جستجوی استاد راهنمای دانشگاهی

Kelly Stephaniمشاهده پروفایل

دانشیار

• Hypersonics
• High-temperature aerothermodynamics
• Surface chemistry
• +۵ مورد دیگر

Kelly Stephani is an Associate Professor in the Department of Mechanical Science and Engineering at the University of Illinois Urbana-Champaign (UIUC), and the Associate Director of the Center for Hypersonics and Entry Systems Studies (CHESS). She holds additional roles such as Kritzer Faculty Fellow and Faculty Affiliate in Aerospace Engineering. Her research focuses on hypersonics, high-temperature aerothermodynamics, and surface chemistry interactions with plasma. Stephani has contributed to advancements in kinetic methods for non-equilibrium flows and the development of oxidation models for carbon-based materials. Education: Ph.D. Aerospace Engineering, University of Texas at Austin (2012) M.S. Aerospace Engineering, University of Texas at Austin (2006) B.S. Aerospace Engineering and Mechanics, University of Minnesota (2005) Research Interests: Gas-surface interactions in porous materials Plasma-surface dynamics Thermal protection systems for aerospace vehicles Computational modeling of hypersonic flows Her work bridges experimental and computational approaches, with notable contributions to understanding oxidation mechanisms in carbon-fiber composites and the design of light-weight thermal protection systems. Awards and Honors: PECASE Award (2019) AFOSR YIP Award (2017) NASA Early Career Faculty Award (2015) Recipient of multiple fellowships including AFOSR Summer Faculty Fellow (2015) Teaching and Service: Teaches courses in gas dynamics and fluid mechanics (e.g., AE 312, ME 510). Serves as Co-director of the University Consortium for Applied Hypersonics and leads service roles in professional societies like AIAA. Key Projects: Leads research on hypersonic aerothermodynamics, including modeling surface reactions in carbon-based materials and advancing DSMC techniques for plasma interactions.

David Kellermannمشاهده پروفایل

مدرس ارشد

• Continuum Mechanics
• Computational Mechanics
• Advanced Composite Materials
• +۷ مورد دیگر

David Kellermann is a Senior Lecturer in the School of Mechanical and Manufacturing Engineering at the University of New South Wales (UNSW). His research focuses on advanced composite materials, continuum mechanics, and nonlinear finite element analysis, with particular emphasis on orthotropic and hyperelastic material modeling. He has contributed significantly to the understanding of free-edge effects in laminates and fiber kinematics in biological tissues. Dr. Kellermann teaches courses such as ENGG1300 (Engineering Mechanics), ENGG2400 (Mechanics of Solids), and MECH4320 (Engineering Mechanics 3). His educational innovations, including remote learning strategies, earned him the 2018 VCATE Vice-Chancellor's Award for Teaching Excellence. His research interests span computational mechanics, buckling analysis, and material characterization. Notable contributions include developing fourth-order tensor methods for anisotropic materials and finite element frameworks for free-edge singularity analysis. He has published extensively in journals like Mathematics and Mechanics of Solids and Composites Part A . Dr. Kellermann has collaborated on projects involving micropolar modeling of composite interfaces and hyperelastic constitutive laws for biological tissues. His work bridges theory and application, addressing challenges in structural stability and material behavior under extreme conditions.

• Partial Differential Equations
• Calculus of Variations
• Geometric Analysis
• +۳ مورد دیگر

László Székelyhidi is a Full Professor in the Faculty of Mathematics and Computer Science at Leipzig University, where he has been a central figure since October 2011. He is also recognized as an Honorary Professor and serves as an External Scientific Member at the Max Planck Institute for Mathematics in the Sciences (MPI Leipzig), highlighting his continued influence in mathematical research. His primary research lies at the intersection of geometric analysis and mathematical fluid mechanics. He specializes in partial differential equations, calculus of variations, and nonlinear problems arising in continuum mechanics. His work often bridges deep theoretical mathematics with physical applications, particularly in understanding fluid flow and geometric structures. Prof. Székelyhidi holds influential editorial positions across major mathematical journals, including: Editor in Chief, Calculus of Variations and Partial Differential Equations Associate Editor, Archive for Rational Mechanics and Analysis Associate Editor, Journal of Mathematical Fluid Mechanics Associate Editor, Journal of Evolution Equations Associate Editor, Acta Mathematica Hungarica His career includes prestigious appointments such as Bonn Junior Fellow at the University of Bonn (2007–2011) and Heinz Hopf Lecturer at ETH Zürich (2005–2007), establishing him early as a leading figure in mathematical analysis. These roles, combined with his long-standing professorship and MPI affiliation, reflect a sustained and impactful research trajectory. He advises no students listed in the provided data, and there is no mention of specific grants or funded projects. However, his editorial leadership and external membership at MPI Leipzig suggest active participation in the broader mathematical community and likely involvement in collaborative research initiatives.

