جست‌وجوی استاد و پژوهشگر

Deji Aremuمشاهده پروفایل

مدرس

• Additive Manufacturing
• Mechanical Engineering
• Materials Science
• +۸ مورد دیگر

Deji Aremu is a Lecturer in Mechanical Engineering at the CEES School of Engineering. He holds a Doctorate in Mechanical and Manufacturing Engineering from Loughborough University, specializing in Topology Optimization for Additive Manufacturing, alongside an MSc in Manufacturing Systems Engineering from the University of Warwick and a degree in Metallurgical and Material Engineering from Obafemi Awolowo University. His research focuses on additive manufacturing, composites, and finite element analysis, with notable contributions to machine learning applications in materials science. Education: Doctorate in Mechanical and Manufacturing Engineering (2009–2013), Loughborough University MSc in Manufacturing Systems Engineering (2006–2007), University of Warwick Bachelor’s in Metallurgical and Material Engineering (1998–2005), Obafemi Awolowo University His research interests include additive manufacturing techniques, mechanical properties of composite materials, lattice structures, and structural optimization. He employs machine learning to enhance parameter optimization and predictive modeling in materials processing. Recent work explores porosity effects in thermoplastic composites and crashworthiness of polymer-based honeycomb structures. Dr. Aremu supervises PhD projects on additive manufacturing for developing nations, algorithm development for lattice structures, and material design for cost-effective metal AM processes. He actively collaborates on global engineering challenges, particularly leveraging AM for third-world infrastructure solutions.

Aleksandar Bodićمشاهده پروفایل

پژوهشگر

• Mechanical Engineering
• Structural Analysis
• Numerical Simulations
• +۳ مورد دیگر

Aleksandar Bodić is a Researcher at the Department of Applied Mechanics and Automatic Control, Faculty of Engineering, University of Kragujevac, Serbia. His research focuses on structural analysis, materials science, numerical simulations, and biomedical engineering applications. He holds a position in the Applied Mechanics and Automatic Control department and is affiliated with the university's broader engineering community. His work integrates computational methods like the Finite Element Method (FEM), Smoothed Particle Hydrodynamics (SPH), and Finite Volume Method (FVM) to address challenges in mechanical, civil, and biomedical engineering. Notable areas include piezoelectric nanocomposites, blast-resistant structures, dental material performance, and cardiovascular fluid dynamics. His recent studies emphasize predictive modeling for structural safety, fatigue analysis, and particle dynamics in medical devices. Research interests span advanced materials characterization, structural dynamics under extreme conditions, and computational tools for engineering problem-solving. He collaborates on projects involving interdisciplinary applications, such as improving muzzle brake efficiency for firearms and optimizing drug delivery systems via dry powder inhalers. No academic awards or grants are explicitly mentioned in the provided information. His advisory role and student supervision details are currently unavailable. Affiliated with the Faculty's technical and research infrastructure, his work contributes to the Department for Applied Mechanics and Automatic Control's broader mission in advancing engineering science and technology.

Raimund Wegenerمشاهده پروفایل

پژوهشگر

• Fiber Dynamics
• Computational Fluid Dynamics
• Industrial Mathematics
• +۳ مورد دیگر

Raimund Wegener is a researcher at the Fraunhofer Institute for Industrial Mathematics ITWM in Kaiserslautern. His work focuses on modeling fiber dynamics, kinetic theories, and industrial processes, particularly in the context of nonwoven materials and melt spinning. He specializes in developing numerical frameworks and stochastic models to simulate complex systems involving viscoelastic fluids, turbulent airflow interactions, and material behavior under various conditions. His research integrates applied mathematics, computational fluid dynamics, and mechanical engineering to address challenges in manufacturing processes like aerodynamic web forming, electrospinning, and nonwoven production optimization. Key contributions include advancements in predictive modeling for tensile strength inference, boundary condition formulations for viscoelastic fibers, and Pareto-optimized mass distribution strategies. Wegener’s methodologies bridge theoretical models with industrial applications, leveraging asymptotic analysis, finite volume methods, and regression-based approaches. His work is published in journals like the Journal of Computational Physics and Applied Mathematical Modeling, with a strong emphasis on interdisciplinary collaboration.

