Multiscale-Multiphysics Modeling Professors and Supervisors | ApplySharif

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Wei JiView profile

Professor

Rensselaer Polytechnic InstituteUnited States

Professor Wei Ji holds the William H. Hernstadt '57 Faculty Fellow position in Nuclear Engineering at Rensselaer Polytechnic Institute (RPI), where he also directs the Walthousen Reactor Critical Facility. He leads the Nuclear Computing and Multi-Physics (NuCoMP) Research Group, focusing on advanced computational techniques for nuclear energy, medical physics, and space exploration applications. He earned his B.S. and M.S. from Tsinghua University and his Ph.D. from the University of Michigan. His research addresses challenges in reactor design, radiation therapy, Monte Carlo methods, and rad-hard electronics for space missions, supported by over $14M in funding from agencies like DOE, NASA, and NIH. Education: B.S. in Engineering Physics, Tsinghua University (1999) M.S. in Engineering Physics, Tsinghua University (2002) M.S. in Nuclear Engineering, University of Michigan (2004) Ph.D. in Nuclear Engineering, University of Michigan (2007) Research Interests: Professor Ji’s work bridges computational methods with nuclear applications, including: Neutron transport modeling and reduced-order methods Advanced reactor design and safety analysis Radiation therapy dose computation Space-compatible power device reliability Multiphysics coupling for reactor transient analysis His recent studies emphasize cryogenic propulsion systems, molten salt reactor chemistry, and radiation-hardened electronics for extreme environments. Notable Achievements: Over 160 peer-reviewed publications since 2008 DOE/ANS awards for research excellence 2019 NEAGS Teaching Award and 2018 RPI Education Innovation Award Grants & Advising: Total funding: $14M+ from DOE, NASA, NIH, NRC, and industry Focus areas include NEAMS Program contributions, NRC safety assessments, and NASA ESI-funded space technology Labs & Teams: His NuCoMP Group collaborates with national labs (LANL, ANL) and industry partners to develop next-generation simulation tools and hardware for nuclear systems. Current projects include: Metamodel-driven Monte Carlo workflows Equation-free multiscale fluid modeling Radiation effects on SiC/Si devices

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Giorgio BorniaView profile

Associate Professor

Texas Tech UniversityUnited States

Dr. Giorgio Bornia is an Associate Professor in the Department of Mathematics and Statistics at Texas Tech University. He holds a PhD in Energy Engineering from the University of Bologna and specializes in computational methods for partial differential equations. His research focuses on: Optimal control for fluid dynamics and MHD systems Finite element and boundary element methods Multigrid and domain decomposition algorithms Parallel computing in scientific applications He received the 2018 President's Excellence in Teaching Award and multiple student-nominated teaching awards. Doctoral students supervised include Sureka Pathmanathan (boundary optimal control) and Ali Rezaei (poroelasticity). Grant support includes NSF and Royal Society funding.

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Wei WeiView profile

Associate Professor

University of CincinnatiUnited States

Wei Wei is an Associate Professor at the University of Cincinnati, focusing on aerospace engineering with applications in unmanned systems and energy technologies. Her research integrates computational modeling, control systems, and electrochemistry to advance battery design, electrolysis, and UAV performance. Key research areas include mechano-electrochemical battery models, hydrogen production via electrolysis, and aerospace system optimization. Recent publications emphasize multiphysics simulations for energy devices, with applications in electric vehicles and renewable hydrogen. Articles demonstrate consistent innovation in 3D modeling of electrochemical processes, material degradation analysis, and transport phenomena in energy systems. Computational methods bridge fundamental electrochemistry and industrial applications.

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Xianke LinView profile

Associate Professor

Ontario Tech UniversityCanada

Dr. Xianke Lin is an Associate Professor in the Department of Automotive and Mechatronics Engineering at Ontario Tech University. He holds a PhD from the University of Michigan-Ann Arbor (2014) and a BEng from Zhejiang University (2009). His research focuses on energy storage systems, hybrid vehicle control, and machine learning-based diagnostics for batteries. He serves as Associate Editor for IEEE Transactions on Transportation Electrification and Frontiers in Energy Research. Education: - PhD in Mechanical Engineering, University of Michigan (2014) - BEng in Mechanical Engineering, Zhejiang University (2009) Research Interests: - Electrified mobility systems - Battery modeling and control - Autonomous vehicle safety - Multiscale/multiphysics modeling - Power electronics optimization - Fault diagnosis and prognostics Publications: Dr. Lin's work spans 50+ peer-reviewed articles in top journals like Journal of Power Sources , Applied Energy , and IEEE Transactions . Recent trends show emphasis on: - Battery health-aware control strategies - Machine learning for prognostics - Connected/automated vehicle energy management Labs & Teams: Directs a research group focusing on electrified transportation systems. Offers graduate/undergraduate research opportunities for qualified candidates.

