جست‌وجوی استاد و پژوهشگر

Florian Zillمشاهده پروفایل

پژوهشگر

• Computational Geosciences
• Geomechanics
• Numerical Modeling
• +۴ مورد دیگر

Florian Zill is a Researcher in the Department of Environmental Informatics at the Helmholtz Centre for Environmental Research - UFZ in Leipzig, Germany. He is an active contributor to the OpenGeoSys project, an open-source scientific software for simulating thermo-hydro-mechanical-chemical processes in porous media. His work focuses on developing computational tools and models for environmental and geoscientific applications, with particular emphasis on rock salt mechanics and multi-physics simulations. Dr. Zill's research spans computational geosciences, geomechanics, and numerical modeling, with expertise in thermohydromechanical processes, rock salt behavior, and open-source software development. His work bridges theoretical geoscience with practical computational tools, enabling more accurate simulations of complex environmental systems. He has made significant contributions to understanding fluid flow and mechanical behavior in geological formations, particularly relevant for nuclear waste disposal and subsurface engineering applications. Analysis of Dr. Zill's recent publications (2021-2024) reveals a strong focus on developing and applying computational tools for simulating thermohydromechanical processes in geological formations, particularly rock salt. His work demonstrates expertise in both theoretical modeling and practical software implementation, with significant contributions to the OpenGeoSys platform. The research spans fundamental geomechanics, environmental safety assessment, and software engineering for scientific computing. Dr. Zill is an active member of the OpenGeoSys development team at UFZ, collaborating with researchers across multiple institutions on projects related to environmental modeling, nuclear waste disposal safety assessment, and subsurface engineering. His work contributes to the broader mission of the Helmholtz Centre for Environmental Research in addressing complex environmental challenges through interdisciplinary research and innovative computational approaches.

Ivana Markovaمشاهده پروفایل

استاد

• Psychiatry
• Epistemology of Psychiatry
• Neuropsychiatry
• +۴ مورد دیگر

Ivana Markova is Professor of Psychiatry at Hull York Medical School (University of Hull) and Honorary Consultant in Psychiatry at Humber Teaching NHS Foundation Trust. She holds an MBChB from the University of Glasgow, an MPhil in History and Philosophy of Science from Cambridge, and an MD doctorate focusing on insight in psychiatry. Her dual clinical-research role centers on liaison psychiatry with subspecialties in neuropsychiatry and Huntington's disease. Research Interests: Markova's work bridges two core domains: 1) Theoretical and empirical analysis of insight in mental disorders , including scale development for psychoses; and 2) Epistemology of psychiatry , examining the hybrid neurobiological-semantic constitution of mental symptoms. She argues for methodologies integrating neurobiological factors with unique personal/socio-cultural 'semantic elements'. Publication Trends: Her recent works (2020-2021) demonstrate strong emphasis on historical epistemology in psychiatry, reconceptualizing psychopathology through interdisciplinary frameworks. Early publications (2004-2014) focused on empirical dementia research, particularly awareness trajectories and functional assessment. Awards: Fellow of the Royal College of Psychiatrists (FRCPsych) Academic Leadership: Supervises PhD candidates in topics like 'Awareness in mental disorders' and 'Historical epistemology methods'. Affiliated with the Dementia Research Group and Centre for Psychological Science, driving studies on cognitive heterogeneity in neurodegeneration.

