جست‌وجوی استاد و پژوهشگر

Pierre Haessigمشاهده پروفایل

پژوهشگر

• Energy Management
• Dynamic Optimization
• Stochastic Optimization
• +۳ مورد دیگر

Pierre Haessig is a researcher and teacher at CentraleSupélec's Rennes campus, part of the Automation Team within the Rennes Institute of Electronics and Telecommunications (IETR). His work focuses on optimal energy management of storage systems (batteries) integrated with renewable energy sources like wind and photovoltaic. Research addresses uncertainties in energy inputs, such as solar variability and load fluctuations, using stochastic optimization techniques. He teaches Automation and Electrical Engineering in engineering programs. Affiliations: CentraleSupélec, IETR (Rennes) Key Research Areas: Energy Management, Stochastic Optimization, Renewable Integration, Battery Aging Models His publications (36+) explore topics like microgrid optimization, Kalman filter-based battery state estimation, and the impact of uncertainties on energy systems. He has contributed to open-source benchmarks like Solar Home 2020 and collaborated on projects involving hardware-in-the-loop testing for power electronics. His research emphasizes real-world applications in resilient energy systems and control strategies. Notable contributions include developing convex models for battery aging and advancing methods for anticipative/non-anticipative microgrid sizing. His work bridges theoretical optimization with practical implementations in energy storage and renewable integration.

• Computational Science
• Numerical Analysis
• Domain Decomposition Methods
• +۷ مورد دیگر

Victorita Dolean Maini is a Visiting Professor in the Department of Mathematics and Statistics at the University of Strathclyde, Faculty of Science. She is actively engaged in research and supervision, with a focus on computational science and numerical methods for partial differential equations. Her work bridges applied mathematics, high-performance computing, and interdisciplinary applications in geophysics, biomedical engineering, and pharmaceutical modeling. University: University of Strathclyde School: Faculty of Science Department: Mathematics and Statistics Academic Rank: Visiting Professor Her research interests center on computational science, particularly in developing mathematical models and algorithms for complex physical systems governed by partial differential equations. She specializes in domain decomposition methods, iterative solvers, and high-performance computing, with recent extensions into scientific machine learning and physics-informed neural networks. Her work emphasizes rigorous analysis and validation of numerical results. The most recent publications highlight a strong trend in robust and scalable numerical methods for multiscale and multiphysics problems. Topics include domain decomposition with GenEO coarse spaces, optimized transmission conditions for diffusion, wave propagation in anisotropic media, and computational epidemiology. These works span disciplines such as applied mathematics, computational physics, geophysics, and biomedical modeling, reflecting a highly interdisciplinary approach. There is a clear emphasis on industrial and real-world applications, including seismic imaging, crystallization processes, and hemodynamic simulations. Scientific awards include: Fellow (awarded 7 September 2020) Prix Bull-Joseph Fourier 2015 (awarded 12 April 2016) She has been a co-investigator and principal investigator on multiple research grants, including projects like PharmaCrystNet, Fast solvers for frequency domain wave-scattering, and Blood flow dynamics in pulmonary hypertension. She actively supervises PhD students and collaborates internationally. She has organized key seminars and workshops, particularly in scientific machine learning and physics-informed learning, contributing significantly to academic community building. She leads and participates in research teams focused on computational modeling, numerical linear algebra, and interdisciplinary applications. Her group collaborates with institutions in physics, engineering, and life sciences, leveraging high-performance computing for large-scale simulations. She is also involved in promoting diversity through initiatives like the Women in Data Science and Mathematics Seminar Series.

