جست‌وجوی استاد و پژوهشگر

Alberto G. Curtoمشاهده پروفایل

استادیار

• Nanophotonics
• Semiconductor Nanophotonics
• Chirality in Optics
• +۴ مورد دیگر

Alberto G. Curto is an Assistant Professor at Eindhoven University of Technology, specializing in nanophotonics and semiconductor optoelectronics. He leads research on light-matter interactions at the nanoscale, focusing on atomically thin semiconductors and chiral nanophotonics applications. His work spans sensing, imaging, and spectroscopy, with contributions to directional light emission and chiral detection technologies. Education BSc in Physics, Universidad de Salamanca (2002–2007) MSc and PhD in Photonics, ICFO – The Institute of Photonic Sciences (2008–2013) Postdoctoral Fellow at Stanford University (2013–2016) Research Interests Curto’s research explores semiconductor nanophotonics for sensing and imaging, leveraging atomically thin materials and chiral optics. Key areas include: Enhanced light-matter interactions using nano-optical structures Chiral detection via dielectric resonators and metasurfaces Exciton dynamics in 2D semiconductors Publications His work emphasizes practical applications of nanophotonics, with recent studies on chiral sensing enhancement, silicon metasurfaces, and exciton manipulation. Over 47 peer-reviewed articles highlight his contributions to light confinement and directional emission. Awards ERC Starting Grant (2020) NWO START-UP Grant (2018) OSA Senior Member (2021) ICFO PhD Thesis Award (2014) Grants & Projects He leads the Zwaartekracht PSN Research Centre for Integrated Nanophotonics (2014–2025), focusing on nanowires, photonic crystals, and photonics applications. Labs & Teams His research group at TU Eindhoven develops novel nanophotonic devices and chiral sensing platforms, collaborating on projects like the ERC CHANSON grant.

Lawrence H. Staibمشاهده پروفایل

استاد

• Medical Image Analysis
• Machine Learning
• Nonrigid Registration
• +۶ مورد دیگر

Lawrence H. Staib is a Professor of Biomedical Engineering at Yale University, with additional academic appointments in Electrical & Computer Engineering and Radiology & Biomedical Imaging. He holds a Ph.D. from Yale University and specializes in automated medical image analysis, including techniques like model-based segmentation, nonrigid registration, and diffusion tensor imaging (DTI). His research focuses on applications in neuroscience, cardiology, and cancer imaging, emphasizing machine learning and functional MRI analysis. His key contributions include advancements in white matter tractography via anisotropic wavefront evolution, real-time neural tract parcellation (Fasciculography), and noise reduction in diffusion tensor fields. Staib is a Fellow of the American Institute for Medical and Biological Engineering (2015), recognizing his impactful work in medical imaging technologies. Staib's research also encompasses statistical deformation models, perturbation-based shape analysis, and 3D deformable models for volumetric segmentation. He has developed patented 3D ultrasound computed tomography systems (USPTO #6878115, 7025725). His work bridges clinical needs with computational methods, addressing challenges in image registration, structural connectivity analysis, and medical robotics.

Matthias Schlottbomمشاهده پروفایل

دانشیار

• Numerical Analysis
• Computational Mathematics
• Radiative Transfer
• +۴ مورد دیگر

Matthias Schlottbom is an Associate Professor specializing in Mathematics of Computational Science, with a focus on numerical methods and their applications in physics, biology, and engineering. His research integrates advanced computational techniques with interdisciplinary problems, including radiative transfer, photonic crystals, and chemotaxis modeling. Research Interests: Schlottbom’s work spans numerical analysis, finite element methods, and machine learning. He develops high-order discretization schemes, iterative solvers for anisotropic transport, and mathematical frameworks for biological network formation. Publications: Recent articles highlight his contributions to accelerating radiative transfer simulations, extending component mode synthesis for Helmholtz equations, and analyzing diffusion limits in kinetic models. His work often bridges computational mathematics with practical applications in photonics and multiscale systems. Collaborations: He actively collaborates on datasets for optical simulations, radiative transfer algorithms, and photonic crystal modeling, contributing to open-access repositories like 4TU.Centre and Zenodo. Activities: Schlottbom has organized workshops such as the Kinetic Theory Workshop in the Netherlands and delivered keynotes on residual minimization and data-driven methods for transport equations. Scientific Awards: No specific awards or fellowships are mentioned in the provided materials. Advising & Grants: Details about students, advising roles, or grant funding are not included in the available data.