Nick Pohlmanمشاهده پروفایل

استاد

• High Energy Physics
• Granular Flow Dynamics
• Biomass Energy
• +۳ مورد دیگر

Nicholas Pohlman is a Professor in the Department of Mechanical Engineering at Northern Illinois University (NIU), with a career spanning over 15 years. He holds a Ph.D. from Northwestern University, an S.M. from MIT in Aeronautics and Astronautics, and a B.S. from the University of Dayton. As a Presidential Teaching Professor and ACUE Distinguished Teaching Scholar , his student-centered philosophy emphasizes problem-solving and adaptability, teaching courses like Statics, Fluid Mechanics, and Senior Design. He contributes to cutting-edge research in high-energy physics , granular flow dynamics , and biomass energy , collaborating with Fermilab and Argonne National Laboratories. His publications bridge mechanical engineering and physics, with recent work on muon magnetic moments and granular material behavior. Pohlman has received multiple accolades, including Faculty of the Year awards (2009, 2012), the University Honors Program Great Professor Award (2014), and a Credential in Effective College Instruction (2021). He mentors M.S. and undergraduate researchers, guiding projects for Fermilab's mu2e and muon g-2 experiments. Outside academia, he supports community organizations like Boy Scout Troop 37 and Geneva Baseball Association. Research Trends: Pohlman's recent articles focus on three core areas: High-energy particle accelerator design (e.g., Fermilab experiments), Granular flow analysis (conveyor systems, tumbler dynamics), and Sustainable energy systems (biomass gasifiers, energy optimization). These works emphasize experimental validation, interdisciplinary collaboration, and practical engineering solutions for both scientific and industrial challenges. Scientific Awards Presidential Teaching Professor (2022) ACUE Distinguished Teaching Scholar Faculty of the Year (2009, 2012) Credential in Effective College Instruction (2021) Innovation Certificate of Recognition Great Professor Award (2014) Advising Highlights: Pohlman has mentored notable students like Thomas Corbett (Ph.D. candidate at Penn State) and Matthew McCoy (NSF Graduate Research Fellow at Georgia Tech). His research grants include funding from the Environmental Protection Agency – P3 Award , Sustainable Agriculture Grant Program , and collaborations with Argonne National Laboratory.

Tito Andriolloمشاهده پروفایل

استادیار

• Materials Science
• Computational Mechanics
• Fracture Mechanics
• +۴ مورد دیگر

Tito Andriollo is a Tenure Track Assistant Professor at the Department of Mechanical and Production Engineering Mechanics and Materials within College of Engineering at Aarhus University . His work focuses on computational mechanics, fracture analysis, and microstructural modeling of advanced materials. Primary research areas: Materials Science, Computational Mechanics, Fracture Mechanics Recent methodological contributions: Physics-Informed Neural Networks, Digital Volume Correlation Key applications: Additive Manufacturing, Fatigue Analysis, Composite Materials His publications demonstrate expertise in modeling irreversible deformation, strain localization, and vibration damping optimization. Collaborative activities include participation in international conferences like the Risø Symposium and European Mechanics of Materials Conference.

Michael Selzerمشاهده پروفایل

پژوهشگر

• Computational Materials Science
• Phase-Field Modeling
• Research Data Management
• +۷ مورد دیگر

Dr.-Ing. Michael Selzer is a Group Leader in Research Data Management at the Karlsruhe Institute of Technology (KIT), specifically within the Institute of Nanotechnology. He leads the Kadi4Mat project, focusing on FAIR (Findable, Accessible, Interoperable, Reusable) research data infrastructure for materials science. His work bridges computational modeling and digital research workflows. Research Interests: Michael Selzer specializes in computational materials science , with a strong emphasis on phase-field modeling for simulating microstructure evolution, fracture mechanics, and multiphase systems. His research extends to materials informatics , digital workflows , and research data management , particularly in the context of battery materials, porous media, and solid-state systems. He integrates machine learning and data science to analyze and optimize materials properties. Publication Trends: His recent publications (2023–2025) highlight a growing focus on FAIR data infrastructure (e.g., Kadi4Mat, KadiStudio), large language models in battery science (LISA), low-code simulation platforms (MUSICODE), and reproducibility in bioprinting . These reflect a strategic shift toward digitalization and automation in materials research, while maintaining a strong foundation in physics-based modeling. Scientific Contributions: Developed and advanced phase-field models for grain growth, crack propagation, and interfacial phenomena. Contributed to the development of Kadi4Mat, a research data infrastructure for materials science. Integrated machine learning and AI into materials characterization and battery research. Published extensively in journals such as Acta Materialia , Computational Materials Science , and Scientific Data . Advising and Grants: While no direct students are listed, his leadership role in Kadi4Mat suggests mentorship and team supervision. He has likely secured funding for digital infrastructure and computational materials projects, evidenced by sustained publication output and collaborative work with major institutions. His research is highly collaborative, involving teams across KIT and international partners. Labs and Teams: He leads the Research Data Management group under the Kadi4Mat initiative at KIT. This team focuses on developing digital tools for materials research, including electronic lab notebooks (KadiWeb), workflow automation (KadiStudio), and ontology-based data integration. The group operates at the intersection of computational science, data engineering, and materials discovery.

