Lazaro J. Perez is an Assistant Professor in the School of Civil and Construction Engineering at Oregon State University, part of the College of Engineering. His research focuses on hydrological and biogeochemical processes in subsurface porous media, particularly quantifying incomplete mixing effects on chemical reactions and contaminant transport. He integrates experimental and numerical methods to address groundwater remediation, aquifer management, and bioremediation challenges. Education: Ph.D., Civil and Environmental Engineering, Polytechnic University of Catalonia (2019) M.S., Engineering Geology and Geologic Resources, University of Oviedo (2015) B.S., Geology, University of Oviedo (2013) Research interests include bacterial transport dynamics, biofilm impacts on fluid flow, and multiscale modeling of reactive transport. His work spans pore-to-field scales, emphasizing practical applications like arsenic removal using metal-organic frameworks and climate change effects on water systems. Key contributions include advancements in solute transport prediction via machine learning, upscaling bacterial migration in porous media, and understanding biofilm-induced flow heterogeneities. Current projects involve climate change impacts on mountain hydrology and innovative remediation strategies for contaminated waters.
Prof. François Desbouvries is a Full Professor at Telecom SudParis and Director of the SAMOVAR lab, part of the Institut Polytechnique de Paris. He holds degrees from Telecom Paris and a HDR from Marne la Vallée University. His expertise spans statistical signal processing, Bayesian statistics, and data science, with a focus on hidden data models and Monte Carlo methods. He has held leadership roles including heading the TIPIC team and serving as an IEEE Senior Member since 2007. His research contributions include over 150 publications in top journals and conferences, with recent advancements in Bayesian filtering and machine learning integration. He actively contributes to academic governance through roles in ANR committees and the GdR ISIS network. Education: Engineer Degree in Telecommunications (1987, Telecom Paris), Ph.D. in Signal and Image Processing (1991, Telecom Paris), and Habilitation à Diriger des Recherches (HDR, 2001, Marne la Vallée University). Research interests include sequential Monte Carlo methods, variational inference, and applications in signal processing. Recent work explores Bayesian classification and neural network modeling comparisons. His articles emphasize algorithmic efficiency and theoretical rigor in dynamic systems. Leadership: SAMOVAR lab director (2020–present), former head of TIPIC team (2011–2019), and member of national scientific committees like ANR and GdR ISIS. Grants secured through collaborative projects in signal/image processing and data science. Labs/Teams: SAMOVAR lab (specializing in ICT) and former leadership of the TIPIC team, fostering interdisciplinary research in signal processing and communication systems.
Chantal Taconet is a Lecturer at Telecom SudParis, part of the SAMOVAR research institute. Her work focuses on middleware systems for the Internet of Things (IoT), context-aware computing, energy efficiency, and blockchain applications in supply chains. She has co-authored over 20 peer-reviewed articles and conference papers since 2008, addressing IoT middleware design, QoC management, and middleware for cloud-IoT integration. Her research spans IoT middleware architectures (e.g., IoTVar framework), energy-efficient IoT protocols, and blockchain-based supply chain traceability. She contributed to the ANR INCOME project on multi-scale context management, emphasizing model-driven engineering and distributed system frameworks. Taconet has organized workshops like M4IoT and co-edited special issues on IoT middleware in Annals of Telecommunications . Key technical areas include semantic-based discovery services, fog computing integration for sensor networks, and trust models for IoT systems. Her work bridges theoretical middleware design with practical implementations for IoT applications.
Prof. Dr. Britta Nestler serves as a Research Unit Chair at the Institute of Nanotechnology (INT) within the Karlsruhe Institute of Technology (KIT), Germany. Leading the Microstructure Simulations research group (INT-MSS), she focuses on computational modeling of mechanical and microstructural properties in materials, with significant contributions to phase-field methodologies for microstructure evolution and materials design. Her research spans computational materials science, phase-field modeling, and multiphysics simulations for energy storage systems. Key interests include chemo-mechanical coupling in multiphase systems, solid-state dewetting phenomena, battery electrode optimization, and microstructure-property relationships in polycrystalline materials. She integrates machine learning and data management frameworks to advance virtual materials design, particularly for post-lithium battery technologies. Recent publications reveal a strong emphasis on phase-field applications for energy materials, with 15+ 2025 articles addressing battery electrode design, structural optimization of porous materials, and multiphysics coupling in electro-chemo-mechanical systems. Her work bridges fundamental thermodynamics with industrial applications, notably in the POLiS Cluster of Excellence for post-lithium storage. Prof. Nestler actively shapes the field through leadership in the GAMM Workshop on phase-field modeling and the Materials/Microstructure Modeling conference. As part of KIT's Institute of Nanotechnology, her INT-MSS group collaborates on virtual materials design initiatives within the MaTeLiS Focus Field and NFDI4Ing research data infrastructure, driving digitalization in engineering sciences.
