جستجوی استاد راهنمای دانشگاهی

Carlo Cavicchiaمشاهده پروفایل

استادیار

• Statistics
• Data Science
• Machine Learning
• +۶ مورد دیگر

Dr. Carlo Cavicchia is an Assistant Professor of Statistics at the Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam. He holds a PhD in Methodological Statistics from La Sapienza University of Rome and has held roles such as Research Fellow at UnitelmaSapienza University and Consultant for NGOs in Zanzibar. His research focuses on latent variable models, composite indicators, and unsupervised classification, with applications in environmental policy, sports analytics, and teacher job satisfaction. Cavicchia teaches statistics and data science courses at undergraduate and graduate levels and actively contributes to academic communities through journal reviewing, conference organizing, and editorial roles. Education: PhD in Methodological Statistics (La Sapienza University of Rome, 2020) MSc in Statistics and Decision Sciences (La Sapienza University of Rome, 2016) BSc in Statistics (La Sapienza University of Rome, 2013) Dutch University Teaching Qualification (BKO, 2022) Research Interests: Cavicchia’s work emphasizes hierarchical models, non-parametric statistics, and data science applications. He develops methodologies for composite indicators, including ultrametric Gaussian mixture models and disjoint principal component analysis. His research bridges theoretical advancements with real-world problems, such as waste management in Italian municipalities and ranking European football teams using composite metrics. Grants & Awards: 2024: IFCS Chikio Hayashi Award 2023: ESE Starter Grant (€300,000) 2017: Research Grant for Junior Researchers (€1,270) 2016: PhD Scholarship, La Sapienza University Academic Engagement: Cavicchia serves as IASC Data Analysis Competition Officer (2023–2025), co-edits the ISI Magazine , and organizes conferences like DSSV 2020 and DSSV-ECDA 2021. He is an elected member of the International Statistical Institute and contributes to SVQS’s Sustainability initiatives. Labs & Teams: He co-organizes the Econometrics internal seminars at Erasmus University and collaborates with researchers at University of Naples Federico II on hierarchical models and convex clustering.

Bjorn Baumeierمشاهده پروفایل

دانشیار

• Multiscale Simulation
• Electronic Transport
• Computational Chemistry
• +۵ مورد دیگر

Bjorn Baumeier is an Associate Professor in the Department of Mathematics and Computer Science at Eindhoven University of Technology (TU/e). His research group is part of the Centre for Analysis, Scientific Computing and Applications (CASA) and the Institute for Complex Molecular Systems (ICMS). He also participates in several research groups including Scientific Computing, ICMS Core, Eindhoven Hendrik Casimir institute, and Computational Quantum & Molecular Dynamics. His educational background includes: Diploma in Theoretical Solid State Science from the University of Münster PhD in Theoretical Solid State Science from the University of Münster Baumeier's research focuses on the development and application of multiscale simulation techniques for studying electronic transport processes in soft matter. His work combines approaches from computational chemistry, statistical physics, and mathematics to analyze the interplay between molecular electronic structure and material morphology. Additional research lines include studies of disordered biomolecular assemblies and super-coarse-grained modeling of soft granular materials. His group employs large-scale computer simulations linking quantum chemistry, classical Molecular Dynamics at various levels, and rate-based models. Recent publications (2024-2025) demonstrate a strong focus on charge transport phenomena in complex materials, with particular emphasis on interface effects in polymer composites, trap identification in molecular networks, and embedded many-body Green's function methods. His work bridges fundamental physics with practical applications in energy materials and opto-electronic devices. Scientific awards include: Vidi grant from NWO (The Netherlands Organisation for Scientific Research) in 2017 (€800,000) Baumeier has received significant research funding, most notably the Vidi grant focusing on understanding mechanisms underlying long-distance and spin-selective electronic transport in complex molecular systems. His research is often conducted in collaboration with multiple institutions and research groups within TU/e, indicating a strong interdisciplinary approach. His work has practical applications in opto-electronic devices and bio-molecular processes. His research group operates within the Computational Quantum & Molecular Dynamics group, which is part of several larger research initiatives at TU/e including ICMS and the Eindhoven Hendrik Casimir institute. This positioning allows for strong collaboration across physics, chemistry, and engineering disciplines.