• Didactics of Mathematics
• Numerical Analysis
• Partial Differential Equations
• +۲ مورد دیگر

JORGE ALBELLA MARTINEZ is an Assistant Professor at the University of Santiago de Compostela, affiliated with the Applied Didactics Department in the Faculty of Education Sciences. His research focuses on numerical methods for wave propagation, particularly in elastodynamics, and he holds a doctoral degree from the same university (2020). Education: PhD in Applied Mathematics from the University of Santiago de Compostela (2020), thesis on 'Advanced numerical methods for wave propagation problems'. Research Interests: Specializes in numerical analysis of partial differential equations, mechanics of deformable solids, and the application of finite element methods to solve complex problems in elastodynamics and wave propagation. His work bridges mathematical theory with computational techniques. Publications: Authored influential papers in Mathematics of Computation and Journal of Scientific Computing , focusing on innovative numerical techniques for solving 2D elastodynamics equations. Grants/Advising: No explicit grants or student advisement listed. Collaborates with researchers like Sébastien Imperiale and Patrick Joly.

Herbert De Gersemمشاهده پروفایل

استاد

• Electromagnetic Field Theory
• Computational Electromagnetics
• Particle Accelerator Physics and Technology
• +۶ مورد دیگر

Prof. Herbert De Gersem is a Full Professor at the Technische Universität Darmstadt, leading the Computational Electromagnetics Laboratory within the Department of Electrical Engineering and Information Technology. Previously, he held a professorship at KU Leuven (Belgium) from 2006 to 2014, focusing on wave propagation and signal processing. His academic journey began as a research assistant at TU Darmstadt and KU Leuven from 1995 to 2006, specializing in computational electromagnetics and electromagnetic field theory. His research spans electromagnetics, computational electromagnetics, and particle accelerator physics, with applications in electric machines, high-voltage technology, and high-frequency components. Key projects include simulations for muon colliders, rotor optimization in axial flux machines, and thermal analysis of HVDC cable joints. He collaborates on advanced topics like foil winding homogenization and magneto-thermal quench simulations for superconducting magnets. Prof. De Gersem’s publications emphasize innovative numerical methods, such as adjoint sensitivity analysis and data-driven modeling, alongside experimental validation. His work bridges computational theory with practical engineering challenges, addressing energy efficiency, thermal management, and high-performance accelerator design. Despite no listed scientific awards, his extensive contributions to the field are evident through his prolific research output and international conference participation. His academic advising and mentorship are integral to his role, though specific student names are not documented here. Ongoing projects involve interdisciplinary collaborations, including hybrid modeling approaches for engineering systems and optimization strategies for electric machine design under thermal constraints.

Maria Lucia Sampoliمشاهده پروفایل

دانشیار

• Numerical Analysis
• Computer Aided Geometric Design
• Isogeometric Analysis
• +۷ مورد دیگر

Maria Lucia Sampoli is an Associate Professor in the Department of Information Engineering and Mathematics at the University of Siena, Italy. She holds a PhD in Computational Mathematics and Operational Research from the University of Milan and has been a faculty member at the University of Siena since 1999, advancing from Research Assistant to tenured Assistant Professor in 2002 and to Associate Professor in 2010. Her academic journey includes a postdoctoral fellowship at the Technical University of Darmstadt and a CNR Senior Fellowship. PhD in Computational Mathematics and Operational Research, University of Milan (1998) Laurea in Mathematics (Honors), University of Florence (1994) Her research focuses on Numerical Analysis , particularly in Computer Aided Geometric Design (CAGD) , Isogeometric Analysis (IGA) , Pythagorean Hodograph (PH) curves and surfaces , Boundary Element Methods , and constrained interpolation and approximation . Recently, she has explored mathematical aspects of deep learning , especially the theoretical foundations of Graph Neural Networks. Her work bridges pure mathematical theory with engineering and computational applications. The most recent publications highlight a consistent trend in geometric modeling and numerical methods, with increasing interdisciplinary reach into machine learning. Topics span from high-precision curve and surface design to advanced numerical techniques for PDEs and the mathematical analysis of neural networks. She has participated in and organized numerous international conferences such as SIAM CSE, IGA, and SMART, and has been involved in multiple research projects, some as coordinator. While specific scientific awards are not listed, her invited talks at major conferences reflect recognition in her field. Maria Lucia Sampoli supervises graduate research and teaches courses including Numerical Calculation and Numerical Modeling . She is actively involved in academic service, including conference organization and research project leadership. She maintains an open-door policy for student consultations and is accessible via email for appointments. She is affiliated with the SAILab (Siena Artificial Intelligence Lab), indicating institutional engagement with AI and computational intelligence research.

