جست‌وجوی استاد و پژوهشگر

David Simmons-Duffinمشاهده پروفایل

استاد

• Theoretical Physics
• Conformal Field Theory
• Bootstrap Methods
• +۵ مورد دیگر

David Simmons-Duffin is a Professor of Theoretical Physics at the California Institute of Technology (Caltech), where he has held positions since 2016. He is part of the Division of Physics, Mathematics and Astronomy, contributing to the Physics Department. His career progression includes roles as Visiting Associate (2016–17), Assistant Professor (2017–20), and Associate Professor (2020–21) before becoming full Professor in 2021. Education: A.B. and A.M. from Harvard University (2006), CASM from the University of Cambridge (2007), and Ph.D. from Harvard University (2012). His research focuses on conformal field theory (CFT), bootstrap methods, quantum field theory, and AdS/CFT correspondence. Key areas include precision computations in strongly coupled systems, critical phenomena, and applications to holography and quantum gravity. Research highlights include advancing the conformal bootstrap program, analyzing CFT data in 3D Ising models, and exploring connections between CFTs and gravitational theories. His work often bridges theoretical frameworks with numerical methods, yielding insights into operator product expansions (OPE), spectral gaps, and causality constraints. Affiliations include the Institute for Quantum Information and Matter (IQIM) and other Caltech research centers. His contributions have shaped modern approaches to understanding universality in critical systems and the geometric aspects of quantum field theories. Notable collaborations involve high-precision calculations, bootstrap island techniques, and studies of thermal QFT and light-ray operators. His work emphasizes interdisciplinary methods, combining analytic tools with computational advancements to tackle complex theoretical problems.

• Earthquake Engineering
• Structural Dynamics
• Seismic Risk Assessment
• +۳ مورد دیگر

Prof. Dr. Hakkı Polat Gülkan is a Professor at Başkent University's Civil Engineering Department. With a PhD (1971) and Master's (1968) from the University of Illinois in Civil Engineering and a Bachelor's (1966) from METU, his career spans over five decades in earthquake engineering, structural dynamics, and disaster management. PhD: University of Illinois, Civil Engineering (1971) Master's: University of Illinois, Civil Engineering (1968) Bachelor's: Middle East Technical University, Civil Engineering (1966) His research focuses on seismic risk assessment, structural behavior under extreme loads, and disaster mitigation strategies. Key contributions include earthquake simulator development, ground motion analysis, and retrofitting techniques for masonry and reinforced concrete structures. He has published extensively on deformation limits, response spectra, and historical building preservation. Recent work includes 15+ articles from 2024-2012 analyzing Istanbul's seismic hazards, Marmara region dynamics, and post-earthquake structural integrity. Conference papers address Turkey's endemic building vulnerabilities and deformation thresholds for seismic isolation systems. Scientific Achievements: Elected to U.S. National Academy of Engineering (2023) As an active journal reviewer for 13+ publications (2023-2024), he contributes to advancing earthquake engineering discourse. His teaching portfolio includes advanced structural analysis, concrete mechanics, and seismic design courses.

Mark Crowleyمشاهده پروفایل

دانشیار

• Reinforcement Learning
• Deep Learning
• Ensemble Methods
• +۶ مورد دیگر

Mark Crowley is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Waterloo , with a cross-appointment in the Cheriton School of Computer Science . He is actively involved in the Waterloo Artificial Intelligence Institute (WAII) , the Waterloo Institute for Complexity and Innovation (WICI) , and serves as National Secretary for the Canadian Artificial Intelligence Association (CAIAC) , coordinating the Canadian Conference on AI . Research interests span the theoretical and applied aspects of Reinforcement Learning , Deep Learning , Manifold Learning , and Ensemble Methods . His work addresses challenges in domains with spatial dynamics, multi-agent systems, and uncertainty, particularly in Computational Sustainability (forest fire management, sustainable forestry), Autonomous Driving , Medical Imaging , and Material Design . Recent research focuses on integrating causal modeling with generative representation learning to improve out-of-distribution robustness in motion forecasting applications. Key publications include foundational work on ChemGymRL environments for safe chemical process reinforcement learning, Generative Causal Representation Learning for robust forecasting, and collaborative work on multi-advisor reinforcement learning in multi-agent settings. He co-authored a textbook Elements of Dimensionality Reduction and Manifold Learning (Springer, 2023) with Prof. Ali Ghodsi and Prof. Fakhri Karray. Teaching includes graduate and undergraduate courses in Algorithm Design , Computational Intelligence , Reinforcement Learning , and Data Modeling at the University of Waterloo since 2018. His research group has produced several notable graduates including Benyamin Ghojogh (2021), who continued as a postdoc until 2022.

