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Xu ZhangView profile

Associate Professor

• Numerical Analysis
• Scientific Computing
• Numerical Methods for Partial Differential Equations
• +6 more

Xu Zhang is an Associate Professor in the Department of Mathematics at Oklahoma State University, where he has been employed since 2019, initially as an Assistant Professor and promoted to Associate Professor in 2022. He is currently serving as the President of the SIAM Central States Section for 2024-2025. His academic journey includes a Golomb Visiting Assistant Professorship at Purdue University (2013-2016) and an Assistant Professor position at Mississippi State University (2016-2019). Dr. Zhang's educational background includes: Ph.D. in Mathematics from Virginia Tech (2013) M.S. in Mathematics from Virginia Tech (2009) M.S. in Computational Mathematics from Sichuan University (2008) B.S. in Computational Mathematics from Sichuan University (2005) Dr. Zhang's research focuses on numerical analysis and scientific computing, with particular emphasis on immersed finite element methods for interface problems. His work addresses both static and moving interface problems, developing innovative numerical techniques that avoid the need for body-fitting meshes. This research has significant applications in computational fluid dynamics, computational plasma physics, and other areas requiring simulations across material interfaces. He has developed methods including immersed finite element methods, partially penalized immersed finite element methods, and immersed weak Galerkin methods, with applications to Navier-Stokes equations, elasticity problems, and plasma-material interactions. Dr. Zhang's scientific contributions have been recognized with several prestigious awards, including: Distinguished Early Career Faculty Award from Oklahoma State University (2023) Ralph E. Powe Junior Faculty Enhancement Award from ORAU (2021) Holistic Science Prize from Oklahoma State University (2021) Dr. Zhang has successfully secured multiple research grants from the National Science Foundation, including DMS-2110833 ($212,822, 2021-2024), DMS-2224003 ($20,000, 2022-2023), and DMS-1720425 ($125,042, 2017-2021). He has mentored several graduate students, including Ph.D. student Derrick Jones (graduated 2021, now at Johns Hopkins University Applied Physics Lab), Ph.D. student Fang Liu (2024-present), and Master's students Hoang Nam Tran (graduated 2024) and Madylan Rusinek (2022-present). He also supervises postdoctoral fellow Dr. Ahmed Zytoon (2024-present). Dr. Zhang actively contributes to the academic community through conference organization, having organized multiple SIAM Central States Section meetings and other specialized workshops on numerical methods for interface problems. He serves on editorial boards for journals including Frontiers in Applied Mathematics and Statistics and has guest-edited special issues for several computational mathematics journals.

Seth DillardView profile

Academic

• Biomedical Engineering
• Mechanical Engineering
• Cardiovascular Biomechanics
• +5 more

Seth Dillard is an Associate Teaching Professor in the Department of Mechanical Engineering and School of Biomedical Engineering at Colorado State University (CSU). He joined CSU in January 2022, teaching courses such as Introduction to Mechanical Engineering, Finite Element Analysis, Machine Design, and Problem-Based Learning in Biomedical Engineering. He advises Senior Design teams and honors students across both disciplines. In 2023, he introduced new courses including Senior Design and a Berlin-focused Education Abroad program. Education: PhD (2011) and BSE (2004) in Mechanical Engineering from the University of Iowa. He also holds an EMT-P certification (1996) and postdoctoral research experience at the University of Iowa's IIHR from 2011–2014. Research and teaching interests include cardiovascular biomechanics, image-based modeling, energy systems, and applying engineering principles to healthcare. His teaching innovations include courses like Quantitative Systems Physiology and Prosthetics Innovation in Ecuador, blending engineering with global health challenges. Dr. Dillard has received multiple teaching awards, including the College of Engineering Faculty Excellence Award (2020) and four Excellence in Teaching awards from the University of Iowa. He has supervised over 30 students in thesis and design projects and actively participates in academic service roles such as Associate Director of SBME and accreditation committee leadership. His research spans computational fluid dynamics, cardiovascular modeling, and biomedical device design. He has published extensively in journals like Journal of Neurosurgery and Theoretical and Computational Fluid Dynamics, with peer-reviewed conference contributions since 2005.