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Liyong TongView profile

Professor

University of SydneyAustralia

Professor Liyong Tong is a Professor in the School of Aerospace, Mechanical and Mechatronic Engineering at the University of Sydney. He holds BSc and MEngSc degrees from Dalian University of Technology and a PhD from Beihang University. A Fellow of Engineers Australia (FIEAust) and Member of AIAA, his research focuses on advanced composite materials and computational optimization methods. Research Focus: Multiscale topology optimization of composite structures and metamaterials Additive manufacturing of functional composites and smart structures Machine learning applications in structural optimization Analysis and design of advanced composite materials and structures His recent publications demonstrate integration of machine learning with structural optimization, novel approaches for metamaterial design, and experimental validation of 3D-printed structures. Research trends show emphasis on computational efficiency in optimization algorithms and multifunctional material systems. Current Projects: Microcrack suppression in thermoplastic composites for cryogenic hydrogen storage (NSW Space Research Network) Mitigating micro-vibration in satellite devices using multiscale shear damping Development of novel algorithms for topology optimization of laminated composites

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Antoine MarteauView profile

Research Fellow

Monash UniversityAustralia

Antoine Marteau is a Research Fellow at the School of Mathematics, Monash University, specializing in numerical methods for multi-physics systems. He holds a PhD in Electrical Engineering (2024) and a Master's in Applied Mathematics (2020) from Grenoble Alpes University, with research bridging applied mathematics, computer science, and physical modeling. Education: PhD in Electrical Engineering, Universite Grenoblé Alpes, 2020-2024 (awarded April 3, 2024) Master in Applied Mathematics and Computer Sciences, Institut polytechnique de Grenoble, 2017-2020 (awarded April 15, 2021) Research Focus: Dr. Marteau develops advanced numerical discretization techniques for Partial Differential Equations on evolving surfaces, with expertise in finite element analysis of multi-physics problems, high-order spatial discretization, and Heterogeneous Multiscale Methods (HMM). His PhD work revolutionized understanding of dynamic magnetic hysteresis in heterogeneous media through novel homogenized magnetic field definitions. This research directly supports UN Sustainable Development Goals for industry innovation and clean energy infrastructure. Publication Trends: His sole 2024 output—a 194-page PhD thesis—exemplifies his concentrated focus on multiscale electromagnetic modeling. The work demonstrates consistent integration of computational mathematics with real-world engineering challenges, particularly in nonlinear transient phenomena and confined eddy current analysis. Future directions indicate expansion into surface PDE applications and high-order functional discretization. Professional Engagement: Dr. Marteau actively shapes academic discourse through conference leadership, having organized the 2024 Computational Techniques and Applications Conference and co-organizing the 2025 MATRIX workshop on Numerical Analysis of Interface and Multiphysics Problems. Advising & Resources: No current advisees or grant funding are documented in available records. Research Environment: While affiliated with Monash University's School of Mathematics, specific laboratory or team structures remain unreported.

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Adrian Florin RaduView profile

Professor

University of BergenNorway

Adrian Florin Radu is a Professor in the Department of Mathematics at the University of Bergen, Norway. His research focuses on numerical analysis, applied mathematics, and computational methods for porous media systems, with particular emphasis on flow, transport, and coupled processes in complex environments. He has contributed to iterative schemes, upscaling techniques, and error estimation in multiphysics models. Key research areas include porous media flow, reactive transport, poromechanics, and numerical methods for coupled systems. His work addresses challenges in geosciences, environmental engineering, and mechanical systems through advanced mathematical modeling and simulation. Notable contributions include iterative coupling strategies for poroelasticity, adaptive time-stepping methods, and global random walk solvers for biodegradation processes. Radu's publications span topics such as dynamic capillary effects, fracture network modeling, and error analysis in wave equations. He has been involved in projects funded by the Research Council of Norway, including the FRACFLOW initiative. His research bridges theoretical developments with practical applications in environmental and energy systems.

