Find Academic Supervisors

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

Kenny Wiratama is a researcher at the Mathematical Sciences Institute of The Australian National University (ANU). His work focuses on numerical methods for partial differential equations, particularly in computational fluid dynamics and mathematical physics. He specializes in developing stable and accurate schemes for wave equations, Navier-Stokes equations, and related systems using discontinuous Galerkin spectral element methods. His research emphasizes energy stability analysis and weak boundary condition imposition, with applications in coastal engineering, turbulence modeling, and biomedical fluid dynamics. Recent work includes contributions to the linearized Serre equations and gauge formulations of incompressible flows. Publications span topics like higher-order wave equation discretization, SPH method evaluation in pulsating blood vessels, and spectral element method stability. No scientific awards are explicitly mentioned in the data provided. Research interests align closely with his affiliations in applied mathematics and computational science.

Göran KauermannView profile

Professor

• Nonparametric Models
• Semi- and nonparametric analysis
• Generalized Linear Models
• +2 more

Prof. Dr. Göran Kauermann is a Full Professor of Statistics at the Ludwig-Maximilians-University Munich , holding the Chair of Applied Statistics in Social Sciences, Economics and Business . His research spans nonparametric models, generalized linear models, and network data analysis, with applications in economics, epidemiology, and data science. Education: Diplom in Economic Mathematics (1991, TU Berlin), PhD in Statistics (1994), Habilitation (Venia Legendi) in Statistics (2000) Kauermann’s research interests focus on penalized regression , network analysis , and statistical modeling in economics, social sciences, and public health. Recent work explores label uncertainty in machine learning , spatio-temporal conflict diffusion , and dynamic network models for economic and social data. Scientific trends in his publications include penalized splines for nonlinear modeling, network flow estimation in social and economic contexts, and label variation analysis in machine learning. His collaborations span climate zone classification , Covid-19 mortality modeling , and smart city parking analytics . Scientific Awards: Bruce Russett Award (2020) for political network research Leadership Roles: He served as Dean of the Faculty of Mathematics, Informatics and Statistics (2019–2021), Speaker of the Elite Master Program in Data Science (2016–2026), and Chair of the German Statistical Society (2005–2013). He also held editorial roles in journals like AStA Advances in Statistical Analysis and Statistical Modelling .

• Multiphase Flows
• Computational Fluid Dynamics
• Turbulence
• +4 more

Dr. Lina Baroudi is an Associate Professor in Mechanical Engineering at Manhattan University. Her research focuses on multiphase flows, computational fluid dynamics, and turbulence, with applications in nuclear reactor thermal hydraulics and mesoscopic simulation techniques. She holds a Ph.D. from The City College of New York and a B.S. from Damascus University. Education: Ph.D., The City College of New York MPhil, The City College of New York M.S., The City College of New York B.S., Damascus University Her research interests include studying surface-tension-driven flows, particle-laden flows, and developing predictive models using advanced computational methods like Lattice Boltzmann (LB), Molecular Dynamics (MD), and parallel high-performance computing. She has contributed to understanding Taylor-Couette flow dynamics, bubble rising mechanics, and droplet coalescence phenomena. Dr. Baroudi has been awarded prestigious fellowships including the Nuclear Regulatory Commission Graduate Fellowship (2015-2016), MRSEC PREM Fellowship (2011-2015), and NSF Graduate Research Fellowship (2009-2010). Her work bridges fundamental fluid dynamics with industrial and nuclear engineering applications. She teaches courses such as Engineering Mathematics, Applied Heat Transfer, and Finite Element Analysis. Her lab focuses on multiphase flow modeling and high-performance computing, collaborating with ASME, APS, and other professional societies.

• Composite Materials
• Structural Mechanics
• Fracture Mechanics
• +5 more

Dr. Muni Rami Reddy Rasappagari is a casual academic staff member at the University of Southern Queensland (UniSQ) , Australia, within the School of Engineering . He holds a Diploma in Civil Engineering from SV Govt Polytechnic Tirupati, a Bachelor of Technology from Nagarjuna University, a Master of Science in Civil Engineering from Indian Institute of Technology (IIT), and a PhD from the University of Madras . His research spans composite materials , structural mechanics , fracture mechanics , and nanomaterials , with a particular focus on graphene-reinforced composites , functionally graded materials , and delamination modeling . His work integrates finite element analysis , fractal methods , and vibration analysis to address complex structural integrity problems. Dr. Rasappagari's recent publications (2018–2022) emphasize graphene nanoplatelet (GPL) reinforcement in composite plates, exploring free and forced vibration , flexural behavior , and boundary condition effects . Earlier work (2007–2009) centered on fractal finite element methods for crack sensitivity analysis and stress intensity factor computation in anisotropic and multi-crack systems . Contact: 📧 muniramireddy.rasappagari@unisq.edu.au

• 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.