Min SunView profile

Professor

• Educational Policy
• Teacher Education & Research
• AI/ML in Education
• +8 more

Dr. Min Sun is a Professor in the Department of Educational Policy, Organization and Leadership at the University of Washington's College of Education. Her research focuses on teacher learning, AI/ML integration in education, and policy-driven educational reforms. She leads interdisciplinary teams developing AI tools like the NSF-funded Colleague lesson planning platform and the IES-funded AmplifyGAIN Center. Her work addresses inequities in education through policy analysis and partnerships with K-12 schools and EdTech industries. Dr. Sun holds a Ph.D. in Educational Policy and Measurement from Michigan State University. She teaches courses such as EDLPS 302: Intro to Educational Policy and EDLPS 564: Economics of Education. Her research spans four key areas: AI/ML method development, AI-powered educational tools, data science training programs, and policy research with multi-sector collaborations. Notable grants include a $10 million IES grant for the AmplifyGAIN Center and a $1.5 million NSF grant for AI-driven math lesson planning. Her policy work emphasizes equitable education access and data-driven solutions. She directs the Education Policy Analytics Lab (EPAL) and collaborates with stakeholders to translate research into actionable strategies.

Joe D. WarrenView profile

Professor

• Computer Graphics
• Geometric Modeling
• Computational Geometry
• +3 more

Joe D. Warren is a Professor of Computer Science at Rice University, where he has served since 1986. His research focuses on computer graphics, geometric modeling, and computational geometry, with notable contributions to subdivision surfaces, as detailed in his book Subdivision Methods for Geometric Design . He also explores bioinformatics applications, including 3D modeling of mouse brain gene expression and lung motion analysis from 4D CT scans. Additionally, Warren teaches courses in computer game design and introductory programming, co-developing award-winning Coursera specializations. He earned his Ph.D. from Cornell University and previously served as Department Chair (2008-2013). Education: B.Sc. (Rice University, 1983), Ph.D. (Cornell University, 1986) Research Collaborators: Baylor College of Medicine, MD Anderson Cancer Center, Texas A&M Teaching: COMP460 (Game Design), COMP110 (Introductory Computing) His work on the GRACE tool (Graphical Ruler and Compass Editor) won the 1998 Quest for Java award. He has advised PhD students now at Washington University and Texas A&M. Current projects include game prototyping with Pi Studios and lung motion modeling for medical diagnostics.

Giovanni RussoView profile

Professor

• Computational Fluid Dynamics
• Numerical Methods for Conservation Laws
• Numerical Methods for Kinetic Equations
• +5 more

Giovanni Russo is a Full Professor of Numerical Analysis at the Department of Mathematics and Computer Science, University of Catania, Italy . He coordinates the PhD program in Pure and Applied Mathematics and has been a visiting scholar at institutions including Courant Institute, University of California, Los Angeles, University of Michigan, and University of Bordeaux. His career spans over four decades across academia and research institutions. Education: PhD in Physics (1986, University of Catania), Laurea in Nuclear Engineering (1982, Politecnico di Milano). Research Interests: Russo specializes in Computational Fluid Dynamics , Numerical Methods for Conservation Laws , and Kinetic Equations . His work includes asymptotic preserving schemes , IMEX methods , semi-Lagrangian schemes , and high-order numerical techniques for PDEs with applications to fluid dynamics, plasma physics, and multiscale modeling. Scientific Trends: Recent publications focus on modeling epidemic dynamics , kinetic equations for inert mixtures , semi-Lagrangian methods , and uncertainty quantification in quantum systems. These works reflect his expertise in high-order numerical schemes , multiscale analysis , and applied mathematical modeling . Scientific Awards: CNR-NATO Fellowship (1987) Advising and Grants: Russo has supervised nine PhD students and served as Principal Investigator (PI) for major projects including MOSCOVID (modeling COVID-19) and ModCompShock (Horizon 2020 Marie Curie project). He has also organized international conferences like the 18th European Conference on Mathematics for Industry with 370 participants. Labs and Teams: Russo collaborates with research groups at the University of Catania and has been a visiting researcher at Courant Institute, University of Michigan, and GSSI L’Aquila. He contributes to journals as an editor and reviewer, including SIAM Journal of Numerical Analysis and Journal of Computational Physics .