• Fluid Mechanics
• Turbulence
• Computational Fluid Dynamics (CFD)
• +۴ مورد دیگر

Philipp Schlatter is a Professor in the Department of Mechanics at KTH Royal Institute of Technology. His research focuses on fluid mechanics, turbulence, and computational fluid dynamics (CFD), with expertise in high-performance computing and direct numerical simulations (DNS). He leads projects involving scalable CFD frameworks like Neko and Nek5000, and investigates turbulent boundary layers, flow control, and coherent flow structures. His work includes experimental and numerical studies of wing profiles, rotating systems, and transition dynamics. Schlatter teaches courses on computational fluid dynamics and turbulence, emphasizing both theoretical and practical aspects of fluid mechanics. Key research interests include developing numerical methods for high-fidelity simulations, understanding turbulence mechanisms, and optimizing flow control strategies. His contributions span aerodynamics, heat transfer, and the application of machine learning to fluid dynamics problems. Schlatter collaborates extensively on interdisciplinary projects, leveraging advanced computing resources to address complex fluid flow phenomena. Publications highlight advancements in DNS frameworks, Bayesian optimization for flow control, and analysis of turbulent structures in pipe and boundary layer flows. His research also addresses challenges in measurement techniques and uncertainty quantification in CFD simulations.

• Theoretical Chemistry
• Quantum Chemistry
• Relativistic Effects
• +۷ مورد دیگر

Professor Kenneth Ruud is a leading expert in theoretical and computational chemistry at UiT The Arctic University of Norway. He serves as Director General of the Norwegian Defence Research Establishment and leads the Hylleraas Centre for Quantum Molecular Sciences. His research focuses on relativistic quantum chemistry, developing advanced ab initio methods for molecular property calculations, and integrating QM/MM and continuum solvent models. Education: PhD from University of Oslo (1998, supervised by Trygve Helgaker) Postdoc: University of San Diego with Peter Taylor (1998-2000) His work spans relativistic effects in molecular properties, vibronic coupling, and X-ray spectroscopy. He contributes to software development through programs like Dalton, Dirac, ReSpect, and OpenRSP. Recent publications highlight applications in spin-vibronic dynamics, heavy metal L/M-edge XAS, and topological materials. Key scientific contributions include relativistic DFT for nuclear spin-rotation constants, polarizable embedding models for vibrational spectra, and quantum dynamics frameworks. Awards recognize his impact through the Dirac Medal (2008) and multiple academy memberships. Elected to Norwegian Academy of Science and Letters Fellow of American Association for the Advancement of Science (AAAS) Foreign member of Finnish Academy of Science and Letters He actively participates in open science initiatives and serves on boards including Norges Forskningsråd and CAROS center for subsea robotics. Current projects involve quantum molecular science in extreme environments and computational protocol development.

Ilaria Perugiaمشاهده پروفایل

استاد

• Numerical methods for PDEs
• Finite element methods
• Discontinuous Galerkin methods
• +۶ مورد دیگر

