جست‌وجوی استاد و پژوهشگر

• Partial Differential Equations
• Integral Equations
• Inverse Scattering Problems
• +۳ مورد دیگر

Vassilios Sevroglou is a Professor at the Department of Statistics and Insurance Science, University of Piraeus, School of Finance and Statistics. His academic career spans since 2002, with roles including Assistant Lecturer (2002-2006) and Lecturer (2007-2011) at the same university, and visiting positions at the University of Ioannina. He holds a PhD in Applied Mathematics and a bachelor's degree in Mathematics from the National and Kapodistrian University of Athens. His research focuses on Partial Differential Equations, Integral Equations (Riesz-Fredholm Theory), and inverse scattering problems in elasticity and acoustics. Key areas include 2D/3D elastic wave scattering, thermoelastic interactions, chiral media applications, and computational methods for boundary value problems. The 15 most recent articles highlight advancements in chiral electromagnetic scattering, stochastic boundary value problems, thermoelastic wave interactions, and numerical reconstruction techniques. These works emphasize inverse problems, Wiener chaos expansions, and regularization methods in acoustics and elasticity. Teaching activities encompass Calculus, Differential Equations, Stochastic Finance, and advanced applied mathematics courses. No specific scientific awards or lab affiliations are mentioned in the provided texts.

• Applied Mathematics
• Nanotechnology
• Granular Materials
• +۳ مورد دیگر

Professor Natalie Thamwattana holds a position at the University of Newcastle's School of Information and Physical Sciences, specializing in Mathematics. She has been recognized with prestigious awards, including the 2014 JH Michell Medal and the University of Wollongong's Emerging Researchers Excellence Award. Her research focuses on applied mathematics, nanotechnology, and granular materials, with notable contributions to carbon nanostructure modeling and electrorheological fluids. Natalie has supervised ten PhD students, many of whom now hold academic and research roles globally. Education: Doctor of Philosophy in Applied Mathematics, University of Wollongong Research Interests: Natalie's work bridges mathematics and interdisciplinary applications, including nanomechanics, mathematical modeling of nanostructures (e.g., carbon nanotubes, graphene), and fluid dynamics. She pioneered studies on granular materials' exact solutions and developed continuum models for molecular interactions. Her contributions extend to environmental applications, such as permeable reactive barriers and dye-sensitized solar cells. Grants & Collaborations: ARC Discovery Project (2017-2019) on electromaterials for energy ARC Linkage Project (2020-2022) on clogging in reactive barriers Collaborations with engineering, computer science, and medical fields Awards & Recognition: Fellow of the Australian Mathematical Society Fellow of the Royal Society of New South Wales Featured in the 'Women of Mathematics' exhibition Labs & Leadership: Natalie directed the Priority Research Centre for Computer-Assisted Research Mathematics and its Applications (CARMA) and co-directed the Mathematics in Industry Study Group (MISG). She is actively involved in promoting gender equity in mathematics through roles in WIMSIG and outreach programs targeting high school students.

• Partial Differential Equ
• Wave Scattering
• Hydroelasticity
• +۵ مورد دیگر

Professor Mike Meylan is an applied mathematician at the University of Newcastle 's School of Information and Physical Sciences ( Department of Mathematics ). His work bridges differential equations, wave scattering, and hydroelasticity, with applications to ocean engineering, ice floe dynamics, and railway infrastructure. He has received multiple Australian Research Council grants and collaborates internationally with institutions like the University of Cambridge and Indian Institute of Technology Kharagpur. Research interests include Wave propagation in ice shelves and marginal ice zones Wave energy conversion using piezoelectric plates Fluid-structure interactions in marine environments Mathematical modeling of railway ballast scour Development of eigenfunction matching and singularity-respecting numerical methods Recent publications focus on Time-domain vibration analysis of cracked and circular ice shelves Acoustic-gravity wave dynamics in compressible oceans Wave scattering by porous barriers and heterogeneous plates His work has been published in Nature , Journal of Fluid Mechanics , and Proceedings of the Royal Society . He serves as Editor-in-Chief of the ANZIAM Journal and Associate Editor for Wave and Tidal Energy at Frontiers in Energy Research . Awards include the 2012 Teaching Award at the University of Newcastle.