Antonio Huertaمشاهده پروفایل

استاد

• Numerical Methods
• Mechanics
• Applied Mathematics
• +۴ مورد دیگر

Antonio Huerta is a Professor of Applied Mathematics at the Universitat Politècnica de Catalunya (UPC) and Director of ICREA. He leads the Laboratori de Càlcul Numèric (LaCàN) , focusing on numerical methods for scientific and engineering problems governed by mechanics and interdisciplinary principles. His research spans applied mathematics, computational science, and fluid dynamics. Education : Ph.D. from Northwestern University (1987), preceded by studies at the Escuela Técnica Superior de Ingeniería de Caminos, Canales y Puertos de Barcelona (1983). His work emphasizes numerical methods , particularly hybridizable discontinuous Galerkin (HDG), finite volume methods, and proper generalized decomposition (PGD), applied to problems in incompressible/compressible flow simulation , fluid-structure interaction , and magneto-mechanical coupling . Recent projects include data-driven design for automotive battery optimization ( GREEN ) and MATLAB-based open-source tools. Key collaborations include co-authoring the textbook Finite Element Methods for Flow Problems with Jean Donea and developing error estimation frameworks for finite element solutions. His publications highlight interdisciplinary applications in mechanics, mathematics, and computer science.

Shirsendu Sikdarمشاهده پروفایل

مدرس

• Structural Health Monitoring
• Nondestructive Evaluation
• Cyber-physical Systems
• +۴ مورد دیگر

Dr. Shirsendu Sikdar (PhD, MRAeS, FHEA) is a Lecturer in Mechanical Engineering at the School of Computing and Engineering, University of Huddersfield, UK. He holds a PhD in Structural Health Monitoring from IIT Bombay and has held research positions at Cardiff University, Ghent University, and Polish Academy of Sciences. Education: PhD (IIT Bombay), MEng (IIT Kharagpur), BEng (Jadavpur University) Research Interests: • Structural Health Monitoring (SHM) for aerospace, automotive, and wind-energy systems using guided waves and acoustic emission. • Cyber-physical systems and digital twins for real-time structural simulation. • NetZero technologies for sustainable monitoring and renewable energy systems. • Active vibration and noise control under variable operational conditions. • Computational modeling of smart materials and composites. Publications & Expertise: With 50+ peer-reviewed publications and an h-index of 18, his work focuses on SHM strategies for composite structures, smart sensing systems, and reduced-order modeling. He has contributed to journals like Scientific Reports and Smart Materials and Structures . Scientific Awards & Roles: Recipient of Marie Curie and EPSRC fellowships, he serves as Associate Editor for ASME Journal of Nondestructive Evaluation and Lead Guest Editor for Buildings and Signals journals. Collaborations & Grants: Active in cross-disciplinary collaborations across Europe, he has secured £0.5M+ in research grants and reviewed for over 20 journals including Nature and IEEE Transactions .

Sebastian Schöpsمشاهده پروفایل

دانشیار

• Computational Electromagnetics
• Coupled Multiphysical Simulations
• High-Performance Computing
• +۷ مورد دیگر

Prof. Sebastian Schöps is an Associate Professor in the Department of Electrical Engineering and Information Technology at Technische Universität Darmstadt. He leads the Computational Engineering Group, focusing on coupled multiphysical simulations and high-performance computing. His work bridges computational electromagnetics with advanced numerical methods like isogeometric analysis and reduced-order modeling. Education: Joint PhD in Physics (KU Leuven, Belgium) and Mathematics (University of Wuppertal) MSc and BSc in Business Mathematics (University of Wuppertal) Research Interests: Coupled systems involving electromagnetism, thermodynamics, and structural mechanics High-performance parallel algorithms for industrial-scale simulations Uncertainty quantification in engineered systems Optimization of electric machines using isogeometric analysis His work frequently involves developing novel finite element formulations and collaborating with CERN on accelerator magnet simulations. Publications Trends: Recent work emphasizes machine learning integration with physics-based models, optimization under uncertainty, and scalable simulation techniques for superconducting devices. Key applications include electric machine design, particle accelerator magnets, and medical device modeling. Labs & Projects: Leads the PASIROM project (Parallel Simulation and Robust Optimization of Electro-Mechanical Energy Converters), and contributes to CERN's quench protection system research. Active in open-source tool development for multiphysics simulation.