Cai Xia Yangمشاهده پروفایل

دانشیار

• Nonlinear Dynamics
• Data Analysis
• Stability Analysis
• +۶ مورد دیگر

Cai Xia Yang is an Associate Professor in the Department of Mechanical Engineering at the University of North Dakota since August 2020, previously holding the same title there since 2014 and an Assistant Professor role from 2013-2020. Her research focuses on Nonlinear Dynamics , Data Analysis , Stability Analysis , and Fault Detection using vibration signals, with applications in rotating machinery, bipedal robotics, and posture stability. She has developed low-cost diagnostic systems for vibration detection and balance measurement. Ph.D. , Mechanical Engineering, University of Manitoba M.S. , Mechanical Engineering, Tianjin Institute of Textile Science and Technology B.S. , Mechanical Engineering, Tianjin Institute of Textile Science and Technology Her work integrates nonlinear Lyapunov exponent analysis with KNN classification for fault detection in mechanical systems, nonlocal elasticity theory for microsystem vibrations, and computer vision for rotating machine balancing. Publications span journals like Actuators , Nonlinear Dynamics , and conferences including ASME IMECE and IEEE EIT. She has advised numerous graduate and undergraduate students on projects related to machinery fault classification, wind turbine design, and biomedical signal processing. Recent collaborations include low-cost vital signs monitors via computer vision and vibration analysis.

Jeremy N. Bassisمشاهده پروفایل

استاد

• Ice sheet dynamics
• Glacier dynamics
• Fracture mechanics
• +۵ مورد دیگر

Jeremy N. Bassis is a Professor in the Department of Climate and Space Sciences and Engineering (CLaSP) at the University of Michigan's College of Engineering. His research integrates geophysics, fracture mechanics, and climate science to investigate ice sheet dynamics, glacier calving processes, and sea level rise implications. He leads a multidisciplinary research group combining field observations, satellite remote sensing, and numerical modeling to address critical questions in cryospheric science. Education: Ph.D., Scripps Institution of Oceanography, La Jolla, California B.Sc. Physics, Pennsylvania State University, University Park, Pennsylvania Bassis's research centers on the mechanics of iceberg calving—a process responsible for up to two-thirds of ice discharge into the ocean—which introduces rapid timescales into ice sheet response to climate change not captured by current models. His work spans fundamental glaciological processes, planetary ice shell dynamics, and societal impacts of sea level rise, with recent emphasis on community adaptation in coastal regions including Detroit. He employs field instrumentation (GPS, seismometers), satellite monitoring, and theoretical frameworks to model fracture propagation, ice-ocean interactions, and calving mechanisms. Analysis of his 15 most recent publications reveals strong focus areas: marine ice cliff instability, fracture mechanics in ice sheets, calving parameterization, and societal adaptation to sea level rise. His work bridges theoretical glaciology with practical climate solutions, featuring high-impact studies in Science , Nature , and Nature Communications that advance understanding of ice sheet vulnerability. Scientific Awards: Presidential Early Career Award for Scientists and Engineers (PECASE) 2016 Henry Russel Award 2015 Career Award 2011 Professor Bassis actively mentors students in cryospheric research and has served as Associate Editor for the Journal of Geophysical Research – Earth Surfaces (2012-2015) and IPCC Cryosphere Contributing Author (2017-2018). His research is supported by major grants from NSF and NASA, focusing on ice sheet modeling, calving processes, and community resilience to sea level rise. He collaborates extensively with social scientists, engineers, and community organizations to translate glaciological research into actionable climate adaptation strategies. His research group employs a systems-based approach to study ice sheet dynamics, utilizing advanced numerical models and field data to investigate fracture networks, ice-ocean interactions, and calving mechanics. Recent work emphasizes interdisciplinary connections between physical glaciology and societal impacts, particularly in urban coastal environments facing sea level rise threats.

