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Krishna KumarView profile

Assistant Professor

• Geotechnical Engineering
• Sustainable Systems Engineering
• Multi-scale modeling
• +6 more

Krishna Kumar is an Assistant Professor in the Department of Civil Engineering at The University of Texas at Austin, holding the J. Neils Thompson Centennial Teaching Fellowship. His expertise lies in Geotechnical Engineering and Sustainable Systems Engineering, with a focus on multi-scale modeling of natural hazards, landslides, earthquakes, and debris flows. He employs advanced computational techniques such as the material point method, discrete element method, and lattice Boltzmann method, alongside high-performance computing and big data frameworks for infrastructure system modeling. Education: Ph.D., University of Cambridge, 2015 M.S., Indian Institute of Technology Madras, 2010 B.E., Anna University, 2008 Research Interests: His technical interests include computational geomechanics, granular material simulations, and the integration of machine learning with physics-based models. Recent work emphasizes inverse analysis using differentiable neural networks, explainable AI for geotechnical risk assessment, and innovative teaching methods like murder mysteries to enhance engineering education. Publications Trend: His articles from 2023–2025 highlight advancements in hybrid numerical methods (e.g., finite element-material point method), machine learning-driven simulations of granular flows, and computational tools for predicting geotechnical hazards. Cross-disciplinary themes include AI explainability, granular material behavior under cyclic loading, and scalable city-level traffic modeling. Teaching & Innovation: Beyond technical research, he explores pedagogical innovations such as gamified learning through murder mystery scenarios to engage students in complex engineering concepts.

• Fluid Dynamics
• Multiphase Flows
• Monte Carlo Methods
• +3 more

Aaron Morris is an Associate Professor in the Department of Mechanical Engineering at Purdue University's West Lafayette campus. He is affiliated with the Center for Particulate Products and Processes. His research focuses on fluid dynamics, multiphase flows, Monte Carlo methods, and granular media heat transfer. He holds a B.S. from Rensselaer Polytechnic Institute (2006), M.S. and Ph.D. from the University of Texas at Austin (2009/2012), and a postdoctoral fellowship at the University of Colorado Boulder (2013-2015). His research explores heat transfer mechanisms in granular flows, rarefied gas dynamics, and computational modeling of particulate systems. He has pioneered studies on fluidized bed heat exchangers for solar energy applications and developed novel Monte Carlo methods for granular gas simulations. His work bridges fundamental physics with engineering applications in energy storage and aerospace systems. Recent publications emphasize thermal analysis of particle-based energy systems, fluidized bed optimization, and granular gas behavior under extreme conditions. His work on lunar dust transport and rocket plume impingement demonstrates interdisciplinary expertise in aerospace engineering. Key awards: Engineering Foundation Endowed Presidential Scholarship Labs/teams: Center for Particulate Products and Processes Future work: Advanced thermal energy storage systems and multiphase flow modeling innovations

Wing K. LiuView profile

Professor

• Computational Mechanics
• Multiscale Modeling
• Additive Manufacturing
• +5 more

Wing K. Liu is the Walter P. Murphy Professor of Mechanical Engineering, Civil and Environmental Engineering (by courtesy), and Materials Science and Engineering at Northwestern University. He leads the HiDeNN-AI research group, focusing on mechanistic data science, hierarchical deep learning neural networks (HiDeNN), and multiscale modeling for advanced manufacturing and materials innovation. His work integrates physics-based principles with machine learning to address challenges in additive manufacturing, computational mechanics, and materials design. Education : Ph.D., M.S., California Institute of Technology B.S. (Hons) in Engineering Science, University of Illinois at Chicago Research Interests : Liu’s research spans mechanistic data science, AI-driven materials innovation, and multiscale modeling. His HiDeNN framework enables fast design, optimization, and discovery in engineering systems. Key areas include laser powder bed fusion, image-based modeling, and predictive manufacturing processes. He emphasizes combining scientific principles with data to accelerate technology development. Awards and Recognition : Gauss-Newton Medal (2012) John von Neumann Medal (2007) ASME Robert Henry Thurston Lecture Award (2007) ISI Highly Cited Researcher in Engineering (2001) Teaching and Academic Leadership : Liu teaches advanced finite element methods, multiscale modeling, and computational mechanics. He has served as editor for Computational Mechanics , vice president of the International Association for Computational Mechanics, and past president of the U.S. Association for Computational Mechanics. Labs and Teams : His research group, Wing K. Liu Group , develops cutting-edge tools like JAX-FEM and C-HiDeNN, focusing on GPU-accelerated simulations and AI integration in engineering systems.