Daniel Prestonمشاهده پروفایل

پژوهشگر ارشد

• Supramolecular Chemistry
• Inorganic Chemistry
• Organometallic Chemistry
• +۵ مورد دیگر

Dr. Daniel Preston is an ARC DECRA Fellow and leader of the Preston Group at the Research School of Chemistry , Australian National University. His research focuses on supramolecular chemistry, designing structurally and functionally complex architectures from metal ions and organic ligands in solution. Education : PhD in Chemistry from the University of Otago, Rutherford Postdoctoral Fellowship at the University of Canterbury (NZ). Key research themes include: Supramolecular self-assembly of metallosupramolecular systems Development of stimuli-responsive foldamers and sensors Photophysical applications in FRET, donor-acceptor systems Anion recognition and gas adsorption studies His recent publications highlight work on: Low-symmetry metal cages (Fe 2+ , Pd 2+ , Pt 2+ ) Dynamic covalent approaches to lantern-shaped architectures Excited state control in bichromophoric photosensitizers Heterometallic and heteroleptic systems with positional/orientational control Scientific Awards : ARC DECRA Fellow ARC Future Fellow Rutherford Postdoctoral Fellowship Dr. Preston supervises PhD candidates Jessica Algar and Zack Avery, with active projects in mixed-metal clusters, self-assembled systems, and molecular machine development.

• Heat Transfer
• Energy Storage
• Thermal Management
• +۵ مورد دیگر

Ankur Jain is a Professor in the Mechanical and Aerospace Engineering Department at The University of Texas at Arlington, with a joint appointment in Bioengineering. His research focuses on heat transfer in Li-ion batteries, microscale thermal transport, bioheat transfer, and additive manufacturing. He holds leadership roles, including serving as Associate Editor for IEEE Transactions on Components, Packaging and Manufacturing Technologies and Secretary of the ASME Heat Transfer Division's K16 Committee. Education: Ph.D. (2007) and M.S. (2003) in Mechanical Engineering from Stanford University; B.Tech. (2001) in Mechanical Engineering from IIT Delhi with top honors. Research interests span energy conversion/storage, thermal management of electronics, and biomedical heat transfer applications. Notable achievements include the NSF CAREER Award (2016), ASME Fellow status (2022), and UTA President's Award for Excellence in Teaching (2022). His work has been supported by NSF, DOE, ONR, and Indo-US Science & Technology Forum. Advancing thermal runaway prevention in Li-ion batteries and improving additive manufacturing processes are key current focuses. Collaborations include industry partners like Underwriters Laboratories and Cuberg, Inc.

Yves Bourgaultمشاهده پروفایل

استاد

• Computational Fluid Dynamics
• Numerical Methods
• Finite Element Methods
• +۳ مورد دیگر

Yves Bourgault is a Full Professor in the Department of Mathematics and Statistics at the University of Ottawa. He holds a MSc and PhD from Laval University. His research focuses on computational fluid dynamics, numerical methods, finite element techniques, and continuum mechanics modeling, with applications in cardiac electrophysiology and ecological systems. Dr. Bourgault has supervised several graduate students, including Edward Boey (co-supervised), Sana Keita, Saint-Cyr Koyagurebo-Ime, and Kak Choon Loy. His work integrates advanced numerical techniques to address complex problems in biomedical engineering, environmental science, and mathematical physics. Key methodologies include finite element methods, deferred correction schemes, and anisotropic mesh adaptation. His research group is part of the Applied Mathematics division at the University of Ottawa, emphasizing interdisciplinary applications. Recent work explores climate change impacts on ecological systems, cardiac tissue modeling using high-resolution MRI data, and robust numerical methods for reaction-diffusion equations. Publications span topics such as bidomain models for cardiac electrophysiology, fluid-structure interaction in heart mechanics, and mathematical modeling of fuel cells. His contributions bridge theoretical numerical analysis with real-world biomedical and environmental challenges.