Ilaria Perugia is a University Professor (Univ.-Prof.) and Chair of Numerics of PDEs at the Department of Mathematics, Faculty of Mathematics, University of Vienna. She also serves as Deputy Head of the Research Platform Erwin Schrödinger International Institute for Mathematics and Physics. Her research focuses on numerical methods for partial differential equations with applications in computational physics and engineering. Professor Perugia's primary research interests include: Numerical methods for PDEs Finite element methods Discontinuous Galerkin methods Trefftz methods Virtual element methods Space-time methods Computational electromagnetics Wave propagation problems Nonlinear reaction-diffusion problems Her work spans theoretical analysis, algorithm development, and practical implementation of numerical methods for solving complex physical phenomena. Her recent publications demonstrate a strong focus on space-time methods, virtual element methods, and structure-preserving discretizations for wave equations, heat equations, and other PDEs. She has made significant contributions to the development of stable and efficient numerical schemes that preserve important physical properties of the underlying continuous problems, particularly in the context of wave propagation and computational electromagnetics. Professor Perugia leads a research group comprising several researchers and students including Mattia Corti, Matteo Ferrari, Monica Nonino, Andrea Scaglioni, Paul Stocker, Enrico Zampa, and Marco Zank. Her group actively collaborates on projects related to numerical analysis and scientific computing, with particular emphasis on developing novel discretization techniques for challenging PDE problems.

Martin Berggrenمشاهده پروفایل

استاد

• Computational Design Optimization
• Numerical Optimization Algorithms
• Gradient-Based Algorithms
• +۸ مورد دیگر

Martin Berggren is a Professor at the Department of Computing Science , Umeå University , Sweden. His work focuses on Computational Design Optimization , combining computer simulations and numerical optimization to enhance engineering designs for devices like antennas, microwave components, and loudspeakers. Berggren is also active in mathematical modeling of physical phenomena, particularly wave propagation and fluid mechanics, with a strong emphasis on finite-element methods . His research addresses large-scale conceptual design problems using thousands to millions of design variables, relying on gradient-based algorithms and adjoint-based computations of design sensitivities—similar to back-propagation in deep learning. Key application areas include acoustic and electromagnetic devices, where he investigates damping mechanisms, boundary conditions, and material distribution. Other interests, though less active, involve flow control and unsteady fluid–structure interaction . Berggren collaborates extensively on projects such as Structured Regularization , Topology Optimization of Acoustic Black Holes , and Design of Microstrip-to-Waveguide Transitions . His publications span journals like Journal of Computational Physics , Pattern Analysis and Applications , and IEEE Transactions on Antennas and Propagation , often co-authored with researchers like Linus Hägg , Eddie Wadbro , and Disi Lin .

Eddie C. Redمشاهده پروفایل

دانشیار

• Computational Physics
• Quantum Mechanics
• Atomic Physics
• +۳ مورد دیگر

Eddie C. Red is an Associate Professor of Mathematics and Computational Sciences at Morehouse College , where he currently serves as the Interim Dean of the Science, Technology, Engineering, and Mathematics (STEM) Division. He earned his B.S. from Morehouse College (class of 2000) , followed by his M.S. and Ph.D. from Florida Agricultural and Mechanical University . Dr. Red also completed post-doctoral education at Lawrence Berkeley National Laboratory . Interim Dean, STEM Division Former Chair, Mathematics and Computational Science Division Former Chair, Physics & Dual-Degree Engineering Department Dr. Red’s research interests bridge atomic physics, quantum mechanics, and computational modeling , with a focus on: Photoionization cross-sections Bound states in the continuum Velocity map imaging techniques Mathematical formulations for quantum operators His work has resulted in publications in Physical Review A, Communications Physics, and the Journal of Physics B , alongside numerous conference presentations. Dr. Red has led the NuMaSS (Nuclear, Materials, and Space Science) Summer Enrichment Program for K-12 students and directed the Research Experience with Diversification Laboratory , emphasizing student training and research. Scientific awards include: Principal Investigator for Department of Energy National Nuclear Security Administration awards Dr. Red has served on multiple faculty governance committees, including the Admissions Committee , Faculty Grievance Committee , and Faculty Research Committee .

• Functional Analysis
• Quantum Systems with Boundary
• Quantum Control on Infinite Dimensional Systems
• +۵ مورد دیگر