Prof. Alberto Salvadori is an Associate Professor at the University of Brescia (Italy) and Research Assistant Professor at the University of Notre Dame (USA). He founded and leads the Multiscale Mechanics and Multiphysics of Materials Lab, focusing on computational modeling of complex physical phenomena across multiple scales. He holds a Ph.D. in Structural Engineering from Politecnico di Milano (2000). His research spans: Fracture mechanics and crack propagation in embrittled materials Multiphysics modeling of Li-ion batteries and energy storage systems Mechanobiology of cell motility and protein relocation Machine learning applications in materials science Granular material behavior and powder compaction His publications show strong focus on: Advanced battery technologies and solid-state electrolytes Multiscale computational methods for materials design Biomechanics of cellular processes Innovative fracture propagation algorithms Awards include: Marie Curie Fellowship (2013) from European Union Research funding from: EU Marie-Curie Sklodowska actions University of Notre Dame Italian Ministry of Education Private industry partners He leads the Multiscale Mechanics and Multiphysics of Materials Lab at University of Brescia, collaborating with Cornell Fracture Group and Patient-based Medicine Lab.
Sidsel Johansen is a PhD Fellow at the Department of Chemistry and Bioscience , Aalborg University , within the Faculty of Engineering and Science. Her research focuses on disordered materials, specifically oxide glasses, with an emphasis on structural prediction and mechanical behavior. University: Aalborg University School: Faculty of Engineering and Science Department: Department of Chemistry and Bioscience Academic Rank: Research Fellow Email: sidselmj@bio.aau.dk Research Interests Johansen's work intersects materials science , glass structure , and molecular mechanics . She employs machine learning to predict glass properties and investigates nanoscale deformation using in situ X-ray diffraction . Her studies cover: Oxide glass composition and mechanical stability Aluminosilicate network modeling Indentation-induced fracture behavior Shear flow mechanisms in disordered systems Multi-scale structural characterization Data-driven material design frameworks Projects Active in the NewGLASS: New Horizons in Glass Structure Prediction and Mechanics project (2022–2027), collaborating with international researchers on structural-mechanical correlations in glasses. Publications Recent contributions include: 2025: Machine learning study on aluminosilicate stiffness and toughness 2024: In situ X-ray nano diffraction analysis of oxide glass deformation
Chiara Gastaldi is an Associate Professor at the Department of Mechanical and Aerospace Engineering (DIMEAS) at the Polytechnic University of Turin, specializing in mechanical design and machine construction. Her academic career spans multiple teaching roles across bachelor's, master's, and doctoral programs, with particular focus on sustainable design, mechanical engineering, and computational methods. She serves on the College of Mechanical, Aerospace, and Automotive Engineering and the College of Biomedical Engineering, contributing to curriculum development and academic governance. Dr. Gastaldi's research centers on bearings, friction, multiphysics modeling, and numerical modeling, with emphasis on sustainable and circular design approaches. Her work bridges traditional mechanical engineering with modern computational techniques, focusing on practical applications in aerospace engineering, computational engineering, fluid mechanics, and sustainable design. She leads the ISED (Industrial Systems Engineering and Design) research group, driving innovation in model-based systems engineering applied to sustainable product development. Her recent publications reveal a strong trend toward integrating sustainability principles into mechanical design, particularly through life cycle assessment methodologies applied to human-powered vehicles and circular design strategies. The research demonstrates growing interest in lattice metamaterials, friction modeling, and computational approaches to mechanical design optimization, with applications ranging from turbine blades to hydrogen storage systems. ASME Yetep Award (2016) ASME Yetep Award (2019) Dr. Gastaldi actively supervises multiple PhD students working on sustainable mechanical design, lattice metamaterials, and circular economy approaches. Her research portfolio includes significant projects funded by competitive calls and commercial contracts, such as PRIME for predictive maintenance, mechanical design of metal scrap crushing machines, CO2 footprint assessment of vehicle aftermarkets, and dynamic design of turbine blades with friction contacts for renewable energy applications. She also serves as an Associate Editor for the PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS. PART C, JOURNAL OF MECHANICAL ENGINEERING SCIENCE and participates in scientific committees including the ASME Technical Committee on Sound and Vibration and the International Committee on Joint Mechanics. Through the ISED research group, Dr. Gastaldi leads collaborative efforts in industrial systems engineering and design, with particular emphasis on sustainable and circular approaches to mechanical product development. Her team works closely with industry partners on practical applications of advanced mechanical design principles, while also mentoring the next generation of engineers through student teams like Policumbent, which focuses on human-powered vehicle design.