Jörg Henselerمشاهده پروفایل

استاد

• Structural Equation Modeling
• Partial Least Squares Path Modeling
• Composite-Based Structural Equation Modeling
• +۸ مورد دیگر

Prof. Dr. Jörg Henseler is Full Professor and Chair of Product–Market Relations at the Department of Design, Production and Management, Faculty of Engineering Technology, University of Twente, Netherlands. He also holds visiting positions at NOVA Information Management School, Universidade Nova de Lisboa, Portugal, and as Distinguished Invited Professor at the University of Seville, Spain. University: University of Twente School: Faculty of Engineering Technology Department: Department of Design, Production and Management Chair: Product–Market Relations Visiting Professor: NOVA Information Management School, Portugal Distinguished Invited Professor: University of Seville, Spain His research focuses on composite-based structural equation modeling (SEM) , particularly partial least squares (PLS) path modeling , emergent variables , and methodological innovations in empirical research. He bridges design and behavioral sciences through advanced statistical modeling, with applications in marketing, management, and information systems. His recent publications emphasize methodological rigor in PLS-SEM, including consistent PLS (PLSc) , confirmatory composite analysis (CCA) , HTMT for discriminant validity , and second-order modeling . These works highlight trends toward improved model assessment, validity testing, and theoretical integration in composite-based approaches. Highly Cited Researcher by Clarivate/Web of Science Ranked among the top 100 most influential researchers in the Stanford/Elsevier Top 2% Scientists List 2024 Repeated 'Teacher of the Year' award recipient Prof. Henseler contributes extensively to the scientific community as a reviewer, editorial board member, and guest editor. He chairs the scientific advisory board for the ADANCO software and organizes the PLS School , offering seminars on PLS path modeling. He has authored over 130 journal articles and the authoritative book Composite-Based Structural Equation Modeling . His work supports researchers in applying robust, theory-driven methods in empirical studies. He leads methodological innovation in composite-based modeling, with strong ties to software development and global academic outreach. His research group and collaborations focus on advancing SEM techniques for complex, real-world applications in business and engineering contexts.

• Composite Materials
• Additive Manufacturing
• Finite Element Analysis
• +۳ مورد دیگر

Joris J.C. Remmers is an Associate Professor of Composite Materials at the Department of Mechanical Engineering, Eindhoven University of Technology (TU/e). He is also affiliated with the EAISI High Tech Systems and leads the Mechanics of Materials research group. His academic journey includes a MSc in Aerospace Engineering (TU Delft, 1998) and a PhD in Computational Mechanics (TU Delft, 2006). Remmers' research focuses on composite materials and additive manufacturing, particularly the relationship between manufacturing processes, microstructure, and mechanical properties. He employs advanced numerical techniques to study multi-physics phenomena across scales. Research Themes: Composite materials and fiber-reinforced systems 3D printing and additive manufacturing processes Numerical methods (e.g., finite element analysis, model order reduction) Micromechanical modeling of material behavior Grants and Projects: Project Manager for Innovation test bed for development and production of nanomaterials for lightweight embedded electronics (2019–2023) Awards: Emerging DMD Based Systems and Applications Best Paper Award (2025) Teaching: Leads courses on advanced manufacturing, computational mechanics, and data-driven approaches in engineering, including Advanced and Additive Manufacturing and AI-assisted innovation in portable plasma technology . Labs/Teams: Active in the Mechanics of Materials group, collaborating on multi-scale mechanics, damage modeling, and material failure analysis.