Erion Gjonajمشاهده پروفایل

مدرس ارشد

• Multiphysics Simulation
• Fluid Dynamics
• Thermal Engineering
• +۲ مورد دیگر

PD Dr. rer. nat. Erion Gjonaj is affiliated with the Department of Technical Mechanics and Fluid Dynamics (TEMF) at Technische Universität Darmstadt . His research focuses on coupled problems in engineering, particularly in multiphysics simulation, fluid dynamics, and thermal engineering. He holds the academic rank of Senior Lecturer. Contact details include: Office: S2|17 230, Schloßgartenstr. 8, 64289 Darmstadt Phone: +49 6151 16-24024 Fax: +49 6151 16-25249 His work addresses interdisciplinary challenges in technical mechanics, with an emphasis on coupled phenomena such as fluid-structure interaction and thermomechanical systems. No specific grants, awards, or publications are detailed in the provided text. Further information can be found via institutional links.

Alfred Akisanyaمشاهده پروفایل

استاد

• Solid Mechanics
• Fracture Mechanics
• Structural Integrity
• +۱۲ مورد دیگر

Professor Alfred Akisanya is a Personal Chair in the School of Engineering at the University of Aberdeen, where he conducts research and teaches in solid mechanics, structural integrity, and materials engineering. He holds a PhD from the University of Cambridge and is a Chartered Mechanical Engineer and Fellow of the Institution of Mechanical Engineers (IMechE). His research is highly applied, focusing on oil and gas well integrity, corrosion, and mechanical behavior of materials under extreme conditions. Education: BSc (Honours) Mechanical Engineering, University of Ibadan, Nigeria (1985) MSc Mechanical Engineering, University of Ibadan, Nigeria (1987) PhD Solid Mechanics, University of Cambridge, UK (1992) His research interests include micromechanics, fracture of bonded joints, structural integrity, corrosion, mechanics of powder compaction, and deformation of energy-absorbing structures. He has led and participated in numerous funded projects with industry partners such as Shell, Chevron, Total, and PTDF. His recent work explores chemo-thermo-poromechanical modeling, pipeline integrity, and microbiologically influenced corrosion. The trends in his recent publications indicate a strong focus on offshore infrastructure longevity, corrosion mechanisms in marine environments, geomechanics of reservoir rocks, and advanced modeling techniques for structural reliability. His work integrates experimental, computational, and field-relevant approaches to solve industrial challenges in energy and materials sectors. Scientific Awards and Recognitions: Fellow of the Institution of Mechanical Engineers (FIMechE) Chartered Mechanical Engineer (CEng) He has served as an external PhD examiner for leading universities including Cambridge, Oxford, and NTU Singapore, and is an Associate Editor for the International Journal of Mechanical Engineering Education . He has supervised multiple KTP and industry-funded projects, demonstrating strong academic-industry collaboration. He also contributes as a referee for top journals and grant proposals for EPSRC. Professor Akisanya is actively involved in teaching, delivering courses in stress analysis and solids and structures. He is currently accepting PhD students and continues to lead cutting-edge research in mechanical and petroleum engineering domains. His laboratory and research group collaborate with institutions and companies worldwide, focusing on real-world applications in energy and infrastructure.

• Electromagnetic Fields
• Quantum Transport
• Nanoelectronics
• +۵ مورد دیگر

Davide Mencarelli is a Researcher at the Department of Information Engineering (DII) of the University of Ancona and Marche Polytechnic (UNIVPM), Italy. His research focuses on nanoelectronics, quantum transport phenomena, and advanced materials for energy harvesting and optoelectronics. He is affiliated with the Faculty of Engineering and contributes to interdisciplinary projects involving metamaterials, graphene-based devices, and computational materials science. His work spans experimental validation, theoretical modeling (e.g., density functional theory), and device design. Key areas include geometric diodes for THz rectennas, nanoscale ferroelectrics, and biosensors leveraging graphene field-effect transistors (FETs). He collaborates on projects funded by EU initiatives and has developed novel techniques for microwave energy harvesting and nanoscale characterization using inverted scanning microwave microscopy. Recent trends in his publications emphasize quantum effects in nanomaterials, tunable optical properties of 2D materials, and multiphysics modeling of nanoelectronic components. His research bridges fundamental physics and applied engineering, addressing challenges in renewable energy systems, biomedical diagnostics, and high-frequency electronics.