Saeideh Saeidi is a Researcher at the Institute of Biomechanics, Graz University of Technology, Austria, and a doctoral candidate in Biomedical Engineering at Amirkabir University of Technology, Iran. She has a strong academic background in biomechanics, with a B.Sc. and M.Sc. in Biomedical Engineering-Biomechanics from Isfahan University and Amirkabir University of Technology, respectively. PhD Biomedical Engineering-Biomechanics (Amirkabir University of Technology, since 9/17) M.Sc. Biomedical Engineering-Biomechanics (Amirkabir University of Technology, 9/14–10/16) B.Sc. Biomedical Engineering-Biomechanics (Isfahan University, 9/09–9/13) Her research focuses on biomechanics, particularly finite element analysis of musculoskeletal systems, including the knee joint and proximal femur. Her work integrates computational modeling with tissue mechanics to study injury mechanisms and inform medical device design. Her 2023 publication in Scientific Reports on brain white matter modeling highlights her expertise in multiscale computational approaches and histology-informed simulations. She has also contributed to finite element studies on hip fractures and knee biomechanics during her academic training. Ernst Mach Grant (2022) for research at Graz University of Technology She previously worked as a Biomedical Engineer at ATP Medical Device Company, Tehran, and has held a visiting researcher position at Graz University of Technology. Her academic journey reflects a commitment to advancing biomechanical research through interdisciplinary collaboration and computational innovation.
Sadik Omairey is a Senior Research Fellow at Brunel Composites Centre (BCC), a joint venture between Brunel University London and The Welding Institution (TWI) since June 2019. He serves as technical lead for collaborative projects involving automotive crash structures, all-composites aircraft fuselage assembly, and thermoplastic additive manufacturing. Affiliated with Brunel University London's College of Engineering, Design and Physical Sciences, he represents BCC at academic conferences and contributes to postgraduate student training. His research spans composite materials reliability, metamaterials, biomechanics, and sustainable manufacturing. Key interests include computational homogenization (notably through his EasyPBC tool), crashworthiness optimization, adhesive bonding, and additive manufacturing. His work integrates experimental testing with advanced finite element modeling, focusing on applications in aerospace, automotive, and biomedical engineering. Recent publications (2021-2025) reveal strong trends in multiscale modeling of composites, life cycle analysis for sustainable design, and bio-inspired metamaterials. His collaborative work frequently addresses industrial challenges in automotive crash structures and aircraft fuselage assembly, with growing emphasis on recyclability and environmental impact assessment in materials engineering. Awarded significant professional recognitions: PRINCE2® Foundation Project Management certification (2023) Chartered Engineer and Fellow of IMechE (CEng FIMechE, 2018) Fellow of the Higher Education Academy (FHEA, 2018) Omairey actively supervises postgraduate students and leads multiple funded research projects including HyPStore (hydrogen storage), modular crash boxes, and PADICTON (distortion compensation in additive manufacturing). His work bridges academic research with industrial applications through partnerships with automotive and aerospace sectors. He contributes to BCC and IMM research groups, focusing on experimental validation and computational modeling of advanced composite systems.