• Dynamic Fracture Mechanics
• Penetration Mechanics
• Aeroelasticity
• +۵ مورد دیگر

Yuri Antipov is a Professor in the Department of Mathematics at Louisiana State University (LSU). His work focuses on applied mathematics, particularly in dynamic fracture mechanics, fluid dynamics, and scattering of electromagnetic waves. He has held academic positions at LSU since 2002, including roles as Associate Professor (2002–2004) and Professor (2004–present). Prior roles include Lecturer/Research Officer at the University of Bath (1997–2002), Humboldt Foundation Fellow at the University of Stuttgart (1996–1997), and academic roles at Odessa State University (1982–1995). Education: Ph.D. (Doctor in Sciences) in Solid Mechanics from Moscow State University (1993), Ph.D. (Candidate in Sciences) in Differential Equations from Odessa State University (1983), and a Diploma in Applied Mathematics (1979). Research Interests include mathematical modeling of crack propagation, supercavitating flows, and Riemann-Hilbert boundary-value problems. His work integrates advanced analytical methods like automorphic functions and Riemann surfaces to solve complex problems in elasticity and fluid dynamics. Recent publications span topics like graded materials, vortex dynamics, and coupled thermoelasticity models. Notable contributions include studies on fracture mechanics in heterogeneous media, scattering theory for anisotropic materials, and the development of exact solutions for functional-difference equations using Riemann surfaces.

Alexander G. Rammمشاهده پروفایل

استاد

• Wave Scattering
• Inverse Problems
• Mathematical Physics
• +۳ مورد دیگر

Dr. Alexander G. Ramm is Professor of Mathematics at University of Kansas, specializing in mathematical physics and scattering theory. With a PhD from Moscow State University (1964) and Dr.Sci from Mathematics Institute, Minsk (1972), his career includes positions at Leningrad Institute of Precision Mechanics and Optics. Research: Develops asymptotic solutions for wave scattering by small particles, creating materials with engineered refraction properties. His work enables negative refraction materials and customized wave-focusing capabilities through particle distribution design.

Hannah Pinsonمشاهده پروفایل

استاد

• Neural Networks
• Artificial Intelligence
• Computational Neuroscience
• +۳ مورد دیگر

Hannah Pinson is a part-time professor at Vrije Universiteit Brussel (VUB) conducting interdisciplinary research at the intersection of artificial and biological neural networks. Her work integrates experimental, computational, and mathematical methodologies to investigate fundamental neural network principles within the Brussels Humanities, Sciences & Engineering Campus environment. Academic background includes: Master's studies in Physics and Computer Science at VUB with research at MIT's Tegmark group (2017) PhD research commenced 2018 under Prof. Ginis as an FWO fellow, featuring experimental work at Tufts University (Levin lab) and Harvard Medical School (Sahin lab) Her research centers on form-function relationships in neural systems, examining how structural properties determine computational capabilities across artificial and biological networks. Current investigations analyze complexity development in deep neural architectures, dataset-network interactions, and physics-inspired solutions for optical design challenges. This multidisciplinary approach bridges theoretical computer science with experimental neuroscience. Publication analysis (2019-2024) reveals dual research trajectories: theoretical neural network science addressing complexity and optimization landscapes, and biomedical engineering innovations for mechanical ventilation systems developed during pandemic conditions. Her work consistently demonstrates cross-domain applicability from optical component design to critical care medicine. Recognized achievements include: FWO fellowship for doctoral research Funding for doctoral work came through the competitive FWO fellowship, enabling international laboratory collaborations. Current academic mentoring activities are not explicitly documented but align with her part-time professorial role. Experimental capabilities were developed through partnerships with leading neuroscience laboratories at Tufts and Harvard institutions. Her research ecosystem combines VUB's computational resources with experimental facilities from the Levin lab (Tufts) and Sahin lab (Harvard Medical School), creating a unique infrastructure for testing neural network theories against biological systems while advancing medical device engineering.