Chris J BuddView profile

Professor

• Nonlinear Mathematics
• Industrial Mathematics
• Numerical Analysis
• +7 more

Professor Chris J Budd OBE is a distinguished Professor of Applied Mathematics at the University of Bath's Department of Mathematical Sciences, where he serves as Director of Knowledge Exchange for the Bath Institute for Mathematical Innovation (IMI). He is also Professor of Mathematics at the Royal Institution of Great Britain and a former Gresham Professor of Geometry. His leadership extends to directing the Centre for Nonlinear Mechanics and serving as Super Champion of the KE Hub. His educational background includes a gap year with Marconi that profoundly shaped his career, followed by undergraduate studies at Cambridge and a DPhil at Oxford. This industry experience during his formative years established his lifelong commitment to industrial mathematics and knowledge exchange. Budd's research focuses on nonlinear mathematical problems with industrial applications, particularly adaptive moving mesh methods for meteorology and climate modeling, data assimilation, non-smooth dynamical systems, and the mathematics of machine learning. He approaches linear problems as 'for cissies,' preferring the challenges of nonlinear systems that better represent real-world phenomena. His work bridges theoretical mathematics with practical applications across meteorology, environmental science, and engineering. His recent publications reveal a strong trend toward integrating machine learning with traditional numerical methods, particularly in climate modeling and solving partial differential equations. This includes Fourier Neural Operators, adaptive mesh methods enhanced by graph neural networks, and mathematical frameworks for understanding climate tipping points through non-smooth dynamics. OBE for services to mathematics National Teaching Fellowship (NTF) Knowledge Transfer Award for work with the Met Office Fellow of the Institute of Mathematics and its Applications (FIMA) Chartered Mathematician (C Math) British Science Association award for best science festival (2009) As principal investigator of the £3.5M EPSRC Programme Grant 'Maths4DL' on the Mathematics of Deep Learning, Budd leads a major collaborative effort between Bath, Cambridge, and UCL. He actively supervises numerous PhD students across diverse projects including climate modeling, machine learning applications, and industrial mathematics problems. His commitment to knowledge exchange is exemplified through V-KEMS (Virtual Forum for Knowledge Exchange in the Mathematical Sciences), which he co-founded to address challenges like the COVID-19 pandemic through mathematical approaches. Budd directs the Centre for Nonlinear Mechanics at Bath, fostering interdisciplinary research through mathematical modeling of complex systems. He also leads the Bath Institute for Mathematical Innovation's knowledge exchange activities, connecting academic mathematics with industrial and societal challenges. His work with V-KEMS has proven particularly effective during the pandemic, mobilizing teams of mathematicians to address urgent real-world problems.

Harish Nagaraj DixitView profile

Associate Professor

• Interfacial flows
• Moving contact lines
• Drop and bubble dynamics
• +5 more

Dr. Harish Nagaraj Dixit is an Associate Professor in the Department of Mechanical & Aerospace Engineering at the Indian Institute of Technology Hyderabad , where he leads a multidisciplinary research group focusing on Interfacial flows , Hydrodynamic stability theory , Vortex dynamics , and Electrohydrodynamics . His academic journey began with a B.Tech from Osmania University (2003), followed by an M.S. at IIT Madras (2005), and culminated in a Ph.D. from JNCASR, Bengaluru (2010), where his dissertation explored Vortices with density stratification . The group employs theoretical, computational, and experimental approaches to investigate phenomena such as drop impact mechanics , contact line dynamics , and vortex pattern formation . They operate a state-of-the-art laboratory equipped with high-speed cameras and lasers for advanced fluid experimentation. Recent publications span topics including electrospinning , tear-film stability , and vortex shedding in oscillating flows . Dr. Dixit teaches advanced courses like ME 5310: Incompressible Fluid Flow and ME 7100: Advanced Mathematical Tools , emphasizing conceptual understanding and rigorous analytical methods. His research advisory includes multiple Ph.D. and M.Tech students working on problems from drop impact to electrohydrodynamic jetting . Collaborations extend to institutions such as the University of British Columbia and IIT Madras .