• Acoustic waves
• Advanced numerical methods
• Convolution integrals
• +۷ مورد دیگر

Silvia Falletta is an Associate Professor at the Department of Mathematical Sciences 'GL Lagrange' (DISMA), Politecnico di Torino. She teaches courses including Numerical Methods for Differential Equations and Finite Element Modelling across disciplines like Chemical Engineering and Aerospace Engineering. Her research focuses on advanced numerical methods for wave propagation problems, particularly in acoustics, elasticity, and seismology. Research Interests: Acoustic waves, Elasticity, Integral equations, Numerical Analysis, Convolution Quadrature, Wavelet techniques. Teaching Roles: Course Lecturer for Finite Element Modelling (2019–2025), Numerical Calculus collaborator, and contributor to PhD programs in Mathematical Sciences. Publications: Specializes in time-domain boundary integral equations, BEM-FEM coupling, and non-reflecting boundary conditions. Recent work includes virtual element methods for wave propagation and wavelet-based matrix sparsification. Students: Supervises PhD candidates Davide Collato and Matteo Ferrari, focusing on non-symmetric coupling of virtual/boundary elements and unbounded domain problems. Contact: Email: silvia.falletta@polito.it ; Phone: +39 0110907506.

Alexander Freiszlingerمشاهده پروفایل

پژوهشگر

• Numerics of PDEs
• Adaptive Finite Element Methods (FEM)
• Boundary Element Methods (BEM)
• +۳ مورد دیگر

Alexander Freiszlinger is a PhD student and project assistant at the Institute of Analysis and Scientific Computing (E 101) at TU Wien, supervised by Prof. Dirk Praetorius. His research focuses on numerics of parametric partial differential equations (PDEs), adaptive finite element methods (FEM), and boundary element methods (BEM). He holds a Master of Science (2023) and Bachelor of Science (2020) in Technical Mathematics from TU Wien, both completed at the same institution. He presented a talk titled "Convergence of adaptive BEM driven by functional a posteriori error estimates" at the PDE Afternoon in Vienna on December 4, 2024. His academic work integrates advanced numerical techniques for solving complex PDE systems. No teaching activities are currently listed, and no formal awards have been documented. He is based at the Freihaus building, room DA 04 H 02, Wiedner Hauptstraße 8-10, 1040 Vienna, Austria.

Gregor Gantnerمشاهده پروفایل

پژوهشگر

• Numerical Analysis
• Computational Mathematics
• Partial Differential Equations
• +۴ مورد دیگر

Gregor Gantner is a researcher at TU Wien's Department of Numerical Analysis and Partial Differential Equations, part of the Faculty of Mathematics and Geoinformation. He holds a Dipl.-Ing. and Dr.techn. in technical mathematics. His primary research focuses on adaptive numerical methods for partial differential equations (PDEs), particularly boundary element methods (BEM), isogeometric analysis (IGA), and finite element methods (FEM). He investigates topics such as a posteriori error estimation, optimal computational complexity, and convergence analysis of adaptive algorithms. Key research themes include: Design and implementation of adaptive algorithms for BEM and FEM systems Integration of isogeometric analysis with hierarchical B-splines Development of optimal convergence frameworks for nonlinear PDEs Analysis of computational costs and efficiency in adaptive methods Notable contributions include: Establishing rate optimality of adaptive FEM with respect to computational costs Stable MATLAB implementations of adaptive IGABEM techniques Advancements in (h-h/2)-type error estimators for FEM He has advised master's candidates Juliana Kainz (2019) and Stefan Schimanko (2016) on isogeometric BEM applications. His work bridges theoretical foundations with practical implementation, emphasizing algorithmic efficiency and mathematical rigor.

