جست‌وجوی استاد و پژوهشگر

Tony Stillfjordمشاهده پروفایل

دانشیار

• Numerical Analysis
• Partial Differential Equations
• Stochastic Optimization
• +۴ مورد دیگر

Tony Stillfjord is an Associate Professor at the Centre for Mathematical Sciences, Lund University, Sweden. He previously held postdoctoral positions at the Max Planck Institute for Dynamics of Complex Technical Systems and Chalmers/University of Gothenburg. Ph.D. and MSc in Numerical Analysis from Lund University Funded by WASP (Wallenberg AI, Autonomous Systems and Software Program) Research Interests : Numerical methods for partial differential equations, splitting schemes, stochastic optimization, and large-scale differential Riccati equations. His work focuses on developing low-rank approximations and robust optimization algorithms. Recent Publications highlight advancements in Lie/Strang splitting for operator-valued Riccati equations, stochastic descent methods, and GPU-accelerated splitting schemes. Software Contributions : Developed DREsplit (MATLAB package for differential Riccati equations) and BST20_CODE for stochastic optimization experiments. Contact : Office at MH:562E, Lund University. Email: tony.stillfjord@math.lth.se . URL: tonystillfjord.net

• Computational hydroacoustics
• Vibroacoustics
• Flow-induced noise and vibrations
• +۱۰ مورد دیگر

Mahmoud Karimi is a Senior Lecturer at the School of Mechanical and Mechatronic Engineering , University of Technology Sydney (UTS), leading the Vibroacoustics Research Group within the Centre for Audio, Acoustics and Vibration. He holds a PhD in Mechanical Engineering from UNSW with specialization in vibration and acoustics, and has conducted visiting research at University of Cambridge, Technical University of Munich, and INSA Lyon. His research focuses on computational hydroacoustics, vibroacoustics, and uncertainty quantification in noise/vibration problems. Academic Leadership : Editor-in-Chief of Acoustics Australia since 2025 Research Income : Attracted $6M in competitive grants ($2M as Chief Investigator) since 2017 Technical Expertise : Specializes in acoustic black hole structures, flow-induced vibration modeling, and leak detection in buried pipelines Scientific Awards : Recipient of ARC DECRA Fellowship (DE190101412) 2019-2022 Research Trends : His 91+ publications demonstrate expertise in hybrid acoustic modeling techniques, sustainable hempcrete development, and vibration energy harvesting solutions with applications in mining, rail systems, and water infrastructure. International Collaborations: University of Cambridge (UK), Technical University of Munich (Germany), INSA Lyon (France) Teaching Portfolio: Advanced numerical methods, dynamics & control, and computational modeling at UTS

Iason Papaioannouمشاهده پروفایل

استاد مدعو

• Uncertainty Quantification
• Structural Reliability
• Reliability-Based Optimization
• +۵ مورد دیگر

Iason Papaioannou is an Adjunct Professor in the area of Uncertainty Quantification at the Technical University of Munich (TUM), affiliated with the Engineering Risk Analysis Group. He holds a habilitation from the TUM School of Engineering and Design and has been tenured since 2021 as an Akademischer Rat. His academic journey includes a Ph.D. in Civil Engineering from TUM (2012), an M.Sc. in Computational Mechanics (2007), and a Diploma in Civil Engineering from the National Technical University of Athens (2005). His research focuses on uncertainty quantification , reliability assessment , and Bayesian updating of engineering systems. Key areas include probabilistic modeling, machine learning applications, spatial variability analysis, and geotechnical reliability. He has pioneered methods for system reliability analysis, adaptive subset simulation, and cross-entropy-based importance sampling. Teaching responsibilities include courses such as Stochastic Finite Element Methods, Structural Reliability Methods, and Elements of Machine Learning. His work integrates advanced computational techniques with practical engineering challenges, emphasizing high-dimensional uncertainty analysis and data-driven model updating.