Thomas J. SantnerView profile

Professor

• Design of Experiments
• Computer Simulations
• Statistical Selection and Screening
• +3 more

Thomas J. Santner is a Professor in the Department of Statistics at Ohio State University. His research focuses on experimental design, particularly in integrating computer simulations with physical experiments. He co-authored influential books including *The Design and Analysis of Computer Experiments* (Springer, 2019) and *The Design and Analysis of Experiments for Statistical Selection, Screening, and Multiple Comparisons* (Wiley, 1995). His work bridges statistics and engineering, addressing challenges in prosthesis design, biomedical systems, and industrial processes. Notably, he collaborates with the Hospital for Special Surgery on bone-implant systems and biomaterials research. Education: Ph.D., Purdue University, 1973. Research interests include: Computer experiments and hybrid simulation-physical experimentation Statistical selection and screening methodologies Applications in biomedical engineering and manufacturing optimization Uncertainty quantification in finite element models Recent work emphasizes optimizing complex systems through calibrated simulators, with applications in injection molding processes and joint replacement design. His articles demonstrate methodological contributions to design efficiency, sensitivity analysis, and multiobjective optimization. Prior roles include former Director of the Department of Statistics' Consulting Service and former Department Chair at Ohio State University.

Ricardo Ruiz BaierView profile

Professor

• Numerical Analysis
• Scientific Computing
• Finite Element Methods
• +7 more

Ricardo Ruiz Baier is a Professor of Computational Mathematics at Monash University in Melbourne, Australia, where he also holds an ARC Future Fellowship. He is affiliated with the Victorian Heart Institute and the Monash Data Futures Institute, highlighting his interdisciplinary research bridging mathematical theory with biomedical applications. His research focuses on the design and analysis of numerical methods for partial differential equations, particularly those that preserve the physical properties of natural phenomena. His expertise includes fundamental topics in numerical analysis and scientific computing such as analysis of finite volume and finite element methods using mixed and augmented formulations, space-time adaptivity and error estimation, perturbed saddle-point problems, multiphase flow and transport in porous media, cardiac electrophysiology and electromechanics, and interface problems. His recent publications reveal a strong emphasis on virtual element methods, poroelasticity models, and cardiac mechanics applications. His work spans theoretical numerical analysis, computational methods development, and practical biomedical applications, particularly in cardiac modeling. The research demonstrates a consistent focus on multiphysics problems and the development of robust numerical schemes for complex coupled systems. Scientific Awards: ARC Future Fellowship FT22 for 'Next-generation methods for transport in poroelastic media with interfaces' Australian Research Council Discovery Project DP21 for 'Towards predictive 4D computational models for the heart' Ruiz Baier actively supervises a large research group with numerous PhD students and postdoctoral researchers working on diverse aspects of computational mathematics. His group has secured funding from multiple sources including Monash Mathematics, the Australian Research Council, IITB-Monash Doctoral Programme, and international government scholarships. He frequently organizes major conferences and workshops, including the Computational Techniques and Applications Conference (CTAC 2024) and MATRIX workshops on numerical analysis. His research group operates at the intersection of mathematics, computational science, and biomedical engineering, with particular focus on developing computational models for cardiac function and mechanics. The group collaborates with international institutions including the University of Oxford and University of Oslo.

Amirreza KhodadadianView profile

Lecturer

• Uncertainty Quantification
• Numerical Analysis
• Computational Mechanics
• +7 more

Dr. Amirreza Khodadadian is a Lecturer in Mathematics at the School of Computer Science and Mathematics, Keele University, since August 2023. He holds a Ph.D. from the University of Vienna (2017), followed by postdoctoral positions at the Technical University of Vienna and Leibniz University Hannover. His research focuses on uncertainty quantification, numerical methods for stochastic PDEs, finite element methods, computational mechanics, and machine learning applications in nanoelectronics and biological systems. Key research interests include Bayesian inversion, multiscale modeling, reduced-order methods, and the design of nanoscale sensors. He has collaborated with institutions like the University of Oxford and secured an Austrian Science Fund (FWF) grant (476k€) for nanozyme sensor research. Dr. Khodadadian mentors postdoctoral researchers, including Dr. Samaneh Mirsian, and actively publishes in top-tier journals such as Journal of Computational Physics and Computer Methods in Applied Mechanics and Engineering . His work bridges applied mathematics with engineering challenges, emphasizing efficient numerical algorithms for real-world problems like battery degradation, groundwater contamination, and biomedical sensor optimization. Recent projects involve machine learning integration for enhanced predictive modeling. Education: Ph.D. in Mathematics, University of Vienna, Austria (2017) Postdoctoral Fellowships: TU Vienna (2018), Leibniz University Hannover (2018–2022) Grants/Awards: Austrian Science Fund (FWF) Grant: Single Atom Catalysts as Nanozymes in FET Sensors (2023) Advising: Postdoctoral Mentor: Dr. Samaneh Mirsian (Keele University) Dr. Khodadadian’s publications span computational mechanics, stochastic modeling, and interdisciplinary applications, reflecting his expertise in translating mathematical theory into practical engineering solutions.