• Radiative heat transfer
• Computational thermal sciences
• Turbulence-radiation interaction
• +۴ مورد دیگر

Pedro Jorge Martins Coelho is a Professor in the Mechanical Engineering Department at Instituto Superior Técnico, University of Lisbon, Portugal. His academic career spans several decades with a focus on advanced thermal sciences and computational methods. His research has significantly contributed to the understanding of radiative heat transfer phenomena in complex systems. Dr. Coelho's educational background includes a Ph.D. in Mechanical Engineering, which has provided the foundation for his extensive research in thermal sciences. His work demonstrates a strong theoretical foundation combined with practical applications across various engineering domains. His primary research interests encompass radiative heat transfer, turbulence-radiation interaction, combustion modeling, and numerical methods for thermal systems. Recent work has expanded into biomedical applications of thermal radiation, particularly in laser-tissue interactions for cancer detection and treatment. His publications reveal a consistent focus on developing and refining computational methods for solving complex heat transfer problems, with particular emphasis on the radiative transfer equation in various media and geometries. Analysis of his recent publications shows a clear evolution toward more complex and interdisciplinary applications, including biomedical thermal applications, advanced turbulence modeling, and thermal management of electrical systems. His work consistently bridges fundamental theoretical developments with practical engineering applications, particularly in combustion systems, energy recovery, and thermal management. Dr. Coelho has served on editorial boards for prestigious journals including Heat Transfer Research, Computational Thermal Sciences, and International Journal of Energy for a Clean Environment, demonstrating his standing in the thermal sciences community. His research collaborations span numerous institutions and researchers worldwide, as evidenced by his extensive publication record with various co-authors across different countries. He has also been involved in conference organization, serving as Associate Editor for major international heat transfer conferences.

Paul Stevensonمشاهده پروفایل

استادیار

• Biophysics
• Quantum Engineering
• Quantum Sensing
• +۳ مورد دیگر

Paul Stevenson is an Assistant Professor of Physics at Northeastern University's College of Science, leading the Stevenson Group. His research focuses on quantum sensing and biophysical dynamics using solid-state spins, particularly nitrogen vacancy centers in diamond. He develops nanoscale sensors for probing molecular motion and quantum communication technologies. Notably, his work bridges physics, chemistry, and biology, addressing challenges such as magnetism in complex systems and single-molecule imaging. He is a 2023 TIER1 Awardee and collaborates with institutions like Brown University and UC Berkeley. Stevenson's lab explores quantum materials and spintronics, leveraging interdisciplinary approaches to advance quantum hardware and biophysical understanding. His group's innovations include ultrasensitive magnetometers and tools for studying antiferromagnetic ordering. Contact: p.stevenson@northeastern.edu .

Panayiotis Papadopoulosمشاهده پروفایل

استاد

• Computational Mechanics
• Solid Mechanics
• Biomechanics
• +۱ مورد دیگر

Panayiotis Papadopoulos is a Professor and the Byron and Elvira Nishkian Chair in Structural Engineering at the University of California, Berkeley. He serves as Director of the CoE Aerospace Engineering Programs and contributes to the Computational Solid Mechanics Lab. Education: Ph.D. in Civil Engineering, University of California, Berkeley (1991) M.S. in Civil Engineering, University of California, Berkeley (1987) Dipl. in Civil Engineering, Aristotle University, Thessaloniki, Greece (1986) Research Interests: Professor Papadopoulos specializes in computational mechanics, solid mechanics, biomechanics, and applied mathematics. His work bridges theoretical modeling with advanced numerical methods, focusing on multiscale analysis, thermomechanical coupling, and material failure mechanisms. Publication Trends: His recent research emphasizes multiscale finite element methods, thermomechanical analysis of deformable solids, and biomechanical modeling. Key themes include contact mechanics, phase transformations in shape-memory alloys, and computational approaches for microstructural analysis. Scientific Awards: Byron and Elvira Nishkian Chair in Structural Engineering Labs and Teams: He leads the Computational Solid Mechanics Lab, which develops advanced numerical frameworks for material behavior under complex thermomechanical conditions.

Travis B. Thompsonمشاهده پروفایل

استادیار

• Mathematical Modeling
• Scientific Computing
• Machine Learning in Medicine
• +۵ مورد دیگر