Kevin Leoمشاهده پروفایل

پژوهشگر ارشد

• Constraint Programming
• Modelling
• Presolving
• +۳ مورد دیگر

Kevin Leo is a Research Fellow in the Department of Data Science & AI at Monash University. His work contributes to the United Nations Sustainable Development Goals (SDGs), though specific goals are not detailed in the text. **Research Interests**: Constraint Programming Modelling and Presolving Techniques Operations Research Programming Languages Algorithm Design for Optimization Applications in Medical Science and Autonomous Systems His recent research emphasizes core-guided reformulation, human-centred feasibility restoration, and globalization of constraint models. These advancements address both theoretical challenges and real-world applications such as UAV autonomy and medical treatment planning. Collaborations with international researchers are noted, though specifics are not elaborated. Kevin has no recorded part-time status or scientific awards. His advising and grants sections remain empty, with no listed students or active grants. His contributions focus on peer-reviewed publications in artificial intelligence and constraint satisfaction domains.

Markus Heglandمشاهده پروفایل

استاد

• Computational Mathematics
• High-Dimensional Problems
• Ill-Posed Problems
• +۴ مورد دیگر

Markus Hegland is a Professor and Head of the Centre for Mathematics and its Applications (CMA) at the Australian National University (ANU). He holds a PhD from ETH Zurich (1988) and has been affiliated with ANU since 1992, focusing on High-Performance Computing (HPC) and numerical analysis. As a Hans Fischer Senior Fellow at TUM-IAS, his research emphasizes high-dimensional problems, ill-posed systems, and data mining applications. His work bridges computational mathematics with practical domains like systems biology and spectral enhancement. Research interests include sparse grid techniques, regularization methods, and algorithm development for HPC. Notable contributions include the OPTICOM method for stable sparse grid solutions and convergence theory for variable Hilbert scales regularization. He has led projects on fault-tolerant HPC algorithms and collaborated with Fujitsu on HPC applications. Publications span numerical analysis, bioinformatics, and computational physics. His work on the chemical master equation and gyrokinetics showcases interdisciplinary impact. Currently, he explores resilient grid-based solvers and machine learning integration with HPC frameworks. No awards are explicitly listed, but his senior fellowship underscores recognition in his field. Grants and collaborations include ARC-funded research in bioinformatics and HPC resilience. His work on digital twins and algorithm optimization reflects broader interests in advanced computational modeling. He is actively involved in teaching and supervising in computational mathematics and data science at ANU.

• Management Accounting
• Operations Research
• Cost System Design
• +۵ مورد دیگر

Vic Anand is an Assistant Professor of Accountancy at the University of Illinois. His research focuses on operations research, management accounting, and the application of computational methods in accounting. Key areas include cost system design, decision-making under uncertainty, and leveraging machine learning for profitability prediction. He has collaborated on projects involving numerical experiments in cost analysis and frameworks for capacity planning with limited information. Anand also explores behavioral aspects of goal progress feedback and its impact on organizational performance. His academic contributions span Python-based text analysis techniques in accounting research and interdisciplinary applications of biomechanical modeling. Notable works include studies on genetic algorithms and network topology inference from sparse data. Anand has published in journals like Production and Operations Management and Journal of Management Accounting Research. His research has been cited over 40 times, with significant reader engagement on platforms like Mendeley. Anand’s work bridges theoretical models with practical business applications, emphasizing both technical rigor and real-world relevance. He has pioneered methodologies for improving productivity through site-based training and developed frameworks for informationally consistent cost decision-making.