Yuan Tianمشاهده پروفایل

مدرس ارشد

• Thermal Energy Storage
• Phase Change Materials (PCM)
• Energy-Efficient Buildings
• +۱۲ مورد دیگر

Dr. Yuan Tian is a VC2020 Senior Lecturer at De Montfort University (DMU) within the School of Engineering and Sustainable Development, Faculty of Computing, Engineering and Media. He is affiliated with the Institute of Energy and Sustainable Development (IESD), where he conducts research in thermal energy systems and sustainable engineering. Current Position: VC2020 Senior Lecturer, De Montfort University (2018–present) Previous Roles: Lecturer at Aston University (2017–2018), Diamond Jubilee Lecturer at University of Hertfordshire (2013–2017), Research Associate and PhD Student at University of Warwick (2008–2013) Dr. Tian holds a PhD from the University of Warwick, a PgCert in Teaching in UK Higher Education from the University of Hertfordshire, and a BEng (Distinction) from Xi’an Jiaotong University (XJTU). His research focuses on thermal energy storage , phase change materials (PCM) , energy-efficient buildings , waste heat recovery , and battery thermal management . He employs computational fluid dynamics (CFD) and experimental methods to enhance heat transfer in porous media such as metal foams. His work bridges fundamental thermal science with practical applications in renewable energy and smart grids. The 15 most recent publications reflect a consistent focus on thermal performance in energy storage systems, particularly in PCMs and battery thermal management. His research spans experimental, numerical, and review studies, published in high-impact journals like Applied Energy and International Journal of Heat and Mass Transfer . Key themes include heat transfer enhancement, multiphysics modeling, and system-level optimization. EPSRC PhD Scholarship (2008–2012) Henry Lester Scholarship (2012) Outstanding PhD Completion Award, University of Warwick (2012) Great Britain–China Scholarship (2012) Chinese Government Award for Outstanding Self-financed Students Abroad (2012) Most Downloaded Article of the Year, Applied Energy (2014) Dr. Tian has been actively involved in research funding and peer review, serving in the EPSRC Peer Review College and ranked among the Top 5% Grants Reviewers (2017–18). He regularly reviews for over 85 international journals and has served on the Science Board of the UK Energy Storage Research Hub and the IEA Energy Storage Experts Panel. He led the successful accreditation of DMU's Mechanical and Mechatronics Engineering programs (2018–19). He is affiliated with the Institute of Energy and Sustainable Development (IESD) at DMU, a leading research center in sustainable energy technologies. His work includes consultancy with the Building Research Establishment (BRE) on fire spreading systems and ongoing collaborations with international institutions.

Rustom B. Bhiladvalaمشاهده پروفایل

دانشیار

• Nanoscale Materials
• Mechanics & Transport
• Fluid and Biomedical Sensor Development
• +۶ مورد دیگر

Rustom B. Bhiladvala is an Associate Professor in the Department of Mechanical Engineering at the University of Victoria. His expertise spans nanoscale materials, biomedical sensor development, and sustainable energy solutions. He holds degrees from IIT Kharagpur, the University of Iowa, and Yale University, and is a licensed Professional Engineer (P.Eng). Education: BTech (IIT Kharagpur), MS (University of Iowa), PhD (Yale) Affiliations: Faculty of Engineering, Mechanical Engineering Department, PRIMED Lab His research focuses on nanoresonators for early cancer detection, guard-heated thermal sensors for wind turbine optimization, and scalable nanostructure fabrication. Key projects include vibrating nanowire mass sensors and low-cost solar cell improvements. His work bridges fluid mechanics, materials science, and biomedical engineering. Notable contributions include developing field-directed nanowire assembly techniques and improving turbulent flow measurement accuracy. He teaches courses on energy systems and fluid mechanics at both undergraduate and graduate levels.