Professor Talal Rahman is a faculty member at the Western Norway University of Applied Sciences, where he works in the Department of Computer Science, Electrical Engineering and Mathematical Sciences. His office is located at Bergen KRONSTAD D305, and he can be reached at phone number +47 55 58 72 46. Professor Rahman's research spans several key areas in computational mathematics and scientific computing. His primary research interests include: Scientific Computing Numerical Analysis Numerical Methods for Partial Differential Equations Preconditioning Finite Element with Domain Decomposition Methods Variational Image Processing Artificial Intelligence and Machine Learning applications Professor Rahman's extensive publication record demonstrates a strong focus on domain decomposition methods, particularly Schwarz methods and their applications to multiscale problems. His recent work shows an increasing integration of machine learning techniques with traditional numerical methods, as evidenced by publications on neural network applications for environmental modeling and capelin migration patterns. His research also extends to biomedical applications, including computational analysis of biodegradable materials and bone tissue engineering scaffolds. He has made significant contributions to the development of adaptive preconditioners and parallel algorithms for solving complex numerical problems, with his work on the TV-Stokes model for image processing representing an important contribution to the field of variational image processing. Professor Rahman has supervised numerous research projects and students, though specific student names are not provided in the available information. His research appears to be supported by grants related to computational science and engineering, though specific grant details are not mentioned in the provided text. Based on his research areas, Professor Rahman likely collaborates with various research groups focused on computational science, with potential connections to biomedical engineering labs and environmental research teams studying the Barents Sea ecosystem.
Nicolas Doyon is a Professor at the Department of Mathematics and Statistics , Université Laval, Canada. His research bridges mathematical modeling and neuroscience , focusing on ion transport, neural networks, and neurodegenerative diseases. He collaborates with experimentalists and companies like Doric Lenses . Education: B.Sc., Université Laval M.Sc., University of Montreal Ph.D., Theoretical Mathematics Postdoctoral Fellowship, Quebec City Institute of Mental Health Research Interests: Dr. Doyon investigates chloride homeostasis via the KCC2 cotransporter , its role in synaptic inhibition, and implications for diseases like epilepsy and autism. He develops finite element models for Poisson-Nernst-Planck equations to study electrodiffusion in complex neural geometries. Scientific Awards: Star Teacher (2016, Faculty of Science and Engineering) NSERC Individual Grant (35K$/year, 2014-2019) FQRNT Establishment Grant (20K$/year, 2013-2015) Students: Supervises Ph.D. and Master's students including Tahmineh Azizi (dynamical systems), Frank Boahen (dendritic spines), and Vincent Ouellet (analytic number theory).
Weria Pezeshkian is an Assistant Professor in the Biocomplexity research group at the Niels Bohr Institute, University of Copenhagen. With expertise spanning computational biophysics and membrane dynamics, Dr. Pezeshkian leads research that bridges physics, biology, and computational science to address fundamental questions in cellular mechanics. Dr. Pezeshkian's research focuses on: Computational modeling of cellular membranes and their dynamic properties Molecular dynamics simulations of protein-lipid interactions Membrane mechanics and curvature generation mechanisms Plasma membrane repair processes Development of computational methodologies for multiscale biological modeling Analysis of recent publications reveals a strong emphasis on membrane biophysics, particularly in understanding how proteins interact with and shape cellular membranes. The research combines advanced computational techniques with experimental data to model complex cellular processes across multiple scales. Key contributions include elucidating mechanisms of membrane repair, protein-induced membrane curvature, and innovative simulation methodologies like FreeDTS and TS2CG. Scientific recognition includes: MGMS Frank Blaney Award (2024) Dr. Pezeshkian maintains an extensive collaborative network across institutions and disciplines, focusing on integrative approaches to complex biological questions. The research has significant implications for understanding fundamental cellular processes and potential applications in disease mechanisms related to membrane dysfunction.
Dr. Xiaowei Zeng serves as Associate Professor and Graduate Advisor of Record for the PhD program in the Department of Mechanical Engineering at the Margie and Bill Klesse College of Engineering and Integrated Design, University of Texas at San Antonio (UTSA). He leads the Computational Mechanics Laboratory, focusing on theoretical and computational approaches to material behavior. His educational background includes: Ph.D. in Engineering, George Washington University Research interests center on computational mechanics with emphasis on bone fracture mechanisms , cell motility modeling , material failure analysis , and multiscale modeling . His work employs advanced methodologies including Finite Element Method (FEM), Cohesive FEM, Meshfree Methods, and Molecular Dynamics Simulation to bridge microstructural properties with macroscopic material behavior in biological and engineered systems. Analysis of recent publications (2019-2025) reveals dominant themes in bioinspired materials , bone mechanics , and cellular dynamics . Key trends include integration of machine learning for mechanics prediction, fracture analysis in polycrystals and biostructures, and multiscale approaches spanning molecular dynamics to continuum modeling. Research increasingly addresses material design challenges through interface engineering and computational optimization. As Graduate Advisor of Record, Dr. Zeng oversees PhD student mentorship in Mechanical Engineering. His research program receives sponsored funding for computational mechanics projects, though specific grant details are not provided in available sources. The Computational Mechanics Laboratory develops theoretical frameworks and computational tools to investigate material microstructure-macroscopic behavior relationships, with current projects targeting bone fracture, cell migration, and bioinspired nanocomposite design.