Travis B. Thompson, Ph.D. is an Assistant Professor in the Department of Mathematics and Statistics at Texas Tech University, leading the TM4 (Texas Tech Translational and Theoretical Mathematical Modeling and Machine Learning in Medicine) research group. His academic journey includes postdoctoral work at Rice University, Simula Research Laboratory, and the University of Oxford, focusing on mathematics applied to neurodegenerative diseases. Education: Ph.D. in Mathematics from Texas A&M University (2013) Dr. Thompson develops theoretical mathematical models and applies scientific computing and machine learning to study neurological pathologies, particularly Alzheimer’s disease. His work explores complex biological processes on networks, translational healthcare applications, and nutritional security implications. Current research trends integrate neuroimaging data with finite element simulations to model tau progression , amyloid beta dynamics , and glymphatic clearance in age-related diseases. Scientific awards and honors were not explicitly mentioned in the provided materials. Dr. Thompson’s interdisciplinary approach connects computational neuroscience with biomedical engineering , utilizing techniques like diffusion tensor imaging and level set methods to analyze pathological protein spread and brain tissue mechanics . The TM4 research group focuses on network neurodegeneration , personalized medicine , and machine learning diagnostics . Their work spans from microfluidic cancer detection to computational modeling of brain clearance mechanisms , addressing challenges in both neurodegenerative diseases and biomedical engineering through rigorous mathematical frameworks.

Daniela Calvettiمشاهده پروفایل

استاد

• Large Scale Scientific Computing
• Computational Inverse Problems
• Uncertainty Quantification
• +۴ مورد دیگر

Daniela Calvetti is the James Wood Williamson Professor in the Department of Mathematics, Applied Mathematics, and Statistics at Case Western Reserve University. Her research focuses on large-scale scientific computing, computational inverse problems, uncertainty quantification, and predictive modeling in neuroscience, metabolism, and cellular physiology. She holds a PhD from the University of North Carolina-Chapel Hill. Her work integrates advanced mathematical techniques with biomedical applications, including brain energy metabolism modeling, MEG/EEG source reconstruction, and computational methods for medical imaging. Notable contributions include Bayesian hierarchical algorithms for inverse problems and interdisciplinary collaborations bridging mathematics with neuroscience and physiology. Recent research highlights include developing sparsity-promoting Bayesian models for tomography, computational frameworks for neuromuscular control variability, and predictive models of disease dynamics like post-pandemic COVID-19 recurrence. Her methodologies emphasize statistically inspired preconditioning and adaptive meshing techniques to enhance computational efficiency in solving complex inverse problems. Dr. Calvetti has published extensively across computational science, inverse problems, and biomedical applications. She leads a research group advancing interdisciplinary computational methods with applications in neuroscience, virology, and metabolic systems.

Gleb Yushinمشاهده پروفایل

استاد

• Nanomaterials
• Energy Storage
• Carbon-Based Materials
• +۹ مورد دیگر

Gleb Yushin is a Professor at the Georgia Institute of Technology’s School of Materials and Engineering, co-founder of Sila Nanotechnologies, and co-Editor-in-Chief of Materials Today . He joined Georgia Tech in 2007 and is a Fellow of multiple scientific societies (ACS, APS, ECS, MRS, NAI). His research focuses on energy storage materials, nanomaterials, and carbon-based hybrids for applications in batteries, supercapacitors, and biomedical devices. Education: B.A. Physics (with Honors, 1999) from Polytechnic Institute (Saint-Petersburg, Russia); Ph.D. Materials Science (2003) from North Carolina State University. Research interests include advancing energy storage systems (lithium-ion, sodium-ion, magnesium-ion batteries), carbon nanomaterials, and functional materials for environmental and biomedical applications. His work emphasizes nanostructured materials design, porous carbon synthesis, and electrochemical performance optimization. Recent trends in his publications highlight innovations in anode materials for high-performance batteries, supercapacitor electrode design, and carbide-derived carbon applications. Awards: NSF CAREER Award (2010), R&D 100 Award (2009), AFOSR YIP Award (2009), and recognition as a Clarivate Analytics “Leading Cited Researcher” (2018). Prof. Yushin advises students in energy storage and materials science, including Vismay Chandra and Ashwin Sankara Raman. His lab focuses on scalable synthesis of advanced materials and has secured grants from NSF, AFOSR, and industry partnerships. He holds over 35 patents and has authored ~130 publications (20k+ citations by 2018). Labs/Teams: His research group (www.nano-tech.gatech.edu) actively collaborates on energy storage innovations and nanomaterials characterization.