Leon E. Govaertمشاهده پروفایل

استاد

• Mechanical Engineering
• Polymer Science
• Materials Science
• +۴ مورد دیگر

Leon E. Govaert is a Professor in the Mechanical Engineering department at Eindhoven University of Technology, leading the Processing and Performance group. His research focuses on polymer mechanics, particularly micromechanical modeling of deformation and failure in semicrystalline and amorphous polymers, with applications in composites and nanocomposites. His work addresses key areas such as Rate- and temperature-dependent viscoplasticity Constitutive modeling for thermoplastics Micromechanical analysis of fiber-reinforced polymers Structure-property relations in semicrystalline polymers Plasticity-controlled and crack-growth-controlled failure mechanisms Recent publications highlight trends in Computational modeling of polymer deformation kinetics Characterization of multiaxial failure in composites Impact of microstructure on mechanical performance Advancements in EMI shielding nanocomposites Thermal residual stress analysis He has supervised numerous doctoral students, including S.B.W. Meijers and T. M. den Hartog, and contributed to datasets like molecular dynamics analysis of iPP-polymorphs. His expertise aligns with the Processing and Performance group, addressing challenges in polymer durability and mechanical behavior under diverse conditions.

Patrick Andersonمشاهده پروفایل

استاد

• Polymer Rheology
• Complex Fluids
• Structure Development During Flow
• +۶ مورد دیگر

Patrick Anderson is Dean of the Department of Mechanical Engineering and full professor specializing in structure and rheology of complex fluids at Eindhoven University of Technology (TU/e). He chairs the Polymer Technology group within the Institute for Complex Molecular Systems. His academic career spans over two decades since completing his PhD in Mechanical Engineering in 1999, with a one-year industry stint at Océ Technologies before joining TU/e. Professor Anderson's research focuses on: Structure development during flow of complex fluids Interfacial phenomena in polymer processing Additive manufacturing technologies Computational methods for analyzing interfacial flows Rheology of polymer blends and composites His recent publications reveal a strong interdisciplinary approach combining polymer science, rheology, and advanced manufacturing. The research shows increasing focus on sustainable materials like polylactic acid (PLA), 3D food printing applications, and electromagnetic interference shielding solutions using polymer nanocomposites. His methodology consistently integrates computational modeling with sophisticated experimental techniques such as in-situ X-ray and light scattering measurements across multiple length scales. Professional recognition includes: Chairmanship of the Dutch Society of Rheology Editorial Board membership for Macromolecular Materials Engineering International Advisory Board participation for polymer science journals Prestigious visiting professorships at UCSB, Stanford, and ETHZ Professor Anderson has developed educational materials including an interactive textbook for first-year mechanical engineering students published in 2024. His research group collaborates extensively with industry partners through projects like the Dutch Polymer Institute initiative ANGLE, demonstrating his commitment to translating fundamental understanding into practical applications across multiple sectors. He leads the Processing and Performance research group within the ICMS Core at TU/e, focusing on advancing quantitative predictive capability in polymer product design and manufacturing processes.

Martijn van Beurdenمشاهده پروفایل

استاد

• Computational Electromagnetics
• Inverse Problems
• Numerical Methods
• +۳ مورد دیگر

Martijn van Beurden is a Full Professor in the Electromagnetics group at Eindhoven University of Technology's Department of Electrical Engineering. His research focuses on computational electromagnetics for high-tech systems, particularly inverse scattering problems and electromagnetic field optimization. Key affiliations: Electromagnetic and Multi-Physics Modeling and Computation Lab, Center for Wireless Technology Eindhoven, EAISI Foundational Research Interests : Specializes in numerical methods for electromagnetic wave analysis, design, and detection. Areas include inverse scattering, integral equations, nonlinear optimization, and modeling of stochastic/uncertain electromagnetic fields. Current projects address periodic structures, antenna design, and soft X-ray metrology. Scientific Awards : C.I.V.I. prize for Electrical Engineering (MSc thesis, 1997) ASML prize for best PhD thesis in applied research (2004) Advising & Collaborations : Collaborates with researchers like Stefan Eijsvogel, Roeland Dilz, and Radovan Bojanic on computational electromagnetics projects.

