Multilevel Structural Equation Modeling Professors and Supervisors | ApplySharif

Find Academic Supervisors

Find and connect with academic supervisors, professors, and scholars for your research journey.

Showing 31-45 of 332 supervisors

Profile data may be stale. It is sourced from public faculty pages.

Jun YanView profile

Professor

University of ConnecticutUnited States

Dr. Jun Yan is a Professor in the Department of Statistics at the University of Connecticut. His research spans network analytics, spatial extremes, survival analysis, and statistical computing with applications in public health, finance, and environmental science. His core research interests include: network modeling and analysis, spatial statistics for climate extremes, survival analysis methodologies, statistical computing frameworks, and applications in interdisciplinary domains including sports analytics. Dr. Yan has developed significant statistical methodologies for network analysis, climate change detection, financial modeling, and health analytics. His recent publications demonstrate innovation in modeling complex network structures, analyzing climate extremes, developing computational approaches for massive datasets, and creating specialized statistical methods for health and finance applications. He maintains active collaborations across disciplines and contributes to open-source statistical software. Honors include: Guggenheim Fellowship, multiple Fromm Foundation commissions, and Barlow Endowment recognition.

Official University Profile

Maria PampakaView profile

Professor

The University of ManchesterUnited Kingdom

Dr. Maria Pampaka is a Professor at the University of Manchester, holding joint appointments in the Manchester Institute of Education and the Department of Social Statistics. Her research focuses on mathematics education, particularly learners’ attitudes and dispositions, advanced quantitative methods, and the application of complex systems theory. She has led projects on mathematics anxiety, gender equality measurement, and longitudinal survey analysis. Pampaka employs methodologies like Rasch modeling, missing data imputation, and agent-based simulations. She has collaborated internationally on studies ranging from regional gender gaps to tourist behavior analysis. Her work contributes to UN Sustainable Development Goals related to quality education and gender equality. Her research interests span mathematics education, quantitative research methods, and social statistics. Notable projects include a systematic review of mathematics anxiety and the development of the Extended Regional Gender Gaps Index (eRGGI). She has also explored applications of machine learning in tourism and healthcare, such as predicting revisit intentions and optimizing hospital resource allocation during the pandemic. Projects: Systematic review of mathematics anxiety, eRGGI development, analysis of sexual assault survivor support needs, and requirements discovery for smart driver assistive technologies. Key methodologies: Rasch modeling, multilevel modeling, thematic analysis, agent-based simulations, and machine learning. Collaborations: Cross-disciplinary work with social scientists, engineers, and healthcare professionals internationally. Pampaka’s work bridges education, statistics, and policy, aiming to inform equitable practices in learning and societal structures. She is engaged in impact initiatives like the Good Behavior Game evaluation and policy-informed gender equality research.

Official University Profile

Leslie GreengardView profile

Professor

New York UniversityUnited States

Leslie Greengard is a Silver Professor of Mathematics and Computer Science at New York University's Courant Institute, part of the Faculty of Arts and Science. His research focuses on integral equation methods for electromagnetics, acoustics, plasma physics, and fluid dynamics, with recent work extending to kernel-based methods in statistical inference. He leads the Courant Mathematics and Computing Laboratory and contributes to novel electromagnetic simulation techniques. Education: Ph.D. and M.D. in Computer Science and Medicine from Yale University (1987) B.A. in Mathematics from Wesleyan University (1979) Research Interests: Greengard's group develops fast solvers for complex geometries in electromagnetics and fluid dynamics. Notable contributions include the Fast Multipole Method (FMM) for particle simulations and Quadrature by Expansion (QBX) for layer potential evaluations. His work bridges computational mathematics and applications in physics, engineering, and biomedicine. Recent Article Trends: Recent publications emphasize fast algorithms (e.g., FMM, adaptive Gauss transforms), biomedical applications (e.g., deep brain stimulation modeling), and cosmological simulations. His methods address challenges in high-dimensional data, multiscale problems, and real-time computation. Awards & Recognition: While no specific prizes are listed, his foundational work on FMM has had a transformative impact on computational science. Advising & Collaborations: Collaborations span academia and industry, with co-authors including V. Rokhlin, M. O’Neil, and others. No formal advisees are listed here, though his research involves postdoctoral fellows and graduate students. Labs & Teams: Active in the Courant Mathematics and Computing Laboratory, focusing on electromagnetic simulation and design methodologies.