Jan-Hendrik Bastekمشاهده پروفایل

پژوهشگر

• Computational Mechanics
• Mechanical Metamaterials
• Physics-Informed Machine Learning
• +۳ مورد دیگر

Jan-Hendrik Bastek is a Researcher affiliated with the Department of Mechanics and Materials Research at ETH Zürich. His work focuses on computational mechanics, mechanical metamaterials, and the application of physics-informed machine learning in engineering challenges. Based in Zürich, Switzerland, he contributes to advancing material design through interdisciplinary approaches that integrate deep learning, inverse problem solving, and advanced modeling techniques. His research interests span topics such as nonlinear mechanics, material property prediction, and the development of novel metamaterials with tailored properties. He has published extensively on physics-informed neural networks, data-driven simulation methods, and the optimization of truss-based metamaterials. His work bridges computational science and engineering applications, emphasizing practical solutions for complex structural and material systems. Recent publications highlight trends in applying video denoising diffusion models for metamaterial design, GNN-assisted phase space integration, and viscoelastic behavior analysis of time-dependent materials. His contributions reflect a commitment to merging traditional mechanics with cutting-edge AI techniques to address forward and inverse problems in computational mechanics. No scientific awards or grants are explicitly listed in the provided information. Bastek collaborates within the Mechanics and Materials Research group at ETH Zürich, contributing to both fundamental and applied research projects in the field.

Stefano van Goghمشاهده پروفایل

پژوهشگر

• Medical Imaging
• Breast Cancer
• Computer Vision
• +۳ مورد دیگر

Dr. Stefano van Gogh is a Researcher affiliated with the Department of X-ray Imaging at ETH Zurich. His research focuses on advanced imaging techniques, particularly in breast cancer diagnosis and X-ray technologies. He holds a position within the Professorship for X-ray Imaging, contributing to interdisciplinary projects involving computer vision and deep learning applications in medical imaging. Research Interests: Breast imaging, Grating Interferometry Breast Computed Tomography, and inverse problem solutions in medical imaging. His work bridges computational methods (e.g., deep learning) with clinical challenges in oncology and diagnostic radiology. No academic awards or grants are explicitly documented in the provided materials. He can be contacted at svangogh@ethz.ch .

• Machine Learning
• Computer Vision
• Data Science
• +۴ مورد دیگر

Xiaojun Li is a Professor affiliated with the Department of Mechanical Engineering at the University of Maryland, with additional research ties to Texas A&M University and institutions in China. His work spans interdisciplinary fields including machine learning, computer vision, and engineering systems. He has contributed to over 130 publications since 1985, focusing on topics like deep learning applications in healthcare, seismic modeling, and intelligent systems for infrastructure. His research emphasizes practical solutions in domains such as medical diagnostics, tunnel construction optimization, and energy forecasting. Key contributions include the development of JaunENet for jaundice detection, advanced seismic wave modeling techniques, and intelligent systems for automated tunnel construction. He collaborates extensively with experts in data science, environmental engineering, and computer science. His work bridges theoretical advancements with real-world applications, addressing challenges in healthcare technology, sustainable infrastructure, and energy management. Recent projects highlight innovation in multimodal hate speech detection, smart evacuation systems using VR, and the application of graph-based methods for EEG emotion recognition. His research often integrates big data analytics and AI-driven approaches to solve complex problems in both technical and societal contexts.