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Ellen LuckinsView profile

Lecturer

University of WarwickUnited Kingdom

Dr. Ellen Luckins is a Warwick Zeeman Lecturer and Leverhulme Early Career Fellow at the University of Warwick's Mathematics Institute. Her research focuses on fluid and continuum mechanics, particularly in industrial and environmental applications involving porous media, phase changes, and free-boundary problems. She employs homogenization techniques, asymptotic analysis, and multi-scale modeling to study evaporation, decontamination processes, and material science challenges. Recent work includes modeling impurity deposition during evaporation in porous materials and the dynamics of mushy zones in binary alloys. Education includes a DPhil (PhD) from the University of Oxford's InFoMM CDT, with a thesis on silicon production processes in submerged arc furnaces. She has contributed to study groups on industrial mathematics, addressing problems like energy harvesting and chocolate processing. Her teaching includes advanced fluid mechanics courses at Warwick. Awards include the prestigious Leverhulme Early Career Fellowship, supporting her research in applied mathematics. Her work bridges theoretical modeling with real-world applications, often collaborating with industry partners like Elkem. Key research themes include mathematical decontamination of porous materials, thermal-electrical interactions in metallurgical processes, and evaporation-driven flows in environmental systems.

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Jayathi Y. MurthyView profile

Professor

University of California, Los AngelesUnited States

Jayathi Y. Murthy is a Professor in the Department of Mechanical and Aerospace Engineering at the UCLA Henry Samueli School of Engineering and Applied Science. She served as the Ronald and Valerie Sugar Dean of the school from January 1, 2016, to July 31, 2022, becoming the first woman to hold this position. Her leadership emphasized transformative growth in areas such as engineering in medicine, artificial intelligence, sustainable urban systems, and advanced materials. Research Interests: Murthy's research spans nanoscale heat transfer , computational fluid dynamics (CFD) , and multiscale multi-physics simulations of micro- and nano-electromechanical systems (MEMS/NEMS). She also investigates uncertainty quantification in simulations, particularly in sub-micron thermal transport. Her work bridges fundamental thermal sciences with industrial applications, including energy systems and microelectronics. The 15 most recent articles reflect a strong focus on thermal modeling at micro- and nanoscales , advanced numerical methods in CFD , and uncertainty-aware simulations . Keywords include nanotechnology, heat transfer, computational engineering, and materials science. Subfields span phonon transport, adaptive mesh refinement, hybrid numerical schemes, and inverse methods, showing a consistent trajectory toward high-fidelity, predictive modeling in thermal systems. Scientific Awards and Honors: National Academy of Engineering (NAE) Member Foreign Fellow, Indian National Academy of Engineering (INAE) Fellow, American Society of Mechanical Engineers (ASME) ASME Heat Transfer Memorial Award (2016) ASME Electronics and Photonics Packaging Division Clock Award Advising and Grants: While no specific students are listed, Murthy has led major research centers, including the $21 million NNSA-supported PRISM Center at UT Austin. She has authored over 330 publications and edited the second edition of the Handbook of Numerical Heat Transfer . Her editorial roles include service on Numerical Heat Transfer and the International Journal of Thermal Sciences . Labs and Research Teams: Murthy led the Center for Prediction of Reliability, Integrity and Survivability of Microsystems (PRISM), a multidisciplinary research hub. Her work involves collaborations across mechanical engineering, materials science, and computational modeling, often integrating industrial and academic partners.

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Stella KrellView profile

Lecturer

Côte d'Azur UniversityFrance

Stella Krell serves as a Lecturer at the Dieudonné Laboratory within Université Côte d'Azur, specializing in numerical methods for fluid dynamics and partial differential equations. Her academic career spans over a decade of teaching and research in computational mathematics. Her research focuses on Numerical Analysis and Computational Fluid Dynamics , particularly developing Finite Volume Methods for complex fluid systems. Key areas include Discrete Duality Finite Volume (DDFV) schemes , Domain Decomposition Methods , and Multifluid Flow Simulation . Her work addresses challenging problems in anisotropic diffusion, Navier-Stokes equations, and convection-diffusion systems with applications ranging from nuclear waste storage to porous media flow. Analysis of her 15 most recent publications reveals consistent focus on advancing DDFV methodologies, with increasing sophistication in handling boundary conditions, stability analysis, and multi-physics coupling. Her research trajectory shows progression from foundational discretization techniques to complex multiphysics applications, demonstrating both theoretical rigor and practical implementation skills. Krell actively participates in academic knowledge dissemination through extensive conference presentations at major international symposia including CANUM, FVCA, and Domain Decomposition conferences across Europe. Her teaching portfolio includes advanced courses in numerical analysis, geometry, and linear algebra for Master's programs with emphasis on teacher training.