• Computational Fluid Dynamics
• Fluid-Structure Interaction (FSI)
• Aerodynamics
• +4 more

Tayfun E. Tezduyar is the James F. Barbour Professor of Mechanical Engineering at Rice University. He holds a Ph.D. from Caltech (1982) and has held faculty positions at the University of Houston, University of Minnesota, and visiting roles at institutions including the University of Tokyo and Waseda University. His research focuses on computational fluid-structure interaction (FSI), cardiovascular biomechanics, and advanced numerical methods such as isogeometric analysis. He pioneered space-time finite element methods and has contributed to the analysis of spacecraft parachutes, car aerodynamics, and bioinspired flapping-wing aerodynamics. Education: M.S. (1978), Ph.D. (1982) in Mechanical Engineering, California Institute of Technology. Awards: John von Neumann Medal (2023), Ted Belytschko Award (2018), Honorary Doctorate (Slovak Republic, 2001). Leadership: Directed the Army High Performance Computing Research Center (1994–1998), chaired Rice's Mechanical Engineering department (1999–2004). His work emphasizes high-resolution flow simulations and has been applied to aerospace, biomedical, and automotive engineering challenges. Over 289 indexed journal articles and 70 book chapters highlight his prolific contributions to computational mechanics.

Jesse ChanView profile

Associate Professor

• Numerical Methods for PDEs
• Scientific Computing
• Discontinuous Galerkin Methods
• +5 more

Jesse Chan is an Associate Professor in the Department of Computational Applied Mathematics and Operations Research at Rice University. He earned his Ph.D. from the University of Texas at Austin and a bachelor's degree from Rice University. His research focuses on high-order numerical methods for partial differential equations, including discontinuous Galerkin (DG) methods, entropy stability, and efficient implementations on modern architectures. He has received the NSF CAREER Award (2020) and leads the development of open-source software like Trixi.jl and StartUpDG.jl. Education: Ph.D., Institute for Computational Engineering and Sciences (ICES), University of Texas at Austin (2013) B.A., Computational and Applied Mathematics, Rice University (2008) Research Interests: Numerical Methods for PDEs High-Order Finite Element and DG Methods Entropy Stability and Conservation Laws Scientific Computing and HPC Wave Propagation and Fluid Dynamics Recent Work Trends: His publications emphasize robust entropy-stable schemes, cut-cell methods, and reduced-order modeling for nonlinear conservation laws, with applications to fluid dynamics and wave propagation. He also explores GPU acceleration for DG methods. Awards: NSF CAREER Award (2020) Advising & Grants: Advised students Brian Christner and Raymond Park (recent MA theses) Funded by NSF grants DMS-CAREER-1943186 and DMS-2231482 Labs/Teams: Active contributor to the Trixi.jl framework and collaborator on open-source DG tools like StartUpDG.jl.

Klaus-Jürgen BatheView profile

Professor

• Computational Mechanics
• Finite Element Analysis
• Fluid-Structure Interaction
• +5 more

Professor Klaus-Jürgen Bathe is a distinguished faculty member at the Massachusetts Institute of Technology in the Department of Mechanical Engineering . As a pioneer in computational mechanics , his work has shaped the development of the finite element method through innovations like the MITC shell elements , Bathe time integration , and subspace iteration method . He founded ADINA R&D, Inc. (acquired by Bentley Systems in 2022) and established the Klaus-Jürgen Bathe Leadership Program at the University of Cape Town to cultivate leadership in South African graduates.