Celal Soyarslanمشاهده پروفایل

دانشیار

• Material Science
• Solid Mechanics
• Additive Manufacturing
• +۵ مورد دیگر

Celal Soyarslan is an Associate Professor in Nonlinear Solid Mechanics, specializing in advanced materials and computational mechanics. His research focuses on material science, additive manufacturing, metamaterials, and machine learning applications in engineering. He has contributed to studies on microstructural modeling, fracture mechanics, and homogenization techniques, with applications in aerospace, biomedical, and energy sectors. Key research interests include the development of coupled damage models for composites, optimization of 3D microstructures using generative methods, and the integration of physics-informed machine learning into multiscale simulations. His work often addresses challenges in material characterization, such as effective magnetic and thermomechanical properties of composites. Publications highlight innovations in additive manufacturing of NiTi metamaterials, physics-informed modeling of elliptic equations, and the study of auxetic biological materials. Collaborations span international institutions, emphasizing interdisciplinary approaches to material design and analysis.

Nick Jaenssonمشاهده پروفایل

استادیار

• Non-Newtonian Fluid Mechanics
• Interfacial Rheology
• Computational Modeling
• +۴ مورد دیگر

Nick Jaensson is an Assistant Professor in the Processing and Performance of Materials group within the Department of Mechanical Engineering at Eindhoven University of Technology (TU/e). He leads Group Jaensson and is affiliated with the Institute for Complex Molecular Systems (ICMS). His work bridges computational methods with experimental validation to advance understanding of soft materials and complex fluids. Jaensson earned his Master's degree in Biomedical Engineering from TU/e in 2012, followed by a PhD in Mechanical Engineering in 2016 with a thesis titled "Modeling interfaces and particles in viscoelastic fluids." After a year at DSM Materials Science Center, he conducted postdoctoral research at ETH Zürich before returning to TU/e as an Assistant Professor in mid-2020. His research focuses on the development and application of numerical methods for soft materials including suspensions, emulsions, and polymeric liquids. Key interests include interfacial rheology, non-Newtonian fluid mechanics, uncertainty quantification, and physics-informed machine learning. His work combines advanced computational modeling with experimental collaboration to gain fundamental insights into flow and transport processes within these materials, with applications ranging from microfluidics to large-scale industrial processing. Analysis of his recent publications reveals a strong emphasis on fiber orientation kinetics in polymer composites, viscoelastic flow modeling, and the integration of machine learning with physics-based models. His work spans both fundamental fluid dynamics and practical industrial applications, with particular attention to experimental validation of computational models. Jaensson contributes to several research projects including the Dutch Polymer Institute (DPI) Project No. 840 (ANGLE) and the DAMOCLES research project funded by the Eindhoven Artificial Intelligence Systems Institute. His work demonstrates strong industry-academia collaboration, particularly with companies involved in polymer processing and material science. As an educator, Jaensson teaches courses including Interfacial Transport Phenomena in Engineering Flows, Structure and Flow, Advanced Computational Continuum Mechanics, and Principles of Design and Programming. He leads research in the Processing and Performance group, focusing on computational methods for soft materials, with particular strength in connecting microstructural properties to macroscopic material behavior.

Xi Yuمشاهده پروفایل

پژوهشگر

• Structural Equation Modeling
• Materials Science
• Nanotechnology
• +۵ مورد دیگر