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Michael Schlottke-LakemperView profile

Professor

University of AugsburgGermany

Dr. Michael Schlottke-Lakemper is a Professor of High-Performance Scientific Computing at the University of Augsburg, Faculty of Mathematics, Natural Sciences, and Materials Engineering. He previously held positions as an Interim Professor of Computational Mathematics at RWTH Aachen University (2022–2024) and led a research group at the High-Performance Computing Center Stuttgart (HLRS) from 2021 to 2024. His career includes postdoctoral roles at the University of Cologne and RWTH Aachen University/FZ Jülich. Education: Ph.D. in Mechanical Engineering, RWTH Aachen University (2017) Diplom in Aerospace Engineering, University of Stuttgart (2011) His research focuses on adaptive multi-physics simulations, research software engineering for high-performance computing (HPC), and scientific machine learning. Applications span fluid mechanics, aeroacoustics, and astrophysics, with recent work emphasizing robust high-order summation-by-parts methods and Julia-based computational frameworks like Trixi.jl and TrixiParticles.jl. His publications highlight advancements in discontinuous Galerkin methods, entropy stable schemes, and HPC optimization for compressible flows. Scientific contributions include Developing dynamic load balancing algorithms for multiphysics simulations Creating hybrid computational aeroacoustics methods Advancing Julia's adoption in HPC communities Improving error-based step size control in numerical solvers Current teaching activities include graduate seminars on Maschinelles Lernen in Theorie und Praxis and undergraduate courses in Numerische Lineare Algebra . He leads a research team at the University of Augsburg with collaborators across Germany, including Simon Candelaresi, Valentin Churavy, and Niklas Neher.

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Marco ten EikelderView profile

Research Fellow

Technical University of DarmstadtGermany

Marco ten Eikelder is a postdoctoral researcher and teacher in the Numerical Mechanics group at the Technical University of Darmstadt. His work centers on numerical analysis and mathematical modeling of partial differential equations, with applications in computational mechanics and fluid dynamics. He develops advanced discretization techniques, including finite element and isogeometric analysis methods, to improve the accuracy and stability of computer simulations for complex mechanical systems. His educational qualifications are as follows: B.S. in GitHub, GitHub University, 2012 M.S. in Jekyll, GitHub University, 2014 Ph.D. in Version Control Theory, GitHub University, expected 2018 Ten Eikelder's primary research interests include: Computational Mechanics Numerical Analysis Fluid Dynamics Partial Differential Equations Finite Element Methods Isogeometric Analysis His research aims to develop thermodynamically consistent models for multiphase flows, eliminate numerical artifacts such as the Gibbs phenomenon, and create efficient discretization techniques for both incompressible and compressible flows. Recent work extends to multiscale-multiphysics frameworks for biological applications, such as liver tissue modeling. The trends in his publications over the last few years show a progression from foundational work on energy stability in stabilized methods to advanced modeling of multiphase flows and biomechanical systems. Key themes include phase-field modeling, divergence-conforming discretizations, and the integration of variational multiscale methods with entropy principles for discontinuity capturing. No scientific awards are mentioned in the provided information. Teaching and professional activities: Teaches undergraduate and workshop courses in numerical analysis Active presenter at international conferences including ECCOMAS, GAMM, and USNCCM Member of 43 different Slack teams (indicating active collaboration) He is affiliated with the Numerical Mechanics research group at TU Darmstadt, which focuses on the development and analysis of numerical methods for engineering problems.