Klemens Fellnerمشاهده پروفایل

استاد

• Partial Differential Equations
• Reaction-Diffusion Systems
• Kinetic Equations
• +۶ مورد دیگر

Klemens Fellner is a Professor of Mathematics/Computational Sciences and Group Leader of the Applied Analysis Group at the Institute of Mathematics and Scientific Computing, University of Graz. His research focuses on the analysis of partial differential equations and mathematical modeling across physics, chemistry, and biology. Research Interests: Prof. Fellner's work spans theoretical analysis of nonlinear PDEs (reaction-diffusion, kinetic, and non-local equations) using entropy/duality methods, with applications to: Biological systems (lipolysis, protein localization, stem-cell division) Physical processes (organic photovoltaics, semiconductor modeling) Collective behavior (swarming micro-organisms, aggregation dynamics) Interdisciplinary Mathematics-Arts collaborations Publication Trends: His recent articles (2018-2021) demonstrate strong focus on: Global existence and regularity for reaction-diffusion systems Convergence to equilibrium via entropy methods Drift-diffusion models in semiconductor physics Mathematical biology applications (prion dynamics, lipolysis) Novel approaches for non-local aggregation and hysteresis phenomena Research Leadership: Currently leads the Applied Analysis Group with members including postdocs and PhD students. Key projects: Doctoral School IGDK (International Graduate School) SFB Lipid Hydrolysis (Special Research Program) Mathematics and Arts collaborations Colibri research platform Supervises PhD candidate Reymart Lagunero studying generalized reaction-diffusion systems.

Kallol Settمشاهده پروفایل

دانشیار

• Risk and Reliability
• Civil Infrastructure
• Extreme Events
• +۵ مورد دیگر

Kallol Sett is an Associate Professor in the Department of Civil, Structural and Environmental Engineering at the University at Buffalo (SUNY), within the School of Engineering and Applied Sciences. His research focuses on risk and reliability analysis of civil infrastructure under extreme events, with expertise in uncertainty quantification, multi-hazard resilience, and geomechanics. He leads the Risk and Reliability Research Group, which develops computational tools integrating physics-based and data-driven modeling, stochastic calculus, and high-performance computing. Education includes a PhD from the University of California, Davis (2007), an MS from the University of Houston (2003), and a BE from Jadavpur University (1997). His work is funded by NASA, NSF, USDOT, NIST, and industry partners. Key research themes include probabilistic geotechnical site characterization, stochastic simulation of seismic ground motion, and life-cycle cost-benefit analysis of infrastructure systems. Advising includes mentoring over 10 PhD and MS students, with notable alumni now in academia and industry roles such as Assistant Professors at Embry-Riddle Aeronautical University and Tianjin University. His lab’s recent studies address real-time decision support systems for hurricane-impacted infrastructure, resilience deficit indices, and multi-hazard financial risk assessment of integrated infrastructure systems.

Caglar Oskayمشاهده پروفایل

استاد

• Multiscale Computational Modeling
• Composite Materials
• Structural Failure Analysis
• +۷ مورد دیگر

Caglar Oskay is the Cornelius Vanderbilt Professor of Engineering and Chair of the Department of Civil and Environmental Engineering at Vanderbilt University. He is also a Professor of Mechanical Engineering. His research focuses on multiscale computational modeling of material and structural systems under extreme conditions, with expertise in composite materials, failure mechanisms, and computational mechanics. Dr. Oskay earned his Ph.D. in Civil Engineering from Rensselaer Polytechnic Institute (2003) and has held academic roles there before joining Vanderbilt in 2006. He was honored as an ASME Fellow in 2017 and as a Chancellor Faculty Fellow in 2016. Key research areas include multiscale failure modeling, life prediction of heterogeneous materials, and computational methods for composites and multiphysics systems. His work integrates advanced simulation techniques with experimental validation, addressing challenges in infrastructure resilience, additive manufacturing defects, and quantum computing applications in engineering. Education: Ph.D., Civil Engineering, Rensselaer Polytechnic Institute (2003) M.S., Civil Engineering, Rensselaer Polytechnic Institute M.S., Applied Mathematics, Rensselaer Polytechnic Institute B.S., Civil Engineering, Middle East Technical University Recent research highlights include stochastic modeling of geotechnical infrastructure failures, quantum-enhanced finite element methods, and predictive analytics for additive manufacturing defects. He leads interdisciplinary efforts on backward erosion piping in flood protection systems and has secured grants for multiscale modeling of titanium alloys and composites. Awards: ASME Fellow (2017) Chancellor Faculty Fellow (2016) Advising and grants: Dr. Oskay’s grants include NSF-funded studies on backward erosion piping and quantum computing applications. His research group collaborates with industry partners on materials for aerospace and energy sectors, emphasizing computational tools for failure prediction and material design. His work bridges computational mechanics with practical engineering challenges, advancing methods for infrastructure resilience, advanced materials, and sustainable design through multiscale modeling innovations.