Stephen LangdonView profile

Professor

• Numerical Analysis
• Numerical Solution of Partial Differential Equations
• Boundary Integral Equation Methods
• +6 more

Professor Stephen Langdon is a faculty member at Brunel University London , holding the position of Professor of Mathematics and serving as Associate PVC for Academic Planning & Strategic Projects . His academic career includes over 15 years at the University of Reading , where he was Head of the Department of Mathematics and Statistics for five years. He also served as Interim Executive Dean of the College of Engineering, Design and Physical Sciences at Brunel from 2022 to 2024. Education: PhD in Numerical Analysis, University of Bath (1999) BA in Mathematics, Oxford University (1994) Postgraduate Certificate of Academic Practice, University of Reading (2009) Research Interests: Professor Langdon's research is centered in Numerical Analysis , with a strong focus on the development, analysis, and implementation of numerical methods for partial differential equations . His work encompasses: Boundary integral and finite element methods High-frequency scattering problems in acoustics and electromagnetics Fluid flow in porous media Computational modeling of tumor growth Machine learning applications in numerical methods Publications Overview: His recent work includes modeling helicopter rotor-induced particle-fluid interactions , developing frequency-independent numerical methods for far-field scattering , and advancing high-frequency boundary element methods . These publications span journals such as AIAA Journal , Journal of Fluid Mechanics , SIAM Journal on Scientific Computing , and IMA Journal of Numerical Analysis . Teaching and Supervision: He teaches MA2690 - Professional Development and Project Work and actively supervises PhD students in areas aligned with his research interests. He welcomes prospective PhD applicants in numerical analysis, PDEs, and related computational fields. Contact: Email: stephen.langdon@brunel.ac.uk Phone: +44 (0)1895 266554 Office: Tower A 030, Brunel University London

• Applied Mathematics
• Numerical and Computational Mathematics
• Partial Differential Equations
• +4 more

Prof. Vanessa Styles is a Professor and Head of the School of Mathematical and Physical Sciences at the University of Sussex. Her research focuses on mathematical and computational analysis of nonlinear partial differential equations, with applications in physical sciences, including materials science, fluid dynamics, and biological modeling. She specializes in numerical methods for evolving surfaces, phase field models, and free boundary problems. Her work often involves interdisciplinary collaborations, addressing challenges in lithium batteries, tumor growth, and cell migration. Prof. Styles has led major grants, including ModCompShock (EU) and Leverhulme-funded projects on cell migration mechanics. She teaches calculus courses and actively contributes to academic leadership. Her research interests span computational fluid dynamics, numerical analysis of PDEs, and mathematical biology. Recent work emphasizes tumor growth modeling via phase field approaches, crystal growth in batteries, and cell migration force estimation. She has published extensively in journals like Interfaces and Free Boundaries and Journal of Computational Physics , with a focus on rigorous error analysis and algorithm development. Grants include funding for modeling grain boundary motion (EPSRC), 3D cell migration (Leverhulme), and shock interface modeling (EU). Her research bridges theoretical analysis and practical applications, with contributions to both fundamental mathematics and engineering/medical fields.

• Quantum Chemistry
• Uncertainty Quantification
• Numerical Analysis
• +5 more

Virginie Ehrlacher Galland is a Professor at CERMICS (Centre d'Enseignement et de Recherche en Mathématiques et Calcul Scientifique) within École des Ponts ParisTech. Her expertise lies in applied mathematics, numerical analysis, and computational physics, with a focus on multiscale problems, quantum chemistry, and uncertainty quantification. She holds a PhD from CERMICS (2012) and a Habilitation (2020) from Université Paris-Dauphine. Her research interests include cross-diffusion systems, reduced basis methods, and optimal transport applications. Key contributions involve numerical methods for electronic structure calculations, homogenization techniques, and adaptive algorithms. She leads the ERC Starting Grant HighLEAP (2023-2028) and contributes to major projects like the ERC Synergy project EMC². Awards: Irène Joliot-Curie Prize (2023), Chevalier de l’Ordre National du Mérite (2025). Grants/Projects: ERC Starting Grant HighLEAP (PI), ERC Synergy EMC² (Member), ANR JCJC COMODO (PI). Her work bridges theoretical analysis and computational methods, addressing challenges in materials science, fluid dynamics, and machine learning applications.