Andreas Juttnerمشاهده پروفایل

استاد

• Theoretical Physics
• Particle Physics
• Quantum Chromodynamics (QCD)
• +۳ مورد دیگر

Professor Andreas Juttner is a Professor of Theoretical Physics at the University of Southampton, affiliated with the Department of Physics and Astronomy. His research focuses on lattice Quantum Chromodynamics (QCD), particle physics, and high-energy phenomena, with particular emphasis on semileptonic decays and computational methods in theoretical physics. He leads or co-leads multiple international research projects funded by the EPSRC, STFC, and the European Union, including the EXA-LAT project exploring lattice field theory at the exascale and the ERC-funded NEWPHYSICSHPC initiative. His work spans lattice calculations of form factors, systematic error analysis in inclusive decays, and interdisciplinary collaborations on quantum gravity via holography. Current PhD students under his supervision include Ahmed Elgaziari (PhD Physics & Astronomy), Rajnandini Mukherjee (PhD Physics), and Callum James Radley-Scott (PhD Physics). He is a member of the Southampton High Energy Physics (SHEP) group and the STAG Research Centre. Recent publications emphasize precision studies of B and D meson decays, lattice QCD benchmarking (FLAG Review 2024), and Bayesian methods for form factor analysis. Research projects include exploring exascale computing's role in advancing lattice field theory and probing new physics through collider and gravitational wave observables.

Xinfeng Liuمشاهده پروفایل

استاد

• Computational Biology
• Mathematical Modeling of Cancer Stem Cells
• Signal Transduction
• +۴ مورد دیگر

Xinfeng Liu serves as Professor and Undergraduate Director in the Department of Mathematics at the University of South Carolina. His academic journey includes progression from Assistant Professor (2009-2013) to Associate Professor (2013-2017) and finally to full Professor (2018-present), following a Visiting Assistant Professor position at UC Irvine (2006-2009). His research spans Computational Biology with focus on cancer stem cell modeling and signal transduction mechanisms, alongside Numerical PDEs specializing in front tracking methods and integration factor techniques. Liu's work bridges mathematical theory with biological applications, particularly in morphogen gradient formation and MAPK cascade regulation. His computational approaches address complex phenomena like Rayleigh-Taylor instability in fluid dynamics. Liu's recent publications demonstrate strong trends in developing numerical methods for free boundary problems in biological systems, with significant contributions to cancer stem cell modeling. His work increasingly integrates stochastic elements and time-delay systems in therapeutic response modeling. NSF Mathematical Biology Division grant DMS1853365 (2019-2022) NSF Mathematical Biology Division grant DMS1308948 (2013-2017) NSF Mathematical Biology Division grant DMS1019544 (2010-2014) University of South Carolina ASPIRE I grant (2013-2014) South Carolina EPSCoR/IDeA GEAR program (2011-2013) Liu has mentored three doctoral students to completion, all securing competitive postdoctoral positions at Los Alamos National Lab, University of Waterloo, and University of North Texas. His teaching portfolio spans computational mathematics, differential equations, and advanced analysis courses since 2009, including honors sections and specialized topics like Modeling of Complex Biological Systems.

Yoichiro Moriمشاهده پروفایل

استاد

• Mathematical Biology
• Physiology
• Biophysics
• +۴ مورد دیگر

Yoichiro Mori is the Calabi-Simons Professor in Mathematics and Biology at the University of Pennsylvania, affiliated with the School of Arts and Sciences. His positions span the Department of Mathematics and the Department of Biology, reflecting his interdisciplinary research focus. He holds an office in both DRL 4N20 (Math) and Levin 352 (Biology). His research interests encompass Mathematical Biology, Physiology, Biophysics, and Applied and Numerical Analysis. Key areas include electrodiffusion theory, cell volume regulation, fluid dynamics of elastic structures, and computational models of physiological processes like cortical spreading depression and cardiac electrophysiology. Mori’s recent work emphasizes theoretical and numerical analysis of slender body theory, ion transport phenomena, and the interplay between cellular mechanics and biochemical signaling. Notable contributions include studies on the Peskin problem, osmotic water flow, and the dynamics of deformable membranes in viscous fluids. His publications frequently address topics such as cell migration energetics, multidomain electrodiffusion models, and mathematical frameworks for biological systems. Collaborations span applied mathematics, bioengineering, and experimental biology, with a focus on bridging theoretical models and real-world biological phenomena.