• Mathematical modeling
• Biomedical engineering
• Cerebral blood flow
• +۴ مورد دیگر

Dr. Irina Sidorenko is a Researcher in the Department of Mathematics at the Technical University of Munich, working within the School of Computation, Information and Technology. She is affiliated with the Chair of Analysis and Modelling under Prof. Zimmer and is an active member of the Analysis and Mathematical Biology research group. Her work bridges advanced mathematical techniques with critical biomedical applications, particularly in neonatal physiology. Dr. Sidorenko's research focuses on mathematical modeling of physiological systems, with particular emphasis on cerebral blood flow and oxygen transport mechanisms in the developing brain. Her work combines differential equations, inverse problems, and numerical analysis to create sophisticated models that capture complex biological processes. She has made significant contributions to understanding hemodynamics in preterm infants, developing models that account for factors like hematocrit levels, blood gases, and capillary network structures. Her research has evolved from plasma physics in her early career to biomedical applications, demonstrating remarkable interdisciplinary versatility. Analysis of her recent publications reveals a strong focus on neonatal cerebral physiology, with consistent output in high-impact journals spanning mathematics, engineering, and medical disciplines. Her work shows increasing sophistication in modeling approaches, moving from basic continuum models to more complex spatially-averaged network models that incorporate multiple physiological factors. The research demonstrates a clear translational trajectory, with mathematical insights increasingly directed toward solving specific clinical challenges in neonatal care. Dr. Sidorenko maintains active collaborations with medical researchers, particularly in neonatology, creating a productive interdisciplinary research environment. Her work on cerebral blood flow modeling has direct clinical relevance, potentially informing diagnostic and therapeutic approaches for preterm infants at risk of intraventricular hemorrhage. The Analysis and Mathematical Biology group provides a rich research environment where mathematical theory meets biomedical application. Dr. Sidorenko's work exemplifies how sophisticated mathematical modeling can address complex physiological questions, creating quantitative tools that have the potential to improve clinical outcomes for vulnerable patient populations.

Fausto Segalaمشاهده پروفایل

استاد

• Fracture Mechanics
• Stress Analysis
• Crack Propagation
• +۳ مورد دیگر

Fausto Segala is a Full Professor in the Department of Mathematics and Computer Science at the University of Ferrara, Italy. His office is located in the Physics Department, Block C #O22, with contact information including email fausto.segala@unife.it and office phone 0532 974650. He maintains active research and teaching responsibilities, with office hours available by appointment. Professor Segala specializes in fracture mechanics and structural integrity analysis, with particular expertise in stress intensity factor calculations for various crack geometries. His research bridges applied mathematics and mechanical engineering, developing analytical methods to evaluate crack propagation in materials. He has made significant contributions to understanding three-dimensional crack behavior, elliptical defects, and weld integrity through precise mathematical modeling. Segala's publication record demonstrates a consistent evolution from basic crack analysis to sophisticated three-dimensional models. His work frequently addresses real-world engineering challenges, particularly in weld defect analysis and fatigue crack propagation. The majority of his publications are co-authored with Paolo Livieri, indicating a long-standing research collaboration focused on advancing fracture mechanics methodologies. His research output shows a methodical progression in complexity, moving from two-dimensional analyses to comprehensive three-dimensional models that better represent real material failures. The publications reveal increasing sophistication in handling complex crack geometries and loading conditions, with particular attention to practical applications in structural engineering and materials science.