• High Performance Computing
• Software Engineering for HPC
• Code Generation
• +12 more

Harald Köstler is an Associate Professor and Head of Research at the Erlangen National High Performance Computing Center (NHR@FAU) within the Department of Computer Science at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU). He leads the research group on HPC Software Design at the Chair of Computer Science 10 (System Simulation), focusing on software engineering for high-performance computing and data analytics. His research interests include: Software Engineering for HPC Code Generation for Numerical Solvers Performance Engineering on Hybrid Architectures Discontinuous Galerkin and Lattice Boltzmann Methods Multigrid Solvers and Parallel Algorithms Performance Portability across CPUs, GPUs, and FPGAs The recent publications highlight a strong trend in developing efficient, scalable, and portable simulation frameworks for complex physical systems. His work emphasizes code generation, performance optimization, and the integration of classical model-driven and data-driven approaches. Key application areas include computational fluid dynamics, geotechnical engineering, and climate modeling, often leveraging the waLBerla and ExaStencils frameworks. Harald Köstler has no listed scientific awards in the provided text. He advises students in the areas of high-performance computing, numerical methods, and software engineering for scientific applications. His research is supported by collaborations within the FAU HPC ecosystem and likely involves grants related to national high-performance computing initiatives. He is a key contributor to the waLBerla framework, a block-structured, high-performance software for multiphysics simulations, and is involved with the ExaStencils project, which focuses on advanced multigrid solver generation. These frameworks form the core of his research team's efforts in scalable scientific computing.

Colin D. RennieView profile

Professor

• River Engineering
• Environmental Hydraulics
• Sediment Transport
• +12 more

Colin D. Rennie is a Professor and Chair in the Department of Civil Engineering at the University of Ottawa, Faculty of Engineering. He holds a Ph.D. and MASc from the University of British Columbia and a B.Sc. from the University of Guelph, and is a licensed Professional Engineer (P.Eng.). He is an active researcher, educator, and leader in river and environmental hydraulics. His research focuses on river morphodynamics, sediment transport, turbulence, and aquatic habitat, utilizing advanced techniques including acoustic Doppler current profilers (ADCPs), laboratory physical models, and 3D numerical modeling. His work addresses critical issues such as river stability, flood dynamics, hydroelectric development, and ecosystem protection. The recent trends in his publications reflect a strong emphasis on high-resolution numerical modeling of local scour, sediment transport using acoustic methods, and the morphodynamic impacts of river confluences and floods. His work integrates field data with computational fluid dynamics (CFD), particularly using OpenFOAM, to understand complex flow-sediment interactions. He is an Associate Editor of the Journal of Hydraulic Engineering (ASCE) and has served on editorial boards of Journal of Geophysical Research – Earth Surface (AGU). He is a member of professional organizations including ASCE, IAHR, CSCE, and AGU, and has held leadership roles such as Secretary of the River Hydraulics Division at IAHR. Professor Rennie currently supervises multiple graduate students, including Yi Man, Xiatong Cai, Qingcheng Yu, and others, supporting research in sediment dynamics and hydraulic modeling. He has secured research funding for projects related to river flooding, ice processes, and habitat restoration. His teaching includes CVG3116 (Hydraulics), CVG4001 (Introduction to Civil Engineering Design), CVG4907 (Design Project), CVG5162 (River Hydraulics), and CVG5160 (Sediment Transport). His research has been conducted globally, with collaborations in New Zealand, Switzerland, Spain, and China, where he has led field campaigns and trained researchers in spatial mapping of water and sediment fluxes. He has applied his expertise to major flood events, including the 2013 Alberta flood and the 2017–2019 Ottawa River floods.

Michael BainesView profile

Lecturer

• Numerical Analysis
• Computational Fluid Dynamics
• Finite Element Methods
• +2 more

Michael Baines is an Associate Lecturer in the Department of Mathematics and Statistics at the University of Reading, affiliated with the School of Mathematical, Physical and Computational Sciences. His research focuses on developing advanced numerical methods for solving complex physical problems, particularly in fluid dynamics and environmental modeling. His educational background and professional appointments include: Visiting Professor at University of Leeds Former Director of the Institute of Computational Fluid Dynamics (ICFD) Research interests span: Computational fluid dynamics with emphasis on moving mesh methods Numerical symmetry preservation techniques Finite element applications in nonlinear systems Environmental transport phenomena modeling His recent publications demonstrate a consistent focus on adaptive numerical methods for environmental and physical systems, with evolving applications in climate science and multiphase systems. The work shows increasing sophistication in handling coupled physical phenomena through innovative computational frameworks. Laboratory affiliations: Numerical Analysis and Computational Modelling research group