Juan Manuel Pérez Pardo is an Associate Professor in the Department of Mathematics at Universidad Carlos III de Madrid, where he has been a faculty member since 2019, progressing from Assistant Professor to his current position as Associate Professor since December 2022. His academic journey includes postdoctoral research at prestigious institutions including the Istituto Nazionale di Fisica Nucleare in Naples, Italy, and the Instituto de Ciencias Matemáticas in Madrid. Dr. Pérez Pardo earned his PhD in Mathematics from Universidad Carlos III de Madrid in 2013, following a Master's degree in Mathematical Engineering from the same institution and a Master's degree in Theoretical Physics from Universidad Complutense de Madrid. His undergraduate studies were in Physics at Universidad Complutense de Madrid. His research focuses on the intersection of functional analysis and quantum physics, particularly in three main areas: Functional Analysis : Applying functional analytical tools to quantum systems, with emphasis on quadratic forms associated with differential operators and evolution equations in Hilbert spaces. Quantum Systems with Boundary : Studying quantum dynamics when boundaries are present, combining operator theory, spectral theory, and differential geometry. Quantum Control on Infinite Dimensional Systems : Developing mathematical theory for controlling quantum systems that are infinite dimensional in nature, relevant to quantum computation technologies. His publication record shows a strong focus on quantum control theory, self-adjoint extensions of differential operators, and the mathematical foundations of quantum mechanics. Recent work (2022-2025) has concentrated on stability of non-autonomous Schrödinger equations, quantum controllability, and relativistic quantum systems. Dr. Pérez Pardo has received several prestigious awards including the Juan de la Cierva Fellowship and the QUITEMAD+ Postdoctoral Fellowship. His work on boundary dynamics driven entanglement was highlighted in Europhysics News and tagged as IOPselect by the Institute of Physics. He actively mentors students at all levels, currently supervising PhD candidate Ángel Aitor Balmaseda Martín on "Quantum Control at the Boundary." He has also supervised numerous Master's and Bachelor's students on topics ranging from numerical solutions of quantum control problems to modeling Josephson junctions. Dr. Pérez Pardo is a key member of the Q-Math Research Group at UC3M and has organized multiple international workshops on Information Geometry, Quantum Mechanics, and Applications. He also serves on the editorial board of the International Journal of Geometric Methods in Modern Physics.

Endre Süliمشاهده پروفایل

استاد

• Numerical Analysis of Partial Differential Equations
• Finite Element Methods
• Computational Modeling of Fracture
• +۴ مورد دیگر

Endre Süli is Professor of Numerical Analysis at the University of Oxford, where he has maintained a distinguished academic career since 1985. He currently serves as Fellow and Tutor in Mathematics at Worcester College and Supernumerary Fellow at Linacre College. His progression at Oxford includes University Lecturer in Numerical Analysis (1985-1996), Reader in Numerical Analysis (1996-1999), and Professor of Numerical Analysis (1999-present). Süli completed his B.Sc. in Mathematics at the University of Belgrade (1974-1978), followed by an M.Sc. in Mathematics (1978-1980). As a British Council Visiting Student, he studied at Reading University and Oxford University in 1983/84, earned his Ph.D. from the University of Belgrade in 1985, and received his M.A. from Oxford University in the same year. Professor Süli's research centers on numerical analysis of nonlinear partial differential equations with applications across multiple scientific domains. His work spans free-discontinuity problems and computational modeling of fracture; finite element methods; Navier-Stokes-Fokker-Planck systems; adaptive algorithms with a-posteriori error control; implicitly constituted material models; and discontinuous finite element methods. His research bridges theoretical mathematics with practical computational approaches for complex physical phenomena. Recent publications (2024-2025) demonstrate Süli's continued leadership in numerical analysis, with focus areas including fractional calculus, stochastic PDEs, and advanced finite element techniques. His work shows strong interdisciplinary connections between mathematical analysis, fluid dynamics, and materials science, addressing challenging problems in polymeric fluids, porous media, and capillary flow modeling. Professor Süli's distinguished career has been recognized with numerous prestigious honors: Invited Speaker at the International Congress of Mathematicians, Madrid (2006) Fellow of the Institute of Mathematics and its Applications (2007) Foreign Member of the Serbian National Academy of Sciences and Arts (2009) Fellow of the European Academy of Sciences (2010) IMA Service Award (2011) SIAM Fellow (2016) Member of the Academia Europaea (2020) London Mathematical Society Naylor Prize and Lectureship (2021) Fellow of the Royal Society (2021) As an educator, Süli has received the Oxford University Teaching Excellence Award (2009) and the Mathematical Institute Teaching Award (2013). He has supervised numerous PhD students and postdoctoral researchers throughout his career, though specific names aren't documented in the available materials. His research has been supported by various grants enabling work on computational methods for partial differential equations. Süli maintains active service to the mathematical community through editorial boards and professional organizations. Professor Süli is affiliated with the Numerical Analysis research group and the Oxford Centre for Nonlinear PDE at the Mathematical Institute. These research centers provide a collaborative environment for theoretical and applied work on partial differential equations. His research often involves interdisciplinary collaborations with physicists, engineers, and computational scientists to develop and analyze numerical methods for complex physical phenomena.