Shanelle Fosterمشاهده پروفایل

دانشیار

• Electromechanical Energy Conversion
• Manufacturability of Electric Machines
• Reliability Analysis
• +۴ مورد دیگر

Shanelle Foster is an Associate Professor in the Department of Electrical and Computer Engineering at Michigan State University's College of Engineering. Her research focuses on developing sustainable electromechanical energy conversion technologies, emphasizing manufacturability, reliability, and control of linear and rotating electrical machines. She leads efforts to integrate advanced materials and additive manufacturing techniques to enhance electric machine efficiency and cost-effectiveness. Education: Ph.D. Electrical Engineering, Michigan State University (2013) M.S. Electrical Engineering, Michigan State University (1998) B.S. Electrical Engineering, Michigan State University (1996) Research Interests: Electromechanical systems and energy conversion Segmented stator/rotor design optimization Additive manufacturing of soft magnetic materials Condition monitoring and fault diagnosis High-performance control algorithms for electric drives Awards & Recognition: NSF CAREER Award (2021) Excellence in Diversity Award (2022) IEEE Women in Engineering Travel Grant (2017) Office of Naval Research Concept Challenge Finalist (2017) Service & Leadership: Associate Editor, IEEE Transactions on Energy Conversion (2021-present) Logistics Co-Chair, 2023 IEEE Energy Conversion Congress & Expo Former Secretary, IEEE Southeastern Michigan Section (2021-2022) Her work bridges fundamental research with practical applications, particularly in advancing additive manufacturing for electric machines and promoting inclusive engineering education through her NSF-funded CAREER project.

Iryna Rybakمشاهده پروفایل

مدرس ارشد

• Multiscale Methods
• Mathematical Modelling
• Numerical Algorithms
• +۳ مورد دیگر

Iryna Rybak is a Senior Lecturer and Principal Investigator at the University of Stuttgart's Institute of Applied Analysis and Numerical Simulation. Her research focuses on mathematical modeling, numerical methods, and multiscale analysis for coupled free-flow and porous medium systems. She coordinates the German side of the ANR-DFG project FLUPOR and leads Project A03 in the Collaborative Research Centre (SFB) 1313 on interface-driven multi-field processes in porous media. Academic Roles: Research Assistant, Principal Investigator Institution: University of Stuttgart Key Projects: FLUPOR (ANR-DFG), SFB 1313 (DFG) Research Interests: Multiscale methods, averaging theories, Stokes-Darcy coupling, numerical algorithms for multiphysics problems, and model validation using neural networks. Her work addresses interface conditions, porous media flow, and sediment transport in three-phase systems. Publications emphasize fluid-porous interface modeling, preconditioning techniques, and sensitivity analysis. She has advised over 15 PhD/Master students on topics like preconditioners for coupled systems and surrogate-assisted validation frameworks. Teaching includes advanced numerical methods, mathematical programming, and partial differential equations at both undergraduate and graduate levels. Grant Roles: Principal Investigator in FLUPOR and SFB 1313; coordinator of DFG-funded projects on interface modeling (2012–2025).

Selda Oterkusمشاهده پروفایل

استاد

• Peridynamics
• Fluid-Structure Interactions
• Fracture Mechanics
• +۷ مورد دیگر