Sara Lombardoمشاهده پروفایل

استاد

• Integrable Systems
• Automorphic Lie Algebras
• Nonlinear Waves
• +۴ مورد دیگر

Sara Lombardo is a Professor of Mathematics and Executive Dean of the School of Mathematical & Computer Sciences at Heriot-Watt University, UK. She holds visiting roles at Loughborough University, Sapienza University of Rome, and the Vrije Universiteit Amsterdam. A graduate of the University of Rome La Sapienza (MSc in Mathematical Physics) and Leeds University (PhD in Mathematics), her career includes positions at Leeds, Manchester, Rome, and Amsterdam before her current role. Her research focuses on integrable systems, automorphic Lie algebras, nonlinear waves, and rogue waves, supported by fellowships from EPSRC, NWO, and IRCSET. Research interests include infinite-dimensional algebras, nonlinear PDEs, and mathematical modeling. She advocates for interdisciplinary research and diversity in science. Awards include the Suffrage Science Award (2020) and Blanceflor Boncompagni Ludovisi Young Scientists Award (2003). Her work addresses fundamental problems in mathematical physics, with contributions to stability analysis of nonlinear waves, soliton theory, and spectral methods. Recent articles explore rogue wave dynamics, automorphic Lie algebra classification, and integrable wave models. She is a member of the Maxwell Institute for Mathematical Sciences and actively contributes to sustainable development goals through her research.

Jörn Behrensمشاهده پروفایل

استاد

• Numerical Methods in Geosciences
• Climate Modeling
• Tsunami Simulation
• +۵ مورد دیگر

Prof. Jörn Behrens is a Professor of Numerical Methods in Geosciences at the University of Hamburg's Department of Mathematics. His work focuses on computational geoscience, including adaptive numerical methods, tsunami modeling, and multiscale simulations. He leads the Numerical Methods in Geosciences research group and is affiliated with the Climate, Climatic Change, and Society (CLICCS) cluster of excellence. Education & Positions: Since 2009: Full Professor at University of Hamburg 2012: Visiting Scientist at Isaac Newton Institute, Cambridge 2007–2009: Privatdozent at University of Bremen Extensive experience at Alfred-Wegener-Institut and TU Munich Research Interests: Behrens develops numerical algorithms for geophysical flows, emphasizing adaptive mesh refinement, discontinuous Galerkin methods, and tsunami hazard modeling. His work bridges computational mathematics and geoscience applications, with a focus on environmental challenges like climate modeling and disaster risk assessment. Recent efforts include cloud computing for instant hazard simulations and interdisciplinary projects like the Global Tsunami Model (GTM). Key Publications: Recent work includes bathymetry reconstruction via PDE-constrained optimization, low-rank preconditioning for fluid flow, and tsunami hazard frameworks within EPOS. These reflect his expertise in computational methods and geophysical problem-solving. Grants & Projects: Lead on EU-funded DT-GEO (Digital Twin for Geophysical Extremes) Co-chair of COST Action AGITHAR (Tsunami Hazard Research) Contributions to CLICCS and EPOS infrastructure development Labs & Teams: Leads the Numerical Methods in Geosciences group, collaborating internationally on tsunami modeling, climate systems, and high-performance computing.

Kacarska Marijaمشاهده پروفایل

استادیار

• Electrical Engineering
• Renewable Energy Systems
• Power Systems Analysis
• +۵ مورد دیگر

Kacarska Marija is an Assistant Professor at the Faculty of Electrical Engineering, University Ss Cyril and Methodius in Skopje, Macedonia. She holds a PhD (1998), MSc (1988), and BSc (1978) in Electrical Engineering from the same institution. Her career spans over four decades, including roles as a Teaching Assistant (1978–2001) and Assistant Professor since 2001. Her research focuses on electrical engineering applications, including renewable energy systems, power systems analysis, electromagnetic compatibility, and smart grid technologies. She has contributed to studies on photovoltaic integration, battery management, and electromagnetic field effects on humans. Her work emphasizes energy storage solutions, grounding systems for renewable installations, and wireless energy management platforms. Notable projects include the PV-ESTIA initiative for building energy storage and the development of systems to monitor low-frequency magnetic fields. Her expertise also extends to computational methods for electrical impedance tomography and contingency analysis in power systems. Her publications reflect a multidisciplinary approach, bridging electrical engineering with environmental sustainability and medical applications. She has pioneered VR-based systems for visualizing electromagnetic influences on humans, particularly near high-voltage lines and in cellular telecommunications. Her contributions aim to enhance energy efficiency, grid stability, and public health through advanced engineering solutions.