• Partial Differential Equations
• Numerical Analysis
• Mathematical Biology
• +5 more

Charles M. Elliott is a Professor of Mathematics at the University of Warwick. His research focuses on mathematical and numerical analysis of partial differential equations (PDEs), particularly in evolving domains, manifolds, and surfaces. Key areas include free boundary problems, geometric evolution equations, biomembranes, and phase transitions. He has contributed to finite element methods for surface PDEs and holds editorial roles at journals like the IMA Journal of Numerical Analysis and Interfaces and Free Boundaries . Notable awards include the Humboldt Prize (2010) and the Royal Society Wolfson Research Merit Award (2016). His work bridges theoretical mathematics and applications in biology, materials science, and continuum mechanics. Educations and career details: While specific educational qualifications are not explicitly stated in the text, his professional trajectory includes leadership in computational mathematics and extensive editorial contributions. His teaching responsibilities include advanced modules like Maths-in-Action and Topics in Partial Differential Equations . Research Interests: Elliott’s work emphasizes PDEs in complex environments, with applications to biomembranes, cell motility, and material phase transitions. His methods integrate evolving surface finite elements and stochastic processes. Recent trends in his publications highlight evolving domains, coupled bulk-surface systems, and geometric PDEs. He addresses challenges in numerical analysis and modeling of evolving interfaces. Awards and Recognition: In addition to the Humboldt Prize and Royal Society award, he is a Fellow of the Society for Industrial and Applied Mathematics (SIAM, 2015) and received an honorary doctorate from the University of Sussex (2022). Advising and Grants: While specific student names or grant details are not listed, his research programs involve collaborations on topics like biomembrane dynamics and phase field models. He has pioneered numerical methods for evolving surface PDEs, impacting fields from materials science to mathematical biology. Labs and Teams: His work is conducted within Warwick’s Department of Mathematics, collaborating on interdisciplinary projects involving computational PDEs and their applications. The research often involves evolving geometries and multiscale modeling approaches.

Arnold ReuskenView profile

Professor

• Numerical Analysis
• Finite Element Methods
• Multigrid Methods
• +7 more

Prof. Dr. Arnold Reusken is a full Professor of Numerical Mathematics at RWTH Aachen University, affiliated with the Institute for Geometry and Practical Mathematics (IGPM). He has held the Chair for Numerical Mathematics since 1997 and maintains an active research and academic profile in computational mathematics. Education: Ph.D. in Mathematics, University of Utrecht (1988) M.Sc. in Mathematics, University of Utrecht (1984) His research focuses on the development and analysis of numerical methods for partial differential equations, with particular emphasis on finite element methods, multigrid solvers, and computational techniques for two-phase incompressible flows and PDEs on surfaces. His work bridges theoretical numerical analysis and practical scientific computing applications in fluid dynamics and interfacial phenomena. He has made significant contributions to trace finite element methods, surface Stokes equations, and unfitted discretizations. The recent publication trend shows sustained activity in numerical methods for evolving surfaces, surface fluid dynamics, and preconditioning techniques. His work often involves rigorous error and stability analysis, demonstrating a strong theoretical foundation. Editorial Roles: Associate Editor, Journal of Numerical Mathematics (2015–present) Associate Editor, IMA Journal of Numerical Analysis (2020–present) Former Associate Editor, SIAM Journal on Numerical Analysis (2016–2021) Former Associate Editor, SIAM Journal on Scientific Computing (2002–2008) Former Associate Editor, Computing & Visualization in Science (2010–2021) Member of Advisory Board, Computing (1997–2009) Prof. Reusken has advised numerous students and researchers, though specific names are not listed in the provided text. He has been involved in collaborative research projects and has secured funding for work in numerical simulation and computational fluid dynamics. He co-authored the influential textbook Numerik für Ingenieure und Naturwissenschaftler , now in its third edition, and has contributed to other key publications in the field. He leads a research group at IGPM focused on numerical methods for interface and surface problems, contributing to both fundamental algorithm development and practical implementation in scientific computing. His team works on cutting-edge methods for simulating complex fluid systems with moving boundaries and topological changes.