Prof. Selda Oterkus is a Professor (Chair) at the University of Strathclyde's Department of Naval Architecture, Ocean and Marine Engineering, and co-director of the PeriDynamics Research Centre (PDRC). She holds a PhD in Mechanical Engineering from the University of Arizona. Her research focuses on multi-physics modeling, including damage prediction in materials and structures under various conditions. Key areas include fluid-structure interactions, offshore renewable energy systems, and composite materials. Her work is supported by organizations like BEIS, Innovate UK, and industry partners such as Babcock and TWI. Research interests span peridynamics, fracture mechanics, computational fluid dynamics, and desalination technologies. She has collaborated internationally, serving as a visiting professor at Stanford University, University of Padova, and Otto von Guericke University. She is an editor for journals like Computational Materials Science and chairs the ASME UK Section. Her projects include advanced manufacturing techniques, floating wind/solar energy devices, and corrosion damage analysis. She contributes to UN Sustainable Development Goals related to affordable clean energy and climate action. Supervised 16 students and led 32 projects, including consultancy work with Ferguson Marine. Active in workshops and conferences on sustainable materials and marine engineering. Labs/Teams: Co-directs the PeriDynamics Research Centre (PDRC), leading interdisciplinary research in computational mechanics and materials science.

Tomasz Plewaمشاهده پروفایل

استاد

• Computational Astrophysics
• Scientific Computing
• fluid dynamics
• +۲۲ مورد دیگر

Dr. Tomasz Plewa is a Professor at Florida State University's Department of Scientific Computing, with extensive expertise in computational astrophysics and high-performance computing. His research focuses on theoretical and computational modeling of complex astrophysical phenomena, particularly supernova explosions, fluid dynamics, and plasma physics. His research interests span: Fundamental astrophysical processes: stellar evolution, core collapse, and thermonuclear supernovae Advanced computational methods: adaptive mesh refinement (AMR), machine learning for subgrid modeling, and verification & validation Multiphysics simulations: magnetohydrodynamics, turbulent combustion, reactive flows, and high-energy density physics High-performance computing applications: extreme-scale simulations, data analytics, and scientific software development Analysis of his 15 most recent publications reveals strong trends in: Supernova explosion mechanisms (core collapse, detonation physics, gravitational confinement) Hydrodynamic instabilities in astrophysical contexts (Rayleigh-Taylor, shock-cylinder interactions) Advanced numerical methods for relativistic and reactive flows Laboratory astrophysics experiments validating cosmic phenomena High-performance computing frameworks for terascale simulations Dr. Plewa leads the Hydro Group research team and participates in the High-Energy Density Laboratory Astrophysics (HEDLA) consortium. He supervises students through Florida State University's Undergraduate Research Opportunity Program (UROP) and maintains active collaborations on international astrophysics projects.

Pejman Tahmasebiمشاهده پروفایل

دانشیار

• Geomechanics
• Subsurface Systems
• Machine Learning
• +۱۲ مورد دیگر

Dr. Pejman Tahmasebi is an Associate Professor in the Department of Geophysics at the Colorado School of Mines, where he leads research in geomechanics, subsurface systems, and machine learning applications. He is affiliated with the G4 Lab (tahmasebi.mines.edu), focusing on advanced computational modeling and data-driven methods for earth sciences. His research interests span geomechanics (from granular particles to large-scale systems and THMC processes), subsurface systems (energy, water, storage) using computational modeling and multiple-point statistics, machine learning with physics-guided AI frameworks, and fluid flow in porous media . His work integrates statistical, multiscale, and data analytics techniques to solve complex geoscientific challenges. Dr. Tahmasebi has received several prestigious awards, including international recognitions from IAMG and EAGE as a rising star, regional SPE awards in Reservoir Description and Data Analytics, and the Elsevier Best Paper Award. He serves on the editorial boards of Water Resources Research , Computers & Geosciences , and Fluids , handling submissions in machine learning and subsurface modeling. He has conducted postdoctoral research at Stanford University and the University of Texas at Austin, and worked at Caltech in the Department of Mechanical and Civil Engineering. His educational background includes a Ph.D. from a joint program supervised by Prof. Muhammad Sahimi at the University of Southern California, focusing on data analytics for porous media modeling. Dr. Tahmasebi advises graduate students and leads the G4 Lab, which specializes in developing novel statistical and multiscale techniques for geoscientific applications. His lab actively contributes to advancing physics-informed AI and uncertainty quantification in subsurface systems.