• Structural Health Monitoring
• Seismic Analysis
• Bayesian Calibration
• +۱۴ مورد دیگر

Gaetano Miraglia is a Fixed-term Assistant Professor in the Department of Structural, Building and Geotechnical Engineering (DISEG) at Politecnico di Torino, where he conducts research in structural health monitoring, seismic analysis, and computational modeling. He is a member of the Interdepartmental Center R3C – Responsible Risk Resilience Centre, contributing to interdisciplinary efforts in risk mitigation and infrastructure resilience. His work spans both theoretical and applied domains, with strong emphasis on heritage preservation and sustainable urban development. His research interests include Bayesian calibration of nonlinear models, hybrid simulation, peridynamics, masonry structures, and the integration of satellite interferometric (InSAR) data with in-situ measurements for structural monitoring. He applies advanced computational and machine learning techniques to improve the accuracy and reliability of structural assessments, particularly in historical and monumental buildings. His work supports UN Sustainable Development Goals 9, 11, and 13. His recent publications demonstrate a consistent focus on data fusion, digital twinning, domain adaptation, and real-time damage detection. He frequently collaborates with researchers such as Rosario Ceravolo and Erica Lenticchia, publishing in high-impact journals like Computer-Aided Civil and Infrastructure Engineering , Structures , and Scientific Reports , as well as at major conferences including EWSHM, SAHC, and EVACES. His research is applied in projects such as the monitoring of the Vicoforte Sanctuary and the development of the CAMELOT and HY-LEARN toolboxes. Research Projects: MONITORAGGIO VICOFORTE (2024–2026) – Member of Research Group CAMELOT – PoC Transition (2023–2024) – Member of Research Group HY-LEARN – Model Calibration via Hybrid Simulation and ML (2022–2024) – Scientific Manager (PNRR Mission 4) He teaches in various programs, including as a course collaborator in PhD, Master’s, and Bachelor’s level courses such as Earthquake Engineering , Structural Consolidation , and Seismic Risk of Cultural Heritage . He is also an inventor on national and international patents and software related to the CAMELOT toolbox, highlighting the translational impact of his research. He has no listed scientific awards or formal advisees in the provided text.

Sumsun Naherمشاهده پروفایل

مدرس ارشد

• Materials Processing
• Laser Engineering
• Metal Matrix Composites
• +۳ مورد دیگر

Dr. Sumsun Naher is a Senior Lecturer in the Department of Engineering at City, University of London , where she has worked since 2013. Previously, she served as Lecturer and Research Development Officer at Dublin City University (2006–2013) and as Scientific Officer at Bangladesh Council of Scientific & Industrial Research (1998–2000). Her academic career includes a Post Graduate Diploma in Academic Practice from City, University of London. PhD , School of Mechanical & Manufacturing Engineering, Dublin City University MSc , Materials & Metallurgical Engineering, Bangladesh University of Engineering and Technology BSc , Materials & Metallurgical Engineering, Bangladesh University of Engineering and Technology Her research focuses on semi-solid processing , laser processing , simulation & modelling of materials technologies , and materials characterisation . Recent work explores cellulose nanofiber-based water filters for antibiotic removal and phase change materials in geothermal energy systems. Key article trends reveal expertise in: Laser Surface Modification of metals and composites Advanced Casting Methodologies and semi-solid metal forming Nanoparticle Reinforcement in metal matrix composites Thermal Modelling for energy systems Sustainable Material Solutions in water treatment and energy Computational Materials Science via finite element analysis Naher has received the DCU Invent Commercialisation Award (2011) and holds fellowships from IMechE , Institute of Materials, Minerals & Mining , and Advance Higher Education Authority . She actively reviews for funding bodies and examines PhD theses internationally. As an organiser of the ESAFORM Conference and co-organiser of its Additive Manufacturing symposium since 2017, she contributes to academic leadership. Her professional roles include Board of Directors for the European Association of Materials Forming and participation in EU COST Action projects (Thixoforming, Thixosteel, Nanostructured Materials).