Xi Yu is a Researcher at the Digital Society Institute, University of Twente. Their work focuses on advancing statistical methodologies in structural equation modeling while also exploring materials science innovations in nanocomposites and phase change materials. Yu has made significant contributions to composite specification techniques and their applications in ecological and technological systems. Education & Research Expertise Completed a PhD thesis titled 'Incorporating Composites in Structural Equation Modeling: Exploiting the Henseler—Ogasawara Specification' at the University of Twente. Active research areas include composite model refinement, statistical data analysis, and material degradation studies. Collaborations involve interdisciplinary projects with institutions globally. Research Highlights Publications span methodological advancements in structural equation modeling and applied material science innovations such as thermoregulating textiles and nanocomposite synthesis. Recent work emphasizes eco-friendly materials and energy-efficient solutions. Awards : Best Conference Paper Award (2021), First Runner-Up Best Paper Award (2022), Top Cited Article (2022-2023) Invited Talks : Presented on composite specification methods at international conferences (2023-2024) Dataset Contributions : Open-access materials on composite modeling techniques via Zenodo Future Focus : Continues developing hybrid methodologies bridging statistical theory and material innovation, with applications in sustainability and digital societal challenges.

• Statistical Modeling
• Data Analysis
• Social Sciences Research
• +۳ مورد دیگر

Dr. Chia Chia is a Research Fellow at the International Institute of Social Studies (ISS) of Erasmus University Rotterdam. Her work focuses on advanced statistical methodologies applied to social sciences, environmental studies, healthcare, and sports analytics. She specializes in hierarchical modeling techniques, composite indicators, and factor analysis to address complex multidimensional problems. Her research bridges theoretical statistical developments with practical applications in policy evaluation and data-driven decision-making. Affiliation: International Institute of Social Studies, Erasmus University Rotterdam Research Themes: Hierarchical clustering, ultrametric models, composite indicators, structural equation modeling, and multivariate analysis Chia Chia’s recent studies include developing unbiased distance metrics for mixed-type data, modeling waste management efficiency in Italian municipalities, and analyzing driver behavior related to mobile phone use. Her work on hierarchical disjoint factor analysis has been applied to environmental policy assessment and sports performance evaluation. She actively contributes to methodological advancements in clustering algorithms and Gaussian mixture models, emphasizing computational efficiency and real-world applicability. Her publications reflect a strong emphasis on bridging statistical theory with practical challenges in education, healthcare, and environmental science. Notable trends in her work include the integration of ultrametric structures into composite indicators and the application of parsimonious models to reduce computational complexity. Grants & Collaborations: While specific grants are not detailed, her research aligns with ISS’s focus on global development issues, suggesting involvement in interdisciplinary projects. She collaborates with institutions specializing in environmental policy, healthcare decision-making, and sports analytics.

Jan Friso Grooteمشاهده پروفایل

استاد

• Formal Methods
• Verification Technology
• Software Engineering
• +۱۲ مورد دیگر

Jan Friso Groote is a Full Professor and Chair of the Formal System Analysis group in the Department of Mathematics and Computer Science at Eindhoven University of Technology (TU/e). He also holds professorial roles in the EAISI Foundational and EAISI High Tech Systems institutes. Since 2016, he has been working part-time at ASML, contributing his expertise in formal verification to industrial applications. Education: Born in 1965, studied Computer Science at Twente University of Technology (now University of Twente), 1983–1988. PhD in 1991 from the University of Amsterdam with thesis 'Process algebra and structured operational semantics', based on research at CWI (Centrum Wiskunde en Informatica). Jan Friso Groote is a leading researcher in formal methods and software verification. His work focuses on enabling the development of flawless software through rigorous formal analysis. Key research areas include structural operational semantics, model checking, branching bisimulation, protocol verification, and the development of the mCRL2 toolset. His current goal is to integrate formal techniques into complete software system design, improving both development speed and quality. His research has demonstrated that formal methods can reduce development time by a factor of three and increase quality tenfold, with potential for zero-defect software. His recent publications demonstrate sustained contributions in formal verification, including work on mutual exclusion algorithms, industrial control system modeling, probabilistic systems, and efficient bisimulation algorithms. The articles span topics such as tunnel control systems, simulation lower bounds, and formal methods for critical systems, reflecting both theoretical depth and practical application. Scientific Awards: Best Paper Award FACS 2018 FMICS-AVoCS Best Paper Award (2017) Jan Friso Groote has held significant leadership roles in education, including Director of Education for Computer Science (2000–2010) and for multiple bachelor’s and master’s programs. He has advised numerous researchers and supervised a large body of research output (over 320 publications). He leads the Formal System Analysis group and has been involved in projects such as 'Composable Embedded Systems for Healthcare'. His work bridges academia and industry, particularly through collaborations with ASML and Rijkswaterstaat, and he has been a visiting researcher at institutions across Europe and China. He is a key contributor to the mCRL2 toolset, which supports modeling and verification of software behavior with data, time, and probabilities. His research fingerprints highlight strong expertise in model checking, transition systems, software design, and process algebra. He teaches courses such as System Validation, Embedded Software, and Capita Selecta in Formal System Analysis.