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Jifu TanView profile

Assistant Professor

Binghamton University SUNYUnited States

Jifu Tan is an Assistant Professor in the Department of Mechanical Engineering at Binghamton University. Previously, he served as an Assistant Professor and later Associate Professor at Northern Illinois University (NIU), and completed a postdoctoral fellowship at the University of Pennsylvania. His research focuses on fluid-structure interaction, high-performance computing, multiscale modeling, and machine learning applications in engineering and medicine. He holds a BS in Civil Engineering from Beijing Jiaotong University and MS/PhD in Mechanical Engineering from Lehigh University. Notable recognitions include the 2024 David W. Raymond Award for Teaching Technology Innovation and the 2024 NSF CAREER Award. His research interests span computational fluid dynamics, microfluidic device design for cell separation, blood flow modeling, and thrombosis simulation. He develops open-source codes for multiphysics simulations and has pioneered parallel fluid-structure interaction models for nanoparticle transport and cellular suspensions. His work integrates physics-based machine learning and data-driven models to address challenges in healthcare and engineering. Recent contributions include studies on granular flow dynamics in conveyor systems, biomimetic fish locomotion analysis, and predictive modeling of disease transmission using dynamic mode decomposition. He collaborates with Argonne National Laboratory on multiphysics research and actively mentors students in computational and experimental projects. Scientific achievements include advancements in microfluidic sorting techniques, nanoparticle delivery systems, and computational tools for in situ visualization of blood flow simulations. His lab focuses on translating multiscale simulations into practical applications for drug delivery, medical diagnostics, and sustainable engineering solutions.

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Christoph KirschView profile

Researcher

Zurich University of Applied Sciences (ZHAW)Switzerland

Christoph Kirsch is a Researcher at the ZHAW School of Engineering's Department of Organic Electronics & Photovoltaics. His work focuses on interdisciplinary research spanning organic electronics, photovoltaics, materials science, and biomedical engineering. He holds a PhD in Applied Mathematics from the University of Basel (2005) and an MSc in Mathematics from ETH Zurich (2001). His research emphasizes advanced modeling techniques for semiconductor devices, thermal imaging systems, and porous media processes. Key projects include: Advanced Imaging and Machine Learning for PV Quality Assurance Advanced Materials and Characterization Tools for Quantum-Dot Enhanced Displays Skinobi – Affordable Sensor for Skin Condition Tracking Research interests include OLED device simulation, solar cell characterization, and thermal properties of biological tissues. Recent work explores non-invasive skin thermal diffusivity measurement and charge transport modeling in organic semiconductors. His publications reflect a strong focus on multiscale modeling and experimental validation across materials science and biomedical applications. Notable contributions include: Electrothermal modeling of large-area semiconductor devices Development of mathematical models for intradermal drainage quantification Lock-in thermal imaging setups for nanoparticle detection Currently leads the Organic Electronics & Photovoltaics research group at ZHAW, collaborating with industry partners on applied materials science and device optimization projects.

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Gary D. SeidelView profile

Professor

Virginia Polytechnic Institute and State UniversityUnited States

Dr. Gary D. Seidel is a Full Professor and Assistant Department Head for Academic Affairs at the Virginia Polytechnic Institute and State University's College of Engineering. He earned his Ph.D., M.S., and B.S. in Aerospace Engineering from Texas A&M University (2007, 2002, 1999) and has held academic positions at Virginia Tech since 2008. His research focuses on multiscale modeling of damage evolution in multifunctional composites, particularly those incorporating carbon nanotubes. Ph.D., Aerospace Engineering, Texas A&M University, 2007 M.S., Aerospace Engineering, Texas A&M University, 2002 B.S., Aerospace Engineering, Texas A&M University, 1999 Dr. Seidel's research bridges atomistic and continuum scales to analyze piezoresistivity, fracture mechanics, and multifunctional properties in nanocomposites. He develops computational tools for modeling damage in materials used for hypersonic vehicles, lunar structures, and energetic materials. His work integrates micromechanics with advanced sensor systems and topology optimization for structural health monitoring. His recent publications focus on multiscale modeling of CNT-polymer composites, thermomechanical properties of ultra-high temperature ceramics, and piezoresistive damage sensing networks. These align with keywords like computational mechanics, nanotechnology, and materials science, covering subfields such as peridynamics, interfacial modeling, and stochastic microstructure analysis. Scientific Awards: ASME Fellow (2020) AIAA Associate Fellow (2013) AFRL Summer Faculty Fellow (2017-2021) Oak Ridge Ralph E. Powe Award (2010) ASME/Boeing Best Paper Award (2016) Dr. Seidel serves as Associate Editor for Applied Mechanics Reviews and Smart Materials and Structures , and actively participates in AIAA and ASME technical committees. He co-directs the Aerospace Structures and Materials Lab (ASML) and mentors NASA MUST undergraduate researchers, demonstrating commitment to both academic leadership and student development.

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