Jayan S. VinodView profile

Associate Professor

• Discrete Element Modelling
• Soil Dynamics
• Transport Geomechanics
• +4 more

Dr. Jayan S. Vinod is an Associate Professor at the University of Wollongong's School of Civil, Mining, Environmental and Architectural Engineering, part of the Faculty of Engineering and Information Sciences. He has held this position since 2022. His expertise includes discrete element modeling of geomaterials, soil dynamics, and transport geomechanics, with a focus on waste material utilization in infrastructure. He has authored over 115 refereed publications and secured numerous competitive grants, including an Australia-India EMCR Fellowship. Vinod serves as an associate editor for the Journal of Materials in Civil Engineering and editor-in-chief of the International Journal of Geotechnical Earthquake Engineering . Education: PhD in Geotechnical Engineering from Indian Institute of Science (2006). Research Interests: His work spans discrete element modeling, liquefaction behavior, ground improvement using recycled materials, and methane hydrate sediment mechanics. Recent studies include: Development of sustainable infrastructure using waste materials (e.g., slag, tyre aggregates). Dynamic performance of ballasted railway tracks. Numerical modeling of cone penetration tests using LBM-DEM. Grants & Awards: Vinod has led projects funded by ARC, DFAT, and industry partners, including research on geothermal energy recovery and methane hydrate sediment behavior. His awards include the IGS biennial best paper award (2003). Advising: Supervises PhD/Master’s students in areas like geothermal fracture connectivity, coir geotextiles, and lignosulfonate soil stabilization. Current projects include studies on scrap tyre mixtures and hybrid renewable energy systems.

• Sustainable Technologies for Metal Production
• Thermodynamics and Kinetics of Metallurgical Processes
• Alternative Technologies in Light Metal Production
• +4 more

Dr. Guangqing Zhang is a Senior Lecturer at the School of Mechanical, Materials, Mechatronic and Biomedical Engineering, University of Wollongong. His research focuses on sustainable chemical and mineral processing, energy efficiency, and metallurgical processes. He holds a Ph.D. in Materials Science and Engineering from the University of New South Wales. Research Interests: Sustainable metal production, energy generation/storage, and extractive metallurgy. He explores novel processes to utilize inferior resources and enhance production efficiency while prioritizing sustainability. Recent work includes studies on shale fracture mechanics, nanolubricant applications in manufacturing, and CO2-brine-rock interactions. He has led over 20 funded projects, including ARC Training Centre for Innovative Composites and the Australian Steel Manufacturing Research Hub. His supervision involves graduate research on topics like micro deep drawing and steelmaking waste valorization. Key grants include the ARC Industrial Transformation Training Centre (2023–2028) and collaborations with industry partners. He is also part of the Steel Research Group Network and contributes to advancing Australian steel manufacturing technologies.

James BrannickView profile

Professor

• Lattice Field Theory
• Numerical Solutions to PDEs
• Multigrid Methods
• +3 more

James Brannick is a Professor in the Department of Mathematics at Pennsylvania State University, affiliated with the Eberly College of Science. His research focuses on numerical solutions to partial differential equations (PDEs), multigrid methods, and lattice field theory, with applications in computational physics and quantum chromodynamics (QCD). He holds a Ph.D. from the University of Colorado Boulder (2005). Research interests include developing advanced multigrid algorithms for complex systems, such as coupled PDEs and spacetime discretizations, with a particular emphasis on algebraic multigrid (AMG) methods. His work bridges theoretical foundations (e.g., convergence analysis) and practical implementations (e.g., parallel solvers for large-scale problems). Recent publications emphasize AMG optimization, bootstrap techniques, and applications to fluid dynamics, quantum field theory, and materials science. Collaborative projects include NSF-funded initiatives for parallel space-time solvers and multigrid methods in lattice QCD. Brannick’s contributions address challenges like critical slowing down in lattice simulations and efficient handling of anisotropic or indefinite problems. Grants include subcontract B629176 (2019) and prior NSF awards for multigrid solvers in coupled PDE systems. His research often intersects with high-performance computing and interdisciplinary applications, such as neutron star dynamics and phase-field modeling.

• Optimization and Control
• Numerical Analysis
• Partial Differential Equations
• +3 more

Kenneth Czuprynski is an Adjunct Professor in the Department of Mathematics at The Pennsylvania State University, affiliated with the Eberly College of Science. His work focuses on computational mathematics, numerical analysis, and optimization with applications in control systems, fluid dynamics, and radiative transfer. He holds an email address: kdc168@psu.edu . Research Interests: Development of scalable algorithms for Partially Observable Markov Decision Processes (POMDPs) Numerical methods for hemivariational inequalities and fluid dynamics equations Energy-dependent radiative transfer models Acoustic radiation problems using boundary element methods Recent Publications: His work spans optimization algorithms, numerical solutions to PDEs, and computational physics. Notable contributions include scalable POMDP controllers, finite element methods for Navier-Stokes equations, and energy discretization techniques in radiative transfer. His research bridges theoretical mathematics with applied computational challenges across multiple engineering domains. Advising & Grants: No formal advisees or grant information listed. His contributions primarily focus on individual and collaborative research initiatives within his academic affiliations. Labs/Teams: No specific labs or teams explicitly mentioned in provided information.