Brandon Karchewskiمشاهده پروفایل

استاد آموزشی

• Computational Geoscience
• Engineering Geology
• Natural Hazards
• +۲ مورد دیگر

Brandon Karchewski is an Associate Head (Undergraduate) and Teaching Professor in the Department of Earth, Energy and Environment at the University of Calgary. He earned his PhD in Civil Engineering from McMaster University and teaches courses including Engineering Geology, Computational Methods, and Natural Disasters. His research program focuses on: Computational methods in geophysics and geomechanics Geoscience education innovation Climate change impacts on frozen soils Inverse modeling applications Karchewski has pioneered virtual field experiences and developed open-source tools for modeling climate impacts on permafrost. His educational research examines metaphor use in geoscience communication and field pedagogy. Recent computational work includes Python-based permafrost modeling and stochastic inversion methods for biogeochemical transport. He leads the geophysics field school program emphasizing team-based learning. Award recognition includes: Geoscience Teaching Award (2019) Best Poster Award for teaching innovation research (2018) Team Teaching Excellence award (2016) Multiple teaching assistant awards

• Control Theory
• Applied Mathematics
• Computational Mechanics
• +۷ مورد دیگر

Goong Chen is a Professor at Texas A&M University (TAMU) within the College of Arts & Sciences. His research focuses on Control Theory, Applied Mathematics, and interdisciplinary applications in computational mechanics, fluid dynamics, and quantum systems. He holds a Ph.D. from the University of Wisconsin (1977) and a B.S. from National Tsing-Hua University (1972). His research interests span computational biomechanics, forensic modeling, nanofluidics, and mathematical physics. Recent work includes modal analysis of animal motion, crash mechanics of aircraft, and forensic reconstruction of disasters. He has contributed to theoretical advancements in PDEs, nonlinear dynamics, and quantum computing. Chen’s articles address cutting-edge topics like thermoelastic plates, Volterra equations, and DFIM systems. He has pioneered numerical methods for complex systems using OpenFOAM and finite element techniques. His computational models have been applied to real-world scenarios such as submarine implosions and chemical warfare forensics. No academic awards are explicitly listed, but his extensive publication record reflects significant contributions to applied mathematics and engineering. He leads research teams focused on interdisciplinary challenges in computational science and engineering.

Sonia Flissمشاهده پروفایل

استاد

• Wave Propagation
• Mathematical Analysis
• Numerical Analysis
• +۵ مورد دیگر

Sonia Fliss is a Full Professor at ENSTA Paris , affiliated with the Department of Applied Mathematics and the POEMS laboratory (UMR CNRS-INRIA-ENSTA) . She teaches applied mathematics courses on partial differential equations (PDEs) , finite element methods , and periodic homogenization to undergraduate and graduate students. Doctor in Applied Mathematics (2009) Authorized to supervise research (2019) Research Interests : Sonia Fliss specializes in the modeling and numerical analysis of wave propagation in periodic, quasi-periodic, and random media . Her work includes transparent boundary conditions , guided waves , and asymptotic methods for acoustic, electromagnetic, and elastic wave phenomena . Recent Publications highlight her contributions to the Half-Space Matching Method , edge states in honeycomb structures , and scattering problems in unbounded domains . Her numerical techniques address multi-scale waveguides and time-harmonic propagation . Laboratory : As a member of the POEMS team, she collaborates on interdisciplinary projects involving mathematical analysis , computational physics , and engineering applications in domains like defence, energy, and transport .