• Nanotechnology
• Materials Science
• Inorganic Materials
• +۴ مورد دیگر

Nobuyasu Adachi is Professor in the Department of Life and Applied Chemistry at Nagoya Institute of Technology, leading the Advanced Ceramics Research Laboratory. His work bridges fundamental materials science with industrial applications in magneto-optics and electromagnetic devices, with continuous research output since the 1990s. He earned his Master of Science and Doctor of Science from Tohoku University (completed 1993), following undergraduate studies at Tokyo University of Science. His postdoctoral research included positions at Tohoku University (1993) and the Swedish Royal Institute of Technology (1999). Adachi's research centers on ferrite-based materials, with expertise in thin-film synthesis (particularly metal organic decomposition), magnetic property characterization, and ceramic microstructure engineering. Current projects focus on porous ferrites for electromagnetic shielding, magneto-optical garnet films for high-frequency sensors, and photonics crystals. His work demonstrates consistent evolution from fundamental magnetic studies toward applied electromagnetic solutions. Recent publications (2014-2025) reveal three dominant themes: (1) ferrite synthesis optimization for GHz-frequency applications, (2) magneto-optical garnet film development for magnetic field imaging, and (3) porous ceramic engineering for dual-function materials. Key innovations include controlled resonance linewidth in garnet films and hollow ferrite particle fabrication using template methods. APSMR Contribution Award (2018) for Synthesis and Characterization of Magnetic Garnet Film Wakabayashi Paper Award (2018) for research on flexible aluminum titanate ceramics He has secured significant funding including MEXT Grants-in-Aid for rare-earth thin film magnets (2004-2006) and magneto-optical sensor development (2005-2007), plus industry collaborations with JST and MIC on GHz-band absorbers (2015-2016). As an active society member, he serves on Japan Ceramic Society committees and organizes academic symposia while mentoring through public lectures at high schools and industry workshops. The Advanced Ceramics Research Laboratory under his direction focuses on green technology applications, particularly electromagnetic materials for sustainable electronics and industrial sensors, maintaining strong ties with regional ceramic industries in Gifu Prefecture.

• Computational Materials Science
• Microstructure Evolution
• Phase-Field Modeling
• +۵ مورد دیگر

Katsuyo Thornton is the L.H. and F.E. Van Vlack Professor in the Department of Materials Science and Engineering at the University of Michigan's College of Engineering. She has held this named professorship since 2018, following promotions from Associate Professor (2010-2015) and Assistant Professor (2004-2010) at the same institution. Prior to joining Michigan, she was a Research Assistant Professor at Northwestern University (2001-2004) and completed her postdoctoral work there (1997-2001), with additional experience as a Visiting Lecturer and Scientist at MIT. Her educational background includes a B.S. with Honors in Physics from Iowa State University (1991), followed by an M.S. (1993) and Ph.D. (1997) in Astronomy and Astrophysics from The University of Chicago. This unique interdisciplinary foundation has informed her distinctive approach to materials science problems. Dr. Thornton's research focuses on computational and theoretical investigations of microstructure and nanostructure evolution during materials processing and operation. Her work employs advanced phase-field modeling techniques to study coarsening in elastically stressed solids, three-dimensional topologically complex systems, electrochemical systems, and self-assembly phenomena during semiconductor heteroepitaxy. Her research group has developed sophisticated computational frameworks that bridge atomistic to continuum scales, enabling predictive modeling of complex materials phenomena. Analysis of her recent publications reveals a strong trend toward energy applications, particularly in solid oxide fuel cells and battery technologies. Her work increasingly integrates experimental data with computational modeling, as evidenced by publications combining phase-field simulations with in situ tomography and other advanced characterization techniques. The research spans fundamental materials science questions to applied engineering challenges in energy conversion and storage. Fellow of ASM, 2018 TMS Brimacombe Medal, 2018 Eschbach Fellow, Northwestern, 2018 Ted Kennedy Family Faculty Team Excellence Award, 2016 NSF CAREER Award, 2008 TMS Early Career Faculty Fellow Award, 2008 Dr. Thornton has secured substantial research funding from NSF, DOE, and AFOSR for projects including the Center for Radiative Shock Hydrodynamics (CRASH), computational materials research, and solid oxide fuel cell development. Her group has developed the PRISMS-PF framework, a general matrix-free finite element method for phase-field modeling. She also leads educational initiatives in computational materials science, including the Summer School for Integrated Computational Materials Education. The Thornton Research Group operates within the Michigan Materials Research Institute and collaborates extensively with researchers at Northwestern University, MIT, and other institutions. Their work combines advanced computational methods with experimental validation, creating a powerful integrated approach to materials discovery and design. Current efforts focus on applying these methodologies to next-generation energy storage and conversion technologies.