• Volcanology
• Geomechanics
• Geohazards
• +3 more

Claire Harnett is an Associate Professor at the School of Earth Sciences, University College Dublin (UCD), where she leads the Geohazards Research Group and serves as the primary supervisor to four PhD students. She is also involved in setting up a rock mechanics laboratory at UCD, focusing on volcanic rocks and civil engineering applications. Her roles include teaching across Earth Sciences and Civil Engineering programs, particularly contributing to the MSc in Subsurface Characterisation and Geomodelling. Beyond UCD, she is the elected Early Career Representative for the Volcanic and Magmatic Studies Group (VMSG) committee and a Technical Editor for the journal Volcanica . Dr. Harnett holds a BSc from the University of Portsmouth, a PhD from the University of Leeds, and a Professional Diploma in University Teaching & Learning from UCD. Her research emphasizes numerical modeling of volcanic environments, specifically investigating dynamic stability in lava domes, calderas, and hydrothermally altered systems. Key interests include extrusion dynamics, collapse mechanisms, and the interplay between mechanical properties and volcanic hazards. She has secured over €2.8 million in research grants, including leadership of the €10 million European Research Council Synergy Grant (ROTTnROCK), which explores hydrothermal alteration's role in volcano instability. Other grants focus on magma-induced deformation, geomechanical property scaling, and geothermal energy potential in volcanic systems. Recent work combines remote sensing, rock physics, and computational modeling with international teams at GFZ Berlin, EOST Strasbourg, and Uppsala University. Her awards include the UCD Excellence in Teaching & Learning Award (2022), the Bob Hunter Memorial Prize for Best Student Talk (2018), and the Itasca Educational Partnership (2015–2019). She actively contributes to professional activities as a peer reviewer for Journal of Volcanology and Geothermal Research and Scientific Reports .

Qingshan ChenView profile

Associate Professor

• Fluid Dynamics
• Geophysical Flows
• Geometric Mechanics
• +4 more

Qingshan Chen is an Associate Professor in the Department of Mathematical and Statistical Sciences at Clemson University, part of the College of Science. His research focuses on fluid dynamics, geophysical flows, geometric mechanics, and turbulence, with expertise in numerical methods for geophysical and climate modeling systems. He develops conservative numerical schemes for complex fluid dynamics problems, including shallow water equations, quasi-geostrophic flows, and multi-layer models. His work emphasizes computational accuracy, stability, and applications in oceanography and atmospheric science. Chen’s research interests span applied mathematics, computational physics, and geophysical modeling. He has contributed to advancing finite volume methods, error analysis on unstructured meshes, and stochastic approaches like the multilevel Monte Carlo method for turbulent flow simulations. His studies often address challenges such as corner singularities in partial differential equations and incompatible initial-boundary conditions. Key applications include climate system modeling with frameworks like E3SM and MPAS, as well as glaciology and ocean circulation dynamics. His publications highlight innovations in numerical schemes for geophysical flows, including energy-conserving methods, optimal dispersive wave relations, and adaptive grid techniques. These contributions aim to bridge mathematical rigor with practical computational tools for environmental and engineering challenges. Chen’s work is disseminated through high-impact journals in applied mathematics, computational physics, and geosciences.

• Numerical Analysis
• Partial Differential Equations
• Computational Fluid Dynamics
• +3 more

Xuejian Li is a Research Fellow in the Department of Mathematical and Statistical Sciences at Clemson University's College of Science. His work focuses on advancing numerical methods for partial differential equations, with a particular emphasis on data assimilation, fluid dynamics, and interface problems. He develops algorithms for coupled systems like Stokes-Darcy flow and Navier-Stokes equations, contributing to computational fluid dynamics and porous media modeling. His research explores topics such as domain decomposition methods, iterative solvers, and stochastic modeling. Recent work addresses challenges in data compression for optimization, uniqueness of steady flows, and convergence analysis of numerical schemes. He applies finite-element discretization and variational techniques to solve interface and multi-physics problems. Notably, Li's studies integrate data assimilation with noisy inputs to enhance computational fluid dynamics simulations. While no academic awards are listed, his publications reflect active engagement in computational mathematics and applied analysis. No advising or grant details are provided in the profile.