Yasmine Abdinمشاهده پروفایل

استادیار

• Polymer Matrix Composite Materials
• Composites Design and Manufacturing
• Structural Reliability
• +۹ مورد دیگر

Dr. Yasmine Abdin serves as an Assistant Professor in the Department of Materials Engineering within the Faculty of Applied Science at the University of British Columbia (UBC). Her research focuses on advancing polymer matrix composite materials through innovative digital simulation and probabilistic design methodologies. Her academic credentials include: B.Sc. from KU Leuven M.Sc. from KU Leuven Ph.D. from KU Leuven Dr. Abdin's research program centers on overcoming limitations in composite material durability through probabilistic design frameworks and multi-scale modeling. She integrates finite element analysis, machine learning, and Industry 4.0 technologies to predict structural reliability under stochastic service conditions, with emphasis on damage tolerance, manufacturing-process-structure relationships, and optimization of carbon fiber production from sustainable precursors like lignin and asphaltenes. Her recent publications (2023-2025) demonstrate strong focus on sustainable composite manufacturing, including carbon fiber production from renewable resources, 4D printing of shape memory polymers, flax fiber-reinforced composites, cellulose nanofibril modification, and fatigue behavior analysis. Key thematic trends include the convergence of digital twin technologies with composite manufacturing, sustainable precursor development, and the application of machine learning to enhance modeling efficiency in structural reliability prediction. Information regarding doctoral students, research grants, laboratory facilities, or scientific awards was not provided in available sources.

P.M. Mohiteمشاهده پروفایل

استاد

• Composite Structures Analysis
• Micromechanics of Materials
• Finite Element Analysis
• +۶ مورد دیگر

Dr. P.M. Mohite is a Professor at the Department of Aerospace Engineering , Indian Institute of Technology Kanpur , with a career spanning over two decades in composite materials research. He holds a PhD in Aerospace Engineering from IIT Kanpur (2007) and has been a Visiting Assistant Professor (2008-2009) and later Assistant , Associate , and Professor (2019-present) at IIT Kanpur. Research Interests include: Advanced composite structures analysis Micromechanics and damage modeling Finite element adaptive methods Metal plasticity and polymer composites Aerostructural optimization Key Publications focus on damage mechanics, structural optimization, and micromechanical characterization, with recent works on evolutionary algorithm-based composite design and boundary layer effects in laminates. Scientific Awards received: Best Student Award (B.E. Mechanical, 1998) AIAA Students Paper Contest Finalist (2006) Teaching Contributions include core courses like Composite Materials and Finite Element Methods , alongside advanced postgraduate topics in aerospace structural analysis. Advising has impacted 30+ M.Tech/Ph.D. students, including international collaborations with Université de Biskra (Algeria) and Ecole Centrale de Nantes (France).

Georgios Zourarisمشاهده پروفایل

استاد

• Numerical Analysis
• Finite Element Methods
• Stochastic Partial Differential Equations
• +۳ مورد دیگر

Georgios Zouraris is a Professor at the University of Crete, where he has maintained an active research profile since earning his Ph.D. from the same institution in 1995. His work is centered in the School of Science and Engineering, focusing on advanced computational mathematics with applications in physics and engineering. Education: Ph.D. in Mathematics, University of Crete, 1995 Professor Zouraris specializes in the development and rigorous analysis of numerical methods for partial differential equations. His research spans finite element and finite difference techniques for nonlinear Schrödinger equations, logarithmic heat equations, and stochastic PDEs with space-time white noise. Key contributions include error estimation frameworks for relaxation schemes, convergence analysis of Crank-Nicolson methods, and efficiency improvements for multilevel Monte Carlo simulations. His theoretical work consistently addresses singular nonlinearities and complex domain geometries, bridging mathematical rigor with computational practicality. Analysis of his 2020-2025 publications reveals a sustained focus on high-accuracy numerical schemes for challenging PDEs, particularly those involving logarithmic singularities and stochastic forcing. Recent work demonstrates increasing sophistication in handling noncylindrical domains and coupling strategies, with applications ranging from quantum systems to material science. The publications show consistent emphasis on provable convergence rates and computational efficiency. Information regarding student advising, research grants, and laboratory facilities is not documented in the available sources. His active publication record through 2025 indicates ongoing research leadership in computational mathematics.