Mauricio Pongaمشاهده پروفایل

دانشیار

• Mechanics of Materials
• Computational Modeling
• Multiscale Modeling
• +۴ مورد دیگر

Mauricio Ponga is an Associate Professor at the Department of Mechanical Engineering, University of British Columbia (UBC), Faculty of Applied Science. His research focuses on computational mechanics, multiscale modeling, and material failure analysis. He holds a Ph.D. and M.Sc. from the University of Seville, a B.S. from the University of La Plata, and completed postdoctoral work at Caltech. Education: B.S. (University of La Plata), M.Sc. (University of Seville), Ph.D. (University of Seville), Postdoctoral Fellowship (Caltech) Research Interests Mechanics of materials under extreme conditions Multiscale modeling (atomic to continuum) Thermal and electronic transport in materials Material failure mechanisms (spallation, twinning) Industrial applications (batteries, superconductors) Recent Publications highlight his work on high-entropy alloys, polymer brushes, 2D materials, and novel simulation methods like local two-temperature molecular dynamics (l2T-MD) and accelerated mesodynamics (aMD). Projects include collaborations with TRIUMF, NSERC, and FP Innovations. Labs & Collaborations Principal Investigator of the Modeling and Simulation Research Group at UBC Collaborations with S2SES (Coanda-effect screens), DND (gradient nano-grained alloys), and Caltech (postdoctoral work)

John R. Dutcherمشاهده پروفایل

استاد

• Nanoscience
• Soft Matter Physics
• Biophysics
• +۴ مورد دیگر

John R. Dutcher is a Professor and Research Chair in Novel Sustainable Nanomaterials at the University of Guelph's Department of Physics. His work bridges soft matter physics, biophysics, and sustainable nanotechnology through experimental studies of polymers, biopolymers, and bacterial systems at surfaces and interfaces. PhD in Condensed Matter Physics (Simon Fraser University, 1989) NSERC Postdoctoral Fellow (University of Arizona, 1989-1990) Director of University of Guelph’s B.Sc. Nanoscience program Research focuses on: Phytoglycogen nanoparticles from sweet corn for biomedical/personal care applications Machine learning analysis of polymer degradation in cross-linked pipes Bacterial motility and biofilm formation via optical microscopy Hydration forces and mechanical properties of nanomaterials His lab employs state-of-the-art equipment including AFMs, SPRi, and rheometers, with industrial partnerships like HeatLink. Recent publications analyze β-VAE applications in IR spectroscopy, acid hydrolysis effects on nanomaterials, and bacterial colony dynamics. Scientific honors include: Tier 1 Canada Research Chair in Soft Matter and Biological Physics (2006) Fellow, American Physical Society (2007) University of Guelph Innovation of the Year (2017) He has co-founded spin-off company Mirexus Biotechnologies and mentored over 50 graduate/undergraduate researchers, with alumni holding faculty positions at Waterloo, McMaster, and Lakehead University. Lab facilities include: Custom self-nulling ellipsometer TA Instruments DHR-3 rheometer Brookhaven BI200-SM light scattering system Thermo/Nicolet Continuum infrared microscope Wyatt SEC-MALS system Advanced microbiology/Biophysics equipment

Francesco V. Pepeمشاهده پروفایل

دانشیار

• Quantum Imaging
• Quantum Information
• Quantum Optics
• +۷ مورد دیگر

Francesco V. Pepe is an Associate Professor in the Department of Physics at the University of Bari Aldo Moro, Italy, where he is affiliated with the Dipartimento Interateneo di Fisica. He leads the Quantum Optical Technologies Laboratory (QuOT Lab) and is the Principal Investigator of the INFN project PICS (Plenoptic Imaging with Correlations), focused on advancing correlation plenoptic microscopy. His research spans quantum imaging, quantum information, and quantum optics, with a strong emphasis on correlation-based imaging techniques and their applications in high-resolution 3D microscopy. PhD in Physics (specific institution and year not specified in text) His research interests lie at the intersection of quantum optics and imaging science, focusing on quantum imaging , correlation-based microscopy , plenoptic imaging , light-field technologies , and quantum information processing . He explores the use of intensity correlations in light to overcome classical limitations in resolution, depth of field, and imaging speed. His work also extends to quantum simulation of many-body systems (e.g., Schwinger model), bound states in the continuum , and light-matter interactions in waveguide QED platforms. The recent articles (2024–2025) reveal a strong trend toward quantum-inspired imaging techniques , particularly correlation plenoptic and hyperspectral imaging, with applications in turbulence-robust and real-time volumetric imaging. There is also a significant focus on quantum simulation of gauge theories using quantum computing platforms, dimensional reduction in field theories , and non-Markovian dynamics in quantum systems. The consistent use of correlation measurements, quantum error mitigation, and GPU-accelerated processing highlights a multidisciplinary approach combining theory, computation, and experimental design. Francesco V. Pepe has supervised Master’s students in Physics and is actively involved in collaborative research projects. While no formal scientific awards are listed in the provided text, his leadership in the INFN PICS project and extensive publication record underscore his prominence in the field. He has also contributed to advancements in quantum decay dynamics , spontaneous emission in dispersive media , and nonexponential decay phenomena , often in collaboration with leading researchers in quantum optics and condensed matter physics. He is associated with the QuOT Lab, which focuses on developing quantum optical technologies for imaging and sensing. The lab engages in both theoretical modeling and experimental implementation, particularly in correlation imaging, plenoptic microscopy, and quantum simulation. The team collaborates widely across Italy and internationally, contributing to projects in quantum 3D imaging, remote sensing, and Earth observation.