• Computational Mechanics
• Stochastic Finite Elements
• Multiscale Modeling
• +۳ مورد دیگر

Professor Chenfeng Li FLSW is Chair in Civil Engineering at Swansea University and Co-Director of the Zienkiewicz Institute for Modelling, Data and AI. An internationally recognized expert in computational engineering, he develops innovative solutions for civil infrastructure, materials science, and energy sectors. Professor Li's research focuses on computational mechanics, uncertainty quantification, and risk assessment. His methods address technical challenges in water-energy-food systems, geotechnical engineering, and manufacturing. Collaborations with industry leaders like ARUP, Costain, and Bauer translate research into practical applications for infrastructure and construction. Key research areas include: Stochastic finite element methods Multiscale modeling of materials Fluid-structure interaction Uncertainty quantification in complex systems Digital reconstruction of microstructures He leads the module 'Design and Analysis for Temporary Works' for MSc Civil Engineering students, providing continuing professional development for industry practitioners. Honors include Fellowship in the Learned Society of Wales. Professor Li serves as Editor-in-Chief of Engineering Computers and contributes to international research networks addressing global infrastructure challenges.

• Thermodynamics
• Heat Transfer
• Fluid Dynamics
• +۴ مورد دیگر

Marco Cavazzuti is an Associate Professor at the Department of Engineering Sciences and Methods (DISMI) at the University of Modena and Reggio Emilia. His research focuses on thermodynamics, fluid dynamics, and energy systems, with a particular emphasis on computational fluid dynamics (CFD), heat transfer, and renewable energy applications. Cavazzuti teaches courses in Energy Engineering, Thermofluid Dynamics, and Industrial Heat Engineering, integrating theoretical and practical components with computational tools like OpenFOAM and Python. His research interests include multi-scale modeling of respiratory droplet transport for infectious disease risk assessment, plate-fin heat exchanger optimization, and thermal management of electric motors. He has contributed to projects like the IDEAS initiative for multi-source heat pump systems and the analysis of tunnel ventilation systems using 1D finite volume models. Cavazzuti's work spans both academic and industrial collaborations, addressing challenges in energy efficiency, CFD validation, and thermal system design. Key research trends in his publications include CFD-based modeling of complex flows (e.g., micro-channels, swirled jets), epidemiological droplet transport analysis, and optimization of thermal systems for renewable energy integration. He has also explored applications in automotive chassis design and cardiovascular flow dynamics using ultrasound and computational methods.

Luca Del Zannaمشاهده پروفایل

دانشیار

• Plasma Astrophysics
• Relativistic Magnetohydrodynamics (MHD)
• Neutron Stars
• +۳ مورد دیگر

Luca Del Zanna is an Associate Professor at the Department of Physics and Astronomy , University of Florence. He holds dual affiliations with the University of Florence (UniFi) and the National Institute for Astrophysics (INAF). His research focuses on plasma astrophysics, relativistic magnetohydrodynamics (MHD), and compact objects such as neutron stars and black holes. He leads the Space Plasma and Astrophysics Group at UniFi and co-organizes international workshops like the Arcetri Workshop on Plasma Astrophysics and Vlasovia . Research Interests include relativistic MHD simulations, magnetic reconnection, accretion disk dynamics, and the development of computational tools like the ECHO and XNS codes. His work bridges theoretical and numerical approaches to understand astrophysical phenomena such as gamma-ray bursts, pulsar wind nebulae, and solar/heliospheric processes. Recent Activities : Hosted SoHe4 (2023) and Vlasovia 2024 (2024), co-organized the INFN-TEONGRAV meeting (2022), and commemorated the legacy of Claudio Chiuderi (2022). His research group actively collaborates on projects like the XPE mission and explores multi-scale plasma physics. Publications span over two decades, emphasizing numerical methods, relativistic plasma dynamics, and high-energy astrophysics. He is a key developer of the ECHO code, used for GRMHD simulations of neutron stars and accretion disks.