Official University Profile

Anders SkrondalView profile

Professor

University of OsloNorway

Anders Skrondal is a Professor II at the University of Oslo's Faculty of Educational Sciences, affiliated with the Centre for Educational Measurement (CEMO). He also serves as a Senior Scientist at CEFH (Research Council of Norway Centre of Excellence) at the Norwegian Institute of Public Health and Co-Principal Investigator at CREATE, another Norwegian Centre of Excellence. His academic journey includes roles as Head of the Biostatistics Group at the Norwegian Institute of Public Health and Professor of Statistics at the London School of Economics (LSE), where he directed the Methodology Institute. Skrondal's research focuses on psychometrics, statistics, biostatistics, and econometrics, with a major contribution being the development of the GLLAMM framework. He has authored 14 books and over 200 peer-reviewed papers, achieving an h-index of 63 and 30,000+ citations. His awards include the 1997 Psychometric Society Dissertation Prize and leadership roles in prestigious organizations like the Psychometric Society and Royal Statistical Society. Research Interests: Skrondal specializes in statistical methodologies including latent variable modeling, multilevel modeling, and missing data analysis. His work bridges theoretical advancements and practical applications in medicine, psychology, and social sciences. He is renowned for integrating latent variable and mixed model frameworks to address complex data structures. Recent trends in his publications emphasize methodological solutions for missing data, non-ignorable mechanisms, and psychometric model validation. His articles span statistical theory, medical applications, and educational measurement. Awards: President, Psychometric Society (2016–2017) Elected Member, International Statistical Institute Outstanding Academic Title for 'The Cambridge Dictionary of Statistics' (2011) Fulbright Professor at UC Berkeley (2013–2014) Advising & Grants: Skrondal has led major research initiatives such as CEFH and CREATE, funded by the Research Council of Norway. While no specific advisee list is provided, his collaborations span international institutions. His work on GLLAMM software is used in over 750 journals, reflecting widespread academic impact. Labs/Teams: Active in CEMO and CEFH, he contributes to interdisciplinary teams advancing educational measurement and public health research. His involvement in CREATE focuses on equality in education through statistical innovations.

Official University Profile

Ian Brunton-SmithView profile

Professor

University of SurreyUnited Kingdom

Professor Ian Brunton-Smith is a leading academic in Criminology and Advanced Quantitative Methods at the University of Surrey, Department of Sociology. He holds the role of Professor of Criminology and Research Methods, with affiliations including the Surrey Centre for Criminology and editorial positions at journals such as Sociology and the Journal of the Royal Statistical Society Series A . His research focuses on improving crime measurement, multilevel modeling, Bayesian statistics, and the public understanding of science. He has led projects like the ADR UK Data First Evaluation Fellowship and Re-counting Crime, addressing issues like police under-counting and crime data reliability. He currently supervises PhD student Megan Georgiou and teaches on the MSc Social Research Methods program. His work bridges criminological theory and methodological innovation, with notable contributions to topics like hate crime impacts, prisoner reentry outcomes, and interviewer effects in surveys. He has served on the 2021 REF panel for Sociology and advisory groups for police funding formulas. Education: Holds a PhD in Sociology, with prior academic roles at the University of Warwick (Director of the Warwick Q-Step Centre). His research integrates quantitative rigor with real-world policy applications, particularly in crime prevention and data accuracy. Grants and Projects: Principal Investigator for projects such as 'Re-counting Crime: New Methods to Improve the Accuracy of Estimates of Crime' (ESRC, £299,261) and 'ADR UK Data First Evaluation Fellowship' (£177,202). Collaborations include work on synthetic crime data and carbon footprint analysis of crime prevention measures. Awards and Recognition: While no explicit awards are listed, his extensive editorial roles and leadership in high-impact research initiatives reflect his scholarly influence. Labs and Teams: Co-director of the Surrey Centre for Criminology and involved in cross-disciplinary teams analyzing crime data, survey methodology, and environmental criminology.

Official University Profile

Kajsa Hansen YangView profile

Professor

University of GothenburgSweden

Kajsa Hansen Yang is a Professor at the Department of Education and Special Education, University of Gothenburg. Her work focuses on school equity, achievement gaps, and the impact of social background on academic performance, with a particular emphasis on changes in the Swedish educational system over time. She specializes in quantitative research methods, including multilevel analysis, latent variable modeling, and structural equation modeling. Her research examines how educational policies, teacher practices, and socioeconomic factors influence equity in mathematics and science education across Nordic and international contexts. She has led projects like Research on Educational Outcomes (FUR) , School Segregation in Sweden (SSIS) , and Quantitative Research Methods in Education (QRM) , often analyzing large-scale datasets (TIMSS, PISA, PIRLS) to explore global trends in educational inequality. Recent publications highlight her focus on academic resilience, teacher quality, and methodological rigor in international comparative studies. Her work appears in journals like European Journal of Psychology of Education , Studies in Educational Evaluation , and ZDM - the International Journal on Mathematics Education , with key themes spanning from classroom dynamics to systemic policy impacts.