Mikael Andersen Langthjemمشاهده پروفایل

دانشیار

• Applied Mathematics
• Fluid Dynamics
• Structural Mechanics
• +۳ مورد دیگر

Mikael Andersen Langthjem is an Associate Professor at the Department of Mechanical and Production Engineering Mechanics and Materials, Aarhus University. His research focuses on fluid-structure interactions, wave propagation, and stability analysis in mechanical systems. Academic Rank: Associate Professor Department: Mechanical and Production Engineering Mechanics and Materials Email: ml@mpe.au.dk Langthjem's work spans applied mathematics, computational mechanics, and experimental validation, with recent publications on vortex dynamics, pipeline buckling, and rotating fluid systems. His research employs matched asymptotic expansions and multiple scales analysis for complex mechanical problems. He has contributed to studies on fluttering flags, ring tone mechanisms, and transient responses in rotating machinery with fluid balancers.

• Numerical Methods for Continuum Physical Modelling
• Scientific Software Development
• Computational Geometry
• +۱ مورد دیگر

Alan Correa is a PhD candidate and Scientific Researcher at the Chair of Methods for Model-based Development in Computational Engineering, RWTH Aachen University, Germany. His research advances forward solvers for thin film free surface flows over complex geometry through numerical methods, computational geometry, and automatic differentiation, with strong advocacy for open source software principles. Education Master of Science (with distinction), Computer Aided Conception and Production in Mechanical Engineering, RWTH Aachen University, Germany (2023) Bachelor of Technology, Mechanical Engineering, Sardar Patel College of Engineering, University of Mumbai, India (2017) Research Interests Alan's work spans Numerical Methods for Continuum Physical Modelling , Scientific Software Development , Computational Geometry , and Scientific Machine Learning . His PhD project integrates depth-integrated Shallow Water Equations (Surface PDEs) with computational geometry and automatic differentiation to model complex fluid dynamics. He has developed computational material models for visco-elastic hydrogels, automated 3D mesh generation systems, and state estimation software for autonomous vehicles. Publication Trends His 2024 publications demonstrate a cohesive focus on computational reproducibility through Julia-based workflows and FAIR research practices. Both papers address critical challenges in sustainable research software engineering, emphasizing reusable datasets, containerized compute environments, and transparent simulation pipelines within computational engineering and earth sciences contexts. Scientific Awards Dean's List, RWTH Aachen University (2022) Best of Class Awards, RWTH Aachen International Academy (2021) J.N. Tata Scholarship for Higher Education of Indians (2019) Best Outgoing Student Award, Sardar Patel College of Engineering (2017) Advising and Funding As a PhD candidate, Alan does not supervise students. His research is funded through his Scientific Researcher position at RWTH Aachen and scholarship support including the prestigious J.N. Tata endowment. Professional experience includes structural analysis internships at Airbus and graduate research at RWTH's Material Applications Institute. Research Environment Alan operates within RWTH Aachen's Modeling & Simulation Sciences profile area, collaborating across engineering, mathematics, and computer science disciplines. The Chair develops performant simulation methods and sustainable software implementations for model-based decision support systems, with active participation in international conferences like JuliaCon and EGU General Assembly.

