like the Horizontal Wells Artificial Lift Initiative .