Pinon Hermida Victorمشاهده پروفایل

پژوهشگر

• Laser-Induced Breakdown Spectroscopy (LIBS)
• Optical Engineering
• Materials Analysis
• +۳ مورد دیگر

Dr. Pinon Hermida Victor is a Researcher at the Institute of Electronic Structure and Laser (IESL) under the Foundation for Research and Technology – Hellas (FORTH). He holds a PhD in Physics from the University of A Coruña (2011) and has conducted extensive research on Laser-Induced Breakdown Spectroscopy (LIBS), focusing on femtosecond lasers, double-pulse configurations, and applications in material analysis, archaeology, and environmental science. His career includes roles at Applied Photonics Ltd (UK) as Senior Applications Scientist (2014-2020) and postdoctoral fellowships at FORTH-IESL through the Marie Curie ATLAS program (2006-2008). Research interests span LIBS methodology development, optical fiber systems for high-power lasers, and software for spectral analysis. Notable contributions include portable LIBS instrument design and radiation-resistant optical components for nuclear facilities. Awards include the 2008 LIBS Contest and the 2011 Premio Extraordinario de Doctorado. Recent work focuses on applying LIBS to archaeological mollusc shell analysis for climate and environmental studies. He collaborates internationally on LIBS quantification challenges and instrument durability in harsh environments. Education: PhD in Physics (2011), University of A Coruña; Diploma in Physics (2001), University of Santiago de Compostela Key Roles: Senior Applications Scientist (Applied Photonics), Marie Curie Fellow (FORTH-IESL), Researcher (Laboratory of Industrial Applications of Lasers) Lab Affiliations: IESL-FORTH and University of A Coruña laser labs

Stefano Markidisمشاهده پروفایل

استاد

• High-Performance Computing
• Quantum Computing
• Computational Fluid Dynamics
• +۵ مورد دیگر

Stefano Markidis is a Professor of Computer Science at KTH Royal Institute of Technology, affiliated with the School of Electrical Engineering and Computer Science and the Digital Futures Faculty. He holds a Ph.D. from the University of Illinois at Urbana-Champaign and an MS from Politecnico di Torino. His research focuses on high-performance computing systems, including supercomputers and quantum computers, with expertise in plasma simulations, quantum algorithms, and scalable computational frameworks. Markidis leads the development of the Neko framework for high-fidelity computational fluid dynamics and the iPIC3D particle-in-cell code for plasma physics. He teaches courses such as Quantum Computing for Computer Scientists, High-Performance Computing, and Applied GPU Programming. His work addresses exascale computing challenges, including optimizing algorithms for GPUs, quantum systems, and distributed architectures. Key research interests include: Parallel Programming Models and HPC Frameworks Quantum Computing Applications in Scientific Simulations Physics-Informed Machine Learning Exascale System Optimization Turbulence Modeling and Plasma Dynamics His publications span over 100 articles in journals like Journal of Computational Physics and Scientific Reports , focusing on topics such as scalable CFD, quantum neural networks, and plasma simulation techniques. He has advised numerous students in these areas. Markidis collaborates with institutions like Los Alamos National Laboratory and RISE Research Institutes of Sweden through the Digital Futures initiative, aiming to solve societal challenges via digital technologies.

• Numerical Analysis
• Partial Differential Equations
• Optimization

Shaun Lui is Professor and Head of Mathematics at the University of Manitoba's Faculty of Science. His research develops advanced numerical methods for partial differential equations with applications in fluid dynamics and electromagnetics. Education includes B.Sc./M.Sc. from University of Toronto and Ph.D. from Caltech. Research focuses on spectral collocation methods in space-time, domain decomposition, and finite volume schemes. Recent work establishes spectral accuracy for Stokes flows and matrix singularity bounds. Supervises graduate students in numerical PDE projects.