Payman Jalaliمشاهده پروفایل

دانشیار

• Fluid Dynamics
• Granular Materials
• Computational Fluid Dynamics (CFD)
• +۷ مورد دیگر

Payman Jalali is an Associate Professor at the LUT School of Energy Systems, LUT University. His research focuses on fluid dynamics, granular materials, computational fluid dynamics (CFD), heat transfer, and multiphase flows. He has contributed to studies on energy systems, biomaterials, and biomedical engineering applications. His work integrates numerical methods such as the lattice Boltzmann method and discrete element method (DEM) to analyze complex phenomena like granular shock waves, conjugate heat transfer, and fluid-particle interactions. Key research areas include direct air capture systems, granular media failure mechanisms, and turbulence modeling in multiphase flows. His publications span from 2000 to 2025, with recent emphasis on CFD applications in energy systems and biomedical contexts. Notable contributions address challenges in fluid power systems, porous media behavior, and arterial blood flow dynamics. His academic contributions include over 50 peer-reviewed articles, covering topics from granular shear flows to cardiovascular modeling. Collaborative work bridges engineering and biomedical disciplines, reflecting his interdisciplinary approach to solving complex physical and biological systems.

• Partial Differential Equations
• Computational Micromagnetism
• Numerical Analysis
• +۵ مورد دیگر

Michael Feischl is a Professor for Computational PDEs at TU Wien (since 2022) and holds an ERC Consolidator Grant for his project "New Frontiers in Optimal Adaptivity" (2024–2029). His research focuses on partial differential equations with random coefficients, computational micromagnetism (Landau-Lifshitz-Gilbert equation), and optimal adaptive mesh refinement techniques. He leads the Computational PDEs research group within the Institute of Analysis and Scientific Computing. Education and career highlights include roles as Associate Professor at TU Wien (2019–2022), W2 Professor at University of Bonn (2017–2018), and Junior Research Group Leader at KIT (2015–2017). His work bridges numerical analysis, computational physics, and machine learning, with a strong emphasis on rigorous mathematical foundations and algorithmic efficiency. Research interests include: Adaptive finite element and boundary element methods Stochastic modeling and uncertainty quantification Computational methods for micromagnetic simulations Machine learning applications in numerical analysis His recent work explores optimal adaptivity for time-dependent PDEs, neural network-based solvers, and efficient discretization strategies for complex physical systems. Key contributions include advancements in a posteriori error estimation and hierarchical training of neural networks.

Matthew J. Lundquistمشاهده پروفایل

دانشیار

• Urban Ecology
• Biodiversity
• Aquatic Ecology
• +۱۲ مورد دیگر

Matthew J. Lundquist is Associate Professor of Biology and Chair of the Department of Natural Sciences at Marymount Manhattan College. He is based in Carson Hall, Room 603, and actively leads research and teaching in urban ecology, biodiversity, and environmental science. Ph.D. in Biology (Ecology, Evolution, and Behavior), Binghamton University M.S. in Entomology, Michigan State University B.S. in Biology (Ecology & Conservation Biology), SUNY Oneonta Dr. Lundquist's research centers on the ecological impacts of urbanization, particularly on biodiversity and ecosystem function in urban green spaces and freshwater systems. His work includes modeling pollinator movement through NYC via 'Bug Roads,' assessing insect biodiversity in tree pits, and studying aquatic insect communities in the Bronx River. He integrates GIS, statistical modeling, and ecological fieldwork to understand how cities shape natural systems. His recent publications span urban ecology, aquatic biodiversity, and science pedagogy, reflecting a strong trend in applying data science, modeling, and technology to ecological and educational challenges. Research areas include urban stream food webs, functional diversity, and hybrid science lab models using AI and big data. Dr. Lundquist mentors undergraduate and post-bac researchers in the Lundquist Lab, guiding students in ecological research and data analysis. He has secured ongoing research projects but no specific grants are mentioned. He teaches courses such as Conservation Biology, Ecology, Environmental Science, Biostatistics, and The Urban Ecosystem. He leads the Lundquist Lab, which focuses on urban biodiversity in terrestrial and aquatic systems, primarily studying insects and biogeochemistry. The lab uses computational tools, R, Python, and GIS for data analysis and modeling, and maintains a GitHub presence for code sharing and educational resources.