Sébastien Leclaireمشاهده پروفایل

دانشیار

• Fluid mechanics
• Multiphase flows
• Computational Fluid Dynamics
• +۵ مورد دیگر

Sébastien Leclaire is an Associate Professor in the Department of Mechanical Engineering at Polytechnique Montréal, a leading engineering institution in Canada. With over a decade of experience in numerical fluid dynamics, he specializes in multiphase flow modeling using Lattice Boltzmann Methods (LBM), an emerging research niche. His work spans computational fluid dynamics, rarefied gas flows, porous media applications, and multiphase flow simulations. His educational background includes a B.Sc. in Pure and Applied Mathematics from the University of Montreal, an M.Sc. in Applied Mathematics from the University of Montreal, an M.Eng. in Mechanical Engineering from Polytechnique Montréal, and a Ph.D. in Mechanical Engineering from Polytechnique Montréal. Leclaire has built a multidisciplinary research profile through collaborations at institutions worldwide, including applied mathematics at the University of Montreal, mechanical engineering at Polytechnique Montréal, civil engineering at ENS Cachan in France, computer science at the University of Geneva in Switzerland, and chemical engineering at Polytechnique Montréal. Leclaire's research focuses on improving LBM modeling, extending its application to practical cases, and optimizing simulation codes for high-performance computing. His work addresses engineering challenges in fluid mechanics, particularly in multiphase flows, computational fluid dynamics, Lattice Boltzmann Method, and verification and validation. He has published over 65 papers, with recent work (2021-2025) demonstrating continued innovation in rarefied gas flows, porous media applications, and computational efficiency improvements. His publications show a consistent trajectory toward increasingly complex flow scenarios and computational optimizations. As a dedicated educator and researcher, Leclaire actively supervises graduate students and is recruiting for new research projects. He is affiliated with the Industrial Flow Processes Research Unit (URPEI) and teaches courses including MEC8270 (Finite Elements in Thermofluids), MEC6215 (Numerical Methods in Engineering), and MEC2200 (Fluid Dynamics).

Lars Mandrupمشاهده پروفایل

دانشیار

• Biomedical Engineering
• Signal Processing
• Machine Learning
• +۵ مورد دیگر

Lars Mandrup is an Associate Professor in the Department of Electrical and Computer Engineering at Aarhus University, specializing in Signal Processing and Machine Learning. He serves as the Unions Representative for DM and is a member of LSU and LAMU. His primary responsibilities include educating Diploma and Master Engineers in Biomedical Engineering. Mandrup's research expertise lies in Physics, Mathematics, and Biophysics, with a strong focus on Biomedical Engineering. He applies Computational Fluid Dynamics (CFD) to Magnetic Resonance data for cardiovascular modeling, including blood flow analysis and mitral valve mechanics. Additionally, he is a key contributor to Electromagnetic Compatibility (EMC) research, developing foundational educational materials and advancing EMC testing standards and methods. His publication record shows a clear interdisciplinary trajectory, merging engineering with medical applications. Key themes include CFD-based cardiovascular simulations and EMC education. The biomedical work leverages MRI data to model complex physiological processes, while the EMC contributions span theoretical principles to practical testing standards, reflecting a commitment to both academic and industrial relevance. No scientific awards were mentioned in the provided information. Mandrup actively mentors students in Biomedical Engineering programs and serves as a PhD examiner. He is a member of the EMC group within the TUR Network for Electronics and Information Technology, which drives curriculum development in EMC education across Danish engineering institutions. He is affiliated with the EMC group (EMC-gruppen), dedicated to advancing EMC education and professional development. This group collaborates within the TUR Network to enhance teaching materials and methodologies for EMC courses.