• Numerical Methods for Partial Differential Equations
• Fractional Partial Differential Equations
• Inverse Problems
• +۳ مورد دیگر

Abdallah BRADJI is a Full Professor of Mathematics at the University of Annaba-Algeria (since January 2015), affiliated with the Department of Mathematics in the Faculty of Sciences. He holds a PhD from Aix-Marseille University (2005) and a French Habilitation (HDR) from Aix-Marseille University (2016). His research focuses on numerical methods for partial/fractional PDEs, inverse problems, and computational modeling with COMSOL Multiphysics. He has held postdoctoral positions at the Weierstrass Institute (Berlin, Germany) and the Nečas Center (Prague, Czech Republic). Teaching roles include lecturing in undergraduate and graduate courses (e.g., Numerical Analysis, Finite Elements, Operational Research) since 1994, with recent responsibilities in Master’s programs in Metallurgy and Process Engineering. He has been invited as a Visiting Professor at Sorbonne University Paris Nord (2024) and LAGA Paris 13 (multiple visits), and has reviewed for prestigious journals like Comptes Rendus (CRAS) and ESAIM:M2AN. Research interests span numerical methods for fluid mechanics, fractional differential equations, and convergence analysis of finite volume/element schemes. His work emphasizes high-order accuracy and stability in complex applications.

Mirko Rokytaمشاهده پروفایل

دانشیار

• Mathematical Analysis
• Partial Differential Equations
• Numerical Methods
• +۳ مورد دیگر

Doc. RNDr. Mirko Rokyta, CSc. is the Dean of the Faculty of Mathematics and Physics (MFF UK) at Charles University, serving since 2020. He holds the academic rank of Associate Professor in the Department of Mathematical Analysis (KMA). His academic career includes roles as Vice-Dean for Mathematics, Head of KMA, and various leadership positions within MFF UK. Rokyta earned his RNDr. (M.Sc.), CSc. (Ph.D.), and docent (Associate Professor) degrees from MFF UK. His research focuses on mathematical analysis, numerical methods for partial differential equations, and finite volume schemes. As Dean, he prioritizes faculty development, internationalization, and efficient administration while maintaining academic excellence. His work includes contributions to computational fluid dynamics and error analysis in numerical methods. Education: RNDr. (M.Sc.) in Mathematics, 1985 CSc. (Ph.D.) in Mathematics, 1992 Docent (Associate Professor), 2000 Administrative Roles: Dean of MFF UK (2020–2028) Vice-Dean for Mathematics (2012–2020) Head of KMA (2002–2010) Research interests span theoretical and numerical analysis, with emphasis on fluid dynamics and conservation laws. Recent publications address finite volume schemes, convergence proofs, and error estimates. Rokyta actively promotes international collaboration and modernizes faculty operations through digitization and infrastructure improvements.

David Doweمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Data Mining
• +۵ مورد دیگر

David L. Dowe is an Associate Professor in the Department of Data Science & AI at Monash University's Faculty of Information Technology. He holds academic qualifications including a PhD in Mathematics from Monash University (1991), MSc in Econometrics from the London School of Economics (1987), and BSc (Honours) in Mathematics from the University of Melbourne (1982). His research focuses on Minimum Message Length (MML) inference, artificial intelligence, and machine learning applications in diverse domains such as healthcare, environmental science, and bioinformatics. Teaching responsibilities include units like FIT4009 (Advanced Topics in Intelligent Systems), FIT5158 (Customer Relationship Management and Data Mining), and others. He has led or collaborated on ARC-funded projects like 'New Statistical Techniques for Galactic Archaeology' (2016–2019) and 'Rating and ranking sports players using MML' (2011–2017). His work contributes to UN Sustainable Development Goals related to education and innovation. Recent research highlights include developing deep learning frameworks for brain disorder identification, predictive AI models for bacterial drug resistance, and hybrid statistical-LSTM forecasting. He emphasizes interdisciplinary applications of MML in fields ranging from climate modeling to medical imaging.