• Robustness and progressive collapse of structures
• Assessment and retrofitting of structures
• Sustainable infrastructure materials
• +7 more

Dr Levingshan Augusthus Nelson is a Lecturer at The University of Salford's School of Science, Engineering & Environment, affiliated with the Centre for Future Engineering. He holds a PhD in Structural Engineering from the University of Cambridge (2012) and a BSc Eng (Hons) in Civil Engineering from the University of Moratuwa (2006). His research focuses on robustness of structures, retrofitting, sustainable materials, and quasi-brittle fracture mechanics. He has received awards including the Clancy Prize (2023), Research into Practice Award (2022), and Lundgren Research Award (2010). Teaching includes courses like Tall Building Design and Civil Engineering Surveying . He supervises PhD students and contributes to UN Sustainable Development Goals related to resilient infrastructure and sustainable cities. Recognitions include roles as an ICE Chartered Professional Reviewer, EPSRC Peer Review College member, and editorial roles in journals like Masonry International . His research outputs span advanced analytical models for FRP-concrete interfaces, scaling laws for progressive collapse studies, and innovative masonry arch bridge assessment methods. Key projects include KTP collaborations with industry and studies on geomechanical effects in shale production.

Andres Galvis RodriguezView profile

Senior Lecturer

• Lithium-ion Battery Degradation
• Multiscale Modelling
• Micromechanical Modelling
• +4 more

Andres Galvis Rodriguez is a Senior Lecturer at the School of Electrical and Mechanical Engineering, University of Portsmouth. He specializes in multiscale modelling, lithium-ion battery degradation, and micromechanical analysis of heterogeneous materials. His research involves developing novel mathematical models and computational tools, including the BESLE software for boundary element analysis of heterogeneous materials. He collaborates with Brazilian researchers on advancing thermo-elasticity modules for BESLE. Teaching responsibilities include coordinating modules in Solid Mechanics & Dynamics and Engineering Mathematics. His work focuses on finite element and boundary element methods, with applications to battery systems, composite materials, and bone structures. The BESLE software, co-developed by Dr. Galvis Rodriguez, is a pioneering open-source tool for simulating anisotropic and isotropic materials using parallel computing. Current research emphasizes the mechanical behavior of lithium-ion electrodes via homogenization techniques and fatigue analysis in composite-repaired structures. His contributions bridge computational mechanics and materials science, addressing challenges in energy storage and structural integrity.

Zdenek BazantView profile

Professor

• Mechanics of Materials
• Fracture Mechanics
• Structural Safety
• +6 more

Zdenek Bazant is the McCormick Institute Professor and Walter P. Murphy Professor of Civil and Environmental Engineering at Northwestern University, with courtesy appointments in Mechanical Engineering and Materials Science. He has been at Northwestern since 1969, serving as Director of the Center for Geomaterials (1981–1987) and holding leadership roles in multiple academic organizations. His research focuses on mechanics of materials, fracture, and structural safety, with contributions to probabilistic mechanics, nano-mechanics, and concrete technology. He holds 7 honorary doctorates and prestigious awards including NAS membership, NASAE, and medals from ASME and ASCE. His work includes over 575 refereed articles and 6 books, achieving a Google Scholar H-index of 94 and 39,000 citations. Education: PhD in Prague (1963) Positions: Editor of ASCE Journal of Engineering Mechanics, President of Soc. of Engineering Science, and Founding President of IA-FRAMCOS Research interests span quasibrittle fracture mechanics, size effects, and structural safety. Key contributions include scaling laws for structural strength and microplane models for concrete behavior. His work on hydraulic fracturing and creep in concrete has influenced engineering practices globally. Notable awards include the Timoshenko Medal (ASME), von Karman Medal (ASCE), and Prager Medal (SES). He has been honored with Special Issues of major journals and birthday workshops. Current affiliations include memberships in multiple national academies and editorial roles.