Magdalena Schreter-Fleischhackerمشاهده پروفایل

پژوهشگر

• Computational Mechanics
• Additive Manufacturing
• Multi-phase Flow Modeling
• +۳ مورد دیگر

Dr. Magdalena Schreter-Fleischhacker works at the Technical University of Munich within the Professorship of Simulation for Additive Manufacturing . Her research focuses on physics-based computational modeling of coupled liquid-powder-gas dynamics in metal additive manufacturing, including melt pool dynamics and powder-gas interactions . She specializes in multi-phase flow modeling using cut-element and diffuse interface methods with continuous/discontinuous Galerkin schemes . She also develops constitutive models for quasi-brittle materials like 3D printed concrete and rock, incorporating anisotropy , gradient-enhanced damage mechanics , and micropolar continua . Her computational work leverages matrix-free algorithms and parallel computing , with significant contributions to the deal.II finite element library . Research Interests Physics-based computational modeling of coupled liquid-powder-gas dynamics in additive manufacturing Multi-phase flow simulation using sharp/diffuse interface methods Advanced constitutive modeling for quasi-brittle materials (rock, soils, 3D printed concrete) High-performance computing and matrix-free algorithms Notable Contributions Development of consistent diffuse-interface models for melt-vapor dynamics Improvements to continuum surface flux models in additive manufacturing Formulation of gradient-enhanced damage-plasticity models for geological materials Principal contributor to the deal.II library (version 9.6) Supervised Student Projects Johannes Resch (2024): DG-based thermo-hydrodynamic melt pool simulations Julian Brotz (2024): DEM-FEM coupling for fluid-powder interaction Andreas Ritthaler (2024): Matrix-free cutDG formulation for complex flows Tinh Vo (2023): Laser modeling for melt pool simulations Scientific Awards ERC Starting Grant recipient

C. Armando Duarteمشاهده پروفایل

استاد

• Computational Mechanics
• Structural Engineering
• Multiscale Modeling
• +۵ مورد دیگر

Prof. C. Armando Duarte is the Nathan M. Newmark Distinguished Professor in Civil and Environmental Engineering at the University of Illinois at Urbana-Champaign (UIUC). He holds affiliations with the Computational Science and Engineering Program and the National Center for Supercomputing Applications (NCSA). His research focuses on computational mechanics, particularly the Generalized Finite Element Method (GFEM/XFEM), multiscale modeling, fracture mechanics, and hydraulic fracturing. He has authored/co-authored over 100 publications and co-edited books on computational methods. Education: Ph.D. (1996) and M.Sc. (1991) in Engineering Mechanics from the University of Texas at Austin and Federal University of Santa Catarina, respectively, and a B.Sc. in Mechanical Engineering from the Federal University of Pernambuco. Professional Roles: Professor at UIUC since 2015, previously at the University of Alberta and visiting roles at institutions in Brazil, Portugal, and the Netherlands. He serves on editorial boards of computational mechanics journals and chairs committees for professional societies like USACM and ASCE. Research Interests: Multiscale problems, computational fracture mechanics, meshfree methods, and multiphysics simulations. His work emphasizes 3D fracture analysis, hydraulic fracturing, and thermal gradient modeling. Awards: Recognitions include the Nathan Newmark Professorship, USACM Fellowship, and multiple best paper awards. His work has been cited over 9,000 times, with papers featured in top journals like Computer Methods in Applied Mechanics and Engineering . Teaching: Renowned for excellence in courses like Finite Element Methods, Structural Analysis, and Computational Plates and Shells. His teaching accolades span over two decades at UIUC.

Keenan Craneمشاهده پروفایل

دانشیار

• Computer Science
• Mathematics
• Scientific Computing
• +۷ مورد دیگر

Keenan Crane is the Michael B. Donohue Associate Professor of Computer Science and Robotics at Carnegie Mellon University , with membership in the Center for Nonlinear Analysis and mentorship in the Geometry Collective . His research bridges differential geometry and computer science to develop fundamental algorithms for geometric data processing. Education : BS from University of Illinois at Urbana-Champaign, PhD from Caltech Fellowships : Google PhD Fellow, NSF Mathematical Sciences Postdoctoral Fellow Research focuses on Discrete Differential Geometry , addressing PDE solutions, mesh processing, and geometric modeling through methods like: Walk on Spheres for PDEs Intrinsic Triangulations for robust geometry Repulsive Energy formulations for collision avoidance Recent publications span 2025–2021 , emphasizing grid-free algorithms , anisotropic mesh generation , and differentiable systems . Scientific accolades include Packard Fellowship and NSF CAREER Award . Students include Nicole Feng , Olga Gutan , and Zoë Marschner . During his 2024 sabbatical at Roblox , he does not accept new researchers. Key software contributions include Penrose (math diagram generation) and I♥Mesh (domain-specific language for mesh algorithms).