Olivier Martinمشاهده پروفایل

استاد

• Plasmonics
• Nanophotonics
• Nonlinear Optics
• +۱۰ مورد دیگر

Overview Prof. Olivier Martin is a Full Professor of Nanophotonics and Optical Signal Processing at École Polytechnique Fédérale de Lausanne (EPFL), leading the Laboratory of Nanophotonics and Metrology. He holds academic roles in multiple departments including STI's Microengineering and Electrical & Electronics Engineering programs, and oversees doctoral training in Photonics and related fields. His research focuses on plasmonics, nonlinear optics, and metamaterials, with applications in biosensing, optical forces, and nano-manufacturing. Education PhD in Physical Sciences (EPFL, 1994) Engineering Degree (EPFL, 1989) Research Interests Dr. Martin’s work combines numerical simulations, advanced nanofabrication, and experimental techniques to study plasmonic nanostructures. Key areas include metasurface design, nonlinear optical effects, optical trapping, and heterogeneous catalysis. His lab has pioneered studies on anisotropic second-harmonic generation, tunable optical forces, and plasmonic-based security technologies. Publications & Awards With over 300 peer-reviewed articles and patents, his 2016 ERC Advanced Grant supported research into optical-force-driven nanofabrication. He is a Fellow of Optica and serves on editorial boards of Advanced Photonics and Frontiers in Physics . Advising & Leadership Directed 25+ PhD theses at EPFL Directed EPFL’s Doctoral Program in Photonics (2005–2017) Reformed Microtechnology curriculum, launching the Robotics Master’s program Labs & Groups He heads the Laboratory of Nanophotonics and Metrology, focusing on cutting-edge research in nanoscale optical systems and their practical implementations.

Annegret Glitzkyمشاهده پروفایل

استاد پژوهشی

• Partial Differential Equations
• Semiconductor Technology
• Reaction-Diffusion Systems
• +۳ مورد دیگر

Annegret Glitzky is a Research Professor at the Weierstrass Institute for Applied Analysis and Stochastics (WIAS) in Berlin, Germany. She specializes in the Department of Partial Differential Equations, focusing on mathematical modeling and numerical analysis in semiconductor technology, reaction-diffusion systems, and energy models. Her work integrates advanced analytical techniques with computational methods, particularly Voronoi finite volume discretization. With a Dr. rer. nat. habil., she has contributed extensively to the understanding of spin-polarized systems, electrochemical processes, and material interfaces through interdisciplinary research. Her research emphasizes energy estimates, stability analysis, and numerical simulations for complex systems, including semiconductor devices and optoelectronic applications. Notable contributions include studies on the uniform exponential decay of free energy in discretized reaction-diffusion systems and the development of discrete Sobolev-Poincaré inequalities for finite volume approximations. She has presented her findings at major international conferences such as the GAMM Annual Meetings and the International Congress of Mathematicians. Glitzky collaborates with academic and industrial partners, applying mathematical tools to solve real-world problems in energy technology and material science. Her work bridges theoretical analysis and practical engineering, reflecting a commitment to advancing computational methods in applied mathematics.

• Paleoclimatology
• Ocean Circulation
• Climate Modeling
• +۳ مورد دیگر

Dr. Pengyang Song is a Researcher at the Alfred Wegener Institute (AWI) in Bremerhaven, Germany, affiliated with the department 'Dynamik des Paläoklimas'. His work focuses on paleoclimatology, tidal dynamics, and ocean circulation modeling. He contributes to the Finite-volumE Sea ice–Ocean Model (FESOM2.1), exploring tidal effects and their implications for climate systems. Research interests include the Atlantic Meridional Overturning Circulation (AMOC), glacial ocean dynamics, and the interplay between tidal mixing and stratification. His recent studies address how vertical stratification influences glacial AMOC behavior despite vigorous tidal dissipation. Publications highlight advancements in modeling tidal processes and their impact on ocean circulation patterns. Collaborations involve experts in climate modeling and geophysical fluid dynamics, with a focus on paleoceanographic reconstructions.