Marolo AlfaroView profile

Professor

• Geotechnical Engineering
• Geosynthetic Engineering
• Ground Improvement
• +4 more

Dr. Marolo Alfaro is a Professor in the Department of Civil Engineering at the University of Manitoba, Price Faculty of Engineering . He specializes in geosynthetics, ground improvement, cold regions engineering, and climate-resilient infrastructure , with a focus on Arctic and permafrost conditions. Education: BSc (University of Mindanao), MEng (Asian Institute of Technology), PhD (Saga University), Postdoctoral (University of Calgary) Research Interests center on: Geosynthetic-reinforced structures Cold climate infrastructure adaptation Hydro-mechanical interactions in Arctic environments Nano-modified soil stabilization Publication Trends highlight: Numerical and field studies on Arctic embankments Geothermal energy piles in cold climates Rockfill column applications for riverbank stabilization Nanotechnology in soft soil treatment Scientific Awards : 2019 Geosynthetics Award (Canada/International) 2022 Roger J.E. Brown Award (Canadian Geotechnical Society)

Danijela TadićView profile

Professor

• Production Engineering
• Industrial Engineering
• Decision-Making Models
• +5 more

Danijela Tadić is a Professor at the Department of Production Engineering, Faculty of Engineering, University of Kragujevac, Serbia. Her primary research focuses on decision-making models under uncertainty, manufacturing process optimization, failure mode analysis, and sustainable recycling technologies in the automotive and industrial sectors. She holds a leadership role in the Faculty of Engineering, contributing to academic governance and curriculum development. Her scientific work integrates fuzzy logic systems, multi-criteria decision-making (MCDM), and optimization algorithms to address complex engineering challenges. Notable areas include risk management in supply chains, quality improvement in manufacturing processes, and environmental impact assessment of recycling equipment. She has collaborated on projects evaluating organizational resilience, strategic failure management, and resource planning in SMEs. Prof. Tadić’s publications emphasize practical industrial applications, such as PFMEA integration with fuzzy decision tools, cloud platform selection frameworks, and electric vehicle evaluation models. Her work bridges theoretical advancements in fuzzy set theory with real-world manufacturing and environmental sustainability problems. She actively participates in academic and professional networks, contributing to conferences and journals in production engineering and industrial systems. Her expertise spans project lifecycle management, lean manufacturing, and the evaluation of recycling technologies for end-of-life vehicles (ELVs).

Jiong TangView profile

Professor

• System Dynamics
• Control
• Sensing and Automation
• +7 more

Jiong Tang is a Pratt & Whitney Chair Professor in Design and Manufacturing at the University of Connecticut , where he also serves as Co-Director of the Management and Engineering for Manufacturing Program . He received his B.S. and M.S. in Applied Mechanics from Fudan University, China (1989 and 1992), and his Ph.D. in Mechanical Engineering from Pennsylvania State University (2001). Prior to joining UConn, he worked at the GE Research Center as a research engineer. Research Interests : System dynamics, control theory, smart materials, vibration suppression, uncertainty propagation, computational intelligence, and multi-physics system modeling. Current Projects : Digital twin development for aerospace materials, physics-informed machine learning in manufacturing, adaptive metasurface design, and optimization of cooperative robotics. Methodological Focus : Combines Bayesian deep learning , Gaussian process metamodeling , transformer-based architectures , and multi-fidelity data fusion for industrial applications. His work emphasizes smart sensing , electromechanical integration , and uncertainty-robust inverse analysis . Collaboration : Research funded by federal agencies and industrial partners , with particular emphasis on aerospace and manufacturing technologies. His recent publications highlight generative adversarial networks for defect detection , piezoelectric metamaterials , and physics-guided neural network architectures across mechanical, structural, and composite systems.

Haibin NingView profile

Associate Professor

• High Performance Lightweight Materials
• Thermoplastic Matrix Composites
• Additive Manufacturing
• +4 more

Haibin Ning is an Associate Professor and Undergraduate Program Director in the Department of Materials Engineering at the University of Alabama at Birmingham (UAB). His research focuses on high-performance lightweight composite materials, particularly thermoplastic matrix composites and environmentally friendly natural fiber composites. He has pioneered methods for fiber content measurement, developed advanced manufacturing processes, and holds patents in composite materials innovation. Education: Ph.D. in Materials Engineering from UAB. Research Interests: Dr. Ning’s work spans additive manufacturing of composites, recycled material utilization, and bio-inspired damage-tolerant materials. His studies address mechanical properties, flammability, and environmental impact, with applications in aerospace, automotive, and biomedical fields. Awards & Recognition: ASTM International Professor of The Year (2013) UAB President's Award for Excellence in Teaching (2014) Teaching & Advising: Courses include metallic materials, composite materials, and automotive materials frontiers. While no specific advisees are listed, his research group actively explores industrial and academic collaborations. Labs & Teams: Engages in interdisciplinary projects at UAB’s Center for Composites Manufacturing, focusing on structural composites for mass transit, aerospace, and biomedical applications.