Qiushi ChenView profile

Professor

• Computational Geomechanics
• Discrete Element Method
• Finite Element Method
• +5 more

Dr. Qiushi Chen is a Professor of Civil Engineering at Clemson University's College of Engineering, where he leads the Computational Geomechanics Lab. His research spans multiple interdisciplinary fields including computational mechanics, geotechnical engineering, and materials science with applications in biomass processing, extraterrestrial exploration, and earthquake engineering. Dr. Chen received his B.S. in Civil Engineering from Shanghai Jiaotong University (2006), followed by an M.S. (2009) and Ph.D. (2011) in Theoretical and Applied Mechanics with a focus on Geomechanics from Northwestern University. His academic journey has positioned him at the intersection of computational science and practical engineering applications. His primary research interests include computational geomechanics, discrete and finite element methods, extraterrestrial regolith characterization, biomass feedstock preprocessing, and liquefaction hazard assessment. Dr. Chen's work integrates advanced computational techniques with experimental validation to address complex engineering challenges across multiple scales - from particle-level interactions to regional hazard mapping. His research group develops sophisticated numerical models that bridge the gap between theoretical mechanics and practical engineering solutions. Analysis of Dr. Chen's recent publications reveals a strong focus on computational methods for granular materials, with particular emphasis on discrete element modeling (DEM) applications. His work spans terrestrial applications in biomass processing and earthquake engineering to extraterrestrial applications involving lunar and Martian regolith. The integration of machine learning techniques with traditional computational mechanics represents an emerging trend in his research, enabling more efficient and accurate modeling of complex material behaviors. Dr. Chen actively contributes to the professional community as an Associate Member of the American Society of Civil Engineers, Member of the Engineering Mechanics Institute, Member of the Geo-Institute, Member of the Soil Properties and Modeling Committee (ASCE), and Vice-Chair of the Computational Geotechnics Committee (ASCE). In addition to his research, Dr. Chen teaches courses including Introduction to Geotechnical Engineering, Inelastic Materials Modeling, and Computational Mechanics of Granular and Porous Materials. He mentors graduate students interested in computational geomechanics, which sits at the interface of geotechnical engineering, applied mechanics, computational science, and material science. The Computational Geomechanics Lab, directed by Dr. Chen, maintains active research programs in multiple areas including biomass feedstock modeling, extraterrestrial regolith characterization, multiscale liquefaction hazard mapping, and multiphysics problems in porous geomaterials. The lab's work is supported by various funding sources including the U.S. Department of Energy, NSF, NASA, and other federal agencies.

Victor GintingView profile

Professor

• Numerical Analysis
• Multiscale Phenomena
• Porous Media Flow
• +4 more

Victor Ginting is a Professor of Mathematics at the University of Wyoming, Department of Mathematics & Statistics since 2007. He specializes in numerical analysis and multiscale phenomena, particularly in porous media flow. His research bridges mathematical theory and computational methods for complex physical systems. He holds a Ph.D. in Mathematics from Texas A&M University (2004), an M.S. in Ocean Engineering (1998), and a B.S. in Civil Engineering from Institut Teknologi Bandung, Indonesia (1995). Prior to UW, he was a postdoctoral associate at Colorado State University. His research focuses on numerical methods for partial differential equations, including finite element methods, multiscale modeling, and flow in porous media. He has contributed to applications in subsurface flow, contaminant transport, and uncertainty quantification. Notable work includes studies on two-phase flow instabilities, fractional diffusion equations, and Bayesian frameworks for subsurface characterization. Dr. Ginting serves as an Advisory Editor for the Journal of Computational and Applied Mathematics . His publications span 2004–2023, emphasizing computational mathematics, fluid dynamics, and interdisciplinary challenges in geosciences. His methodologies often address challenges in multiscale systems and data-driven simulation frameworks. Grants and collaborations involve advanced numerical techniques for reservoir engineering, environmental modeling, and mathematical software development. His work integrates theoretical rigor with practical applications in energy and environmental sectors.