Florian Schuberthمشاهده پروفایل

دانشیار

• Structural Equation Modeling
• Partial Least Squares
• Composite-based Methods
• +۷ مورد دیگر

Florian Schuberth is an Associate Professor at the Chair of Product–Market Relations within the Faculty of Engineering Technology at the University of Twente. His research focuses on composite-based structural equation modeling (SEM), particularly Partial Least Squares (PLS) methods, with applications across Information Systems, Social Sciences, and Computer Science. He actively contributes to quantitative research methodology and open science. Bachelor's and Master's in Business Administration and Economics, University of Würzburg PhD in Econometrics, summa cum laude, University of Würzburg (2017) His research interests center on advancing composite-based SEM, including model specification, fit assessment, higher-order constructs, and robust estimation techniques. He emphasizes methodological rigor and reproducibility in social science research. His recent work, reflected in publications and software development, demonstrates a strong trend toward improving the transparency, validity, and accessibility of composite modeling techniques, particularly through R-based tools. He has made significant contributions to model evaluation, measurement invariance, and endogeneity correction in PLS-SEM. Florian Schuberth is a passionate educator, coordinating and teaching courses on quantitative research methods. He is also deeply committed to open science, serving as coordinator of the Open Science Community Twente. Notable contributions include the development and maintenance of the cSEM R package, which enables researchers to perform composite-based SEM in R, promoting open, reproducible research practices. Maintainer of the R package cSEM Coordinator, Open Science Community Twente (since 2022) Active contributor to methodological software and open science infrastructure

X. Yuمشاهده پروفایل

پژوهشگر

• Structural Equation Modeling
• Composite-Based Methods
• Statistical Methods in Business Research
• +۸ مورد دیگر

X. Yu is a researcher at the University of Twente, affiliated with the Faculty of Engineering Technology (ET), the Department of Design, Production and Management (ET-DPM), and the Chair of Product-Market Relations (ET-DPM-PMR). They are also associated with the Digital Society Institute, contributing to interdisciplinary research at the intersection of engineering, data science, and societal applications. Bachelor's Degree — University of Twente Master's Degree — University of Twente Ph.D. — University of Twente, supervised by Prof. dr. ir. Jörg Henseler Their primary research focuses on composite-based methods for structural equation modeling (SEM) , particularly advancing the Henseler–Ogasawara specification . They also explore the application of advanced statistical techniques in diverse domains such as business, psychology, and medical research. Their interdisciplinary expertise spans mathematical modeling , illustrative modeling examples , and technical methods like scanning electron microscopy . X. Yu’s work bridges computational statistics and applied research, contributing to robust methodological frameworks in behavioral and composite models. Their research supports the development of more accurate and interpretable models in complex data environments, particularly within the digital society context. No scientific awards were mentioned in the provided text. X. Yu has conducted their academic training and research entirely at the University of Twente, working under prominent supervision in the PMR chair. There is no mention of external grants or funded projects in the available information. X. Yu is embedded in the Product-Market Relations research group within the Design, Production and Management department and contributes to the broader initiatives of the Digital Society Institute, focusing on data-driven societal innovations.