Cláudia Reisمشاهده پروفایل

استادیار

• Coastal Engineering
• Structural Engineering
• Natural Hazards Engineering
• +۵ مورد دیگر

Cláudia Reis is an Assistant Professor at Lehigh University with a joint appointment in the Department of Civil & Environmental Engineering and the Institute for Cyber-Physical Infrastructure and Energy (I-CPIE) within the P.C. Rossin College of Engineering and Applied Science. She teaches courses in Coastal and Offshore Infrastructure Engineering, Structural Analysis I, and Finite Element Method in Structural Engineering. Her research focuses on fluids-solids interaction in coastal and offshore engineering, multi-risk management, and multi-scale/multi-physics modeling of critical infrastructure in multi-hazard regions. Dr. Reis leads the NHERI Lehigh Experimental Facility as a Co-Principal Investigator and chairs the Advanced Technology for Large Structural Systems (ATLSS) Engineering Research Center. She has secured grants including a PITA Grant ('Resiliency of Coastal Infrastructure') and a PEER Transportation Systems Research Program project ('Cascading Seismic and Tsunami Loads for the Design of Open Wharves'). Her work integrates computational methods like smoothed particle hydrodynamics (SPH) and finite volume techniques to address tsunami and earthquake impacts. She contributes to national/international committees such as NHERI and FIB, and serves on editorial boards and grant review panels. Dr. Reis' research emphasizes infrastructure resilience, cascading hazards, and exascale computing applications for natural hazard mitigation.

Fabio Nobileمشاهده پروفایل

استاد

• Scientific Computing
• Uncertainty Quantification
• Numerical Analysis
• +۵ مورد دیگر

Fabio Nobile is a Full Professor at the École Polytechnique Fédérale de Lausanne (EPFL) in the School of Basic Sciences (SB), Department of Mathematics (MATH), holding the CADMOS Chair in Scientific Computing and Uncertainty Quantification. He leads the CSQI (Chair of Scientific Computing and Uncertainty Quantification) group. His work focuses on numerical methods for partial differential equations (PDEs), uncertainty quantification, stochastic modeling, and computational fluid dynamics. He is involved in collaborative projects involving fluid-structure interaction, cardiac electro-mechanics, and energy systems. Professor Nobile has extensive teaching experience, including courses on advanced analysis, stochastic simulation, and numerical integration of stochastic differential equations. He supervises numerous PhD students and has contributed to over 200 peer-reviewed publications, covering topics such as low-rank approximation methods, multilevel Monte Carlo techniques, and optimal control under uncertainty. His research emphasizes interdisciplinary applications, including biomedical engineering (e.g., personalized cardiac simulations) and renewable energy (e.g., probabilistic load forecasting). He collaborates with industries and academic institutions globally, advancing computational methodologies for engineering and scientific challenges.

Günther Grünمشاهده پروفایل

استاد

• Stochastic Partial Differential Equ (SPDE)
• Free Boundary Problems
• Continuum Mechanics
• +۵ مورد دیگر

Prof. Dr. Günther Grün is a faculty member at the University of Erlangen-Nuremberg , specializing in Applied Mathematics . His work bridges rigorous mathematical analysis, numerical methods, and applications in continuum mechanics , fluid dynamics , and free boundary problems . He serves as Spokesperson for the DFG Research Training Group IntComSin (2022–2027), focusing on interfaces, complex structures, and singular limits in mathematical modeling and simulation. Education Diploma in Mathematics (1991), University of Bonn PhD in Mathematics (1994), University of Bonn Habilitation in Mathematics (2001), University of Bonn Research Interests center on degenerate parabolic equations (e.g., porous-medium and thin-film equations), stochastic SPDEs with multiplicative noise, diffuse interface models for two-phase flow with surfactants, and dimension-reduced models via singular limits. His work combines calculus of variations , homogenization , and Gamma-convergence for multi-scale analysis, alongside finite-element/finite-volume schemes for efficient simulations. Scientific Awards Marie Curie Research Fellowship (1996), Universita di Tor Vergata, Rome Advising Legacy includes mentoring doctoral candidates such as Dr. Fabian Klingbeil (Accenture), Dr. Jürgen Becker (Fraunhofer Institute), and Prof. Dr. Julian Fischer (IST Austria), who have pursued careers in academia, industry, and research institutions.