Spencer Szczesny serves as Associate Professor in both the Department of Biomedical Engineering and Department of Orthopaedics and Rehabilitation at Pennsylvania State University, where he leads the Multiscale Biomechanics and Mechanobiology Lab. His research bridges engineering and clinical orthopaedics to investigate tendon pathology, repair mechanisms, and biomaterial design through interdisciplinary approaches. His academic credentials include: PhD in Biomedical Engineering from University of Pennsylvania (2015) MS from Massachusetts Institute of Technology (2005) BS from University of Pennsylvania (2003) Dr. Szczesny's research centers on tendon multiscale mechanics and mechanobiology, examining how mechanical forces influence tissue remodeling in degeneration, repair, and development. His lab integrates multiscale mechanical testing, computational modeling, cell/tissue culture, and biomaterial fabrication to identify pathological mechanisms and develop novel therapeutics. This work directly contributes to UN Sustainable Development Goals in health and well-being through advancements in musculoskeletal treatments. Recent publications reveal strong thematic continuity in tendon/ligament biomechanics, with emphasis on cyclic loading effects across biological scales—from embryonic development to clinical ACL reconstructions. Key trends include sex-specific mechanoresponses, oxygen regulation in tissue culture, and structural determinants of multiscale mechanics, reflecting his lab's focus on translating fundamental mechanobiology into clinical applications. His active research portfolio includes five major grants: NSF CAREER award (2022-2027) on tendon cell mechanobiology in native tissue environments US-Ireland R&D Partnership (2022-2026) for engineering load-bearing soft tissues U.S. Army project (2021-present) identifying mechanobiological deficits in allograft ACL reconstructions Congressionally Directed Medical Research Programs project (2020-present) on same topic National Institute of Arthritis grant (2022-2023) on gene expression-tissue strain colocalization The Multiscale Biomechanics and Mechanobiology Lab maintains cross-disciplinary collaborations spanning engineering, developmental biology, and orthopaedic surgery, with recent work highlighted by 6 news outlets and generating significant social media engagement among researchers.
Andrew Bragg is an Associate Professor in the Department of Civil and Environmental Engineering at Duke University's Pratt School of Engineering. His research focuses on turbulence and fluid dynamics with applications in environmental systems, including atmospheric and oceanic flows, sediment transport, and climate modeling. Research Interests: His primary research areas include the physics and modeling of turbulence, theoretical and computational fluid dynamics, and applied mathematics. He investigates multiscale turbulent transport phenomena, especially in environmental contexts where unresolved scales challenge large-scale models. His work integrates statistical physics, high-performance computing, and collaboration with experimentalists. The recent publications (2024–2023) reflect a strong trend in understanding turbulence across environmental and engineered systems. Key themes include particle and scalar transport in stratified and wall-bounded flows, bubble-induced turbulence, surfactant effects, Lagrangian modeling, and subgrid-scale parameterizations for climate models. The research spans fundamental fluid mechanics to applied environmental engineering, often using advanced computational and theoretical frameworks. Scientific Awards: National Science Foundation CAREER Award (2021) EUROMECH Young Scientist Award (2017) Advising and Grants: While specific students are not listed, Dr. Bragg has secured competitive funding, notably the NSF CAREER award, indicating active mentorship and research leadership. He teaches graduate-level courses such as ME/CEE 634/688: Turbulence and CEE 690: Advanced Topics in Civil and Environmental Engineering, suggesting involvement in training the next generation of researchers. Labs and Teams: Dr. Bragg collaborates extensively with researchers across institutions and disciplines, including experimentalists and modelers in atmospheric science, mechanical engineering, and environmental engineering. His work is part of a broader effort to improve predictive models for environmental resilience and risk assessment.