Official University Profile

Atika KhuranaView profile

Associate Professor

University of OregonUnited States

Atika Khurana is an Associate Professor in the Counseling Psychology and Human Services Department at the University of Oregon's College of Education, and a Research Scientist at the Prevention Science Institute. Her work focuses on developmental-ecological approaches to adolescent risk-taking behaviors. Postdoctoral training (2010-2012): Annenberg Public Policy Center, University of Pennsylvania PhD (2010): The Ohio State University (Major: Human Development and Family Science, Minor: Quantitative Psychology) Her research examines: Self-regulation development in adolescents Media/technology effects on health behaviors Personality-risk interactions (impulsivity, sensation seeking) Longitudinal modeling of behavioral trajectories Parenting behavior moderation Substance abuse prevention Recent publications analyze adolescent risk behaviors through the lens of media exposure, peer influences, and neurocognitive development, employing advanced statistical methods like latent variable modeling and multi-level analysis. Her work has been funded by NIDA, NICHD, and IES. NIDA Early Career Poster Award (2014) Distinguished Research Fellow, Annenberg Public Policy Center (2013) University of Oregon Faculty Research Award (2013) Dr. Khurana serves as Research Scientist at the Prevention Science Institute and will accept new PhD students in Counseling Psychology and Prevention Science in 2026-2027. Her methodological expertise includes missing data analysis, mediation models, and longitudinal research design.

Official University Profile

James TognoliniView profile

Professor

University of SydneyAustralia

Professor James Tognolini is a leading academic in educational measurement and assessment at the University of Sydney, serving as Director of the Centre for Educational Measurement and Assessment (CEMA). He holds adjunct roles at the University of Wollongong and the University of Western Australia. With a background spanning academia, government, and industry, his career includes leadership at Pearson and the Australian Council for Educational Research (ACER). His expertise centers on standards-referenced assessment, psychometrics, and leveraging data to improve educational outcomes globally. Educationally qualified with a BEd (UWA), MEd (Murdoch), and PhD (Murdoch), Tognolini’s research focuses on refining measurement models (e.g., Rasch Models), system-wide assessment frameworks, and teacher/data literacy. He has established assessment centers in institutions worldwide, including India, UAE, and China, and advised governments on educational policy and testing systems. His international engagements include keynote addresses in Singapore, Hong Kong, UAE, India, and South Africa, alongside collaborations with organizations like UNESCO and the Asian Development Bank. Current research explores data-driven leadership, teacher performance assessment, and cross-cultural educational measurement. Key grants include work on teacher quality indicators (NSW Department of Education) and online work-integrated learning equity (Curtin University). He supervises PhD students in areas like TESOL translanguaging, mathematics assessment reform, and teacher professional development. Tognolini is affiliated with the Pearson Psychometric Laboratory and has contributed to projects such as India’s Centre for Assessment, Evaluation and Research (CAER) and Jordan’s National Testing Strategy review. His work balances theoretical psychometrics with practical applications for systemic educational improvement.

Official University Profile

Borja MartinovicView profile

Associate Professor

Utrecht UniversityNetherlands

Borja Martinovic is an Associate Professor at the Department of Interdisciplinary Social Science, Faculty of Social and Behavioural Sciences, Utrecht University, and a member of the European Research Centre on Migration and Ethnic Relations (ERCOMER). His research focuses on group identities, immigrant integration, and intergroup relations in multi-ethnic societies. His research interests include cultural identity, immigration and migrant integration, interethnic attitudes, intra- and intergroup relations, prejudice, discrimination, ethnic conflicts, collective psychological ownership, national and religious identities, intergroup contact, and multilingualism. He employs advanced quantitative methods, including multilevel modeling and structural equation modeling, in his empirical studies. Borja Martinovic was awarded the European Research Council (ERC) Starting Grant for the OWNERS project (2017–2023) on collective psychological ownership and intergroup relations. He is currently a consortium member and work package leader in the Horizon Europe-funded CONCILIARE project (2024–2027) on changing colonial heritage in Europe. Endeavour Research Fellowship Award European Research Council (ERC) Starting Grant Member of the Utrecht Young Academy (UYA) He has supervised bachelor and master theses in the Migration, Ethnic Relations and Multiculturalism program and at University College Utrecht. He teaches courses such as Identity and Cultural Diversity and The Psychology of Ethnic Relations. He has not received any major grants beyond the ERC Starting Grant and current Horizon Europe project, and no specific PhD students are listed. He is actively involved in research through ERCOMER, contributing to both national and international collaborative projects on migration and social cohesion. His work bridges sociology and social psychology, focusing on identity formation and intergroup dynamics in diverse societies.

Official University Profile

Turgay Kerem KoramazView profile

Professor

Istanbul Technical UniversityTurkey

Prof. Dr. Turgay Kerem Koramaz is a faculty member at Istanbul Technical University, holding the academic rank of Professor in the Department of Urban and Regional Planning under the School of Architecture. He has served in administrative roles such as Deputy Head of Department (2018-2020) and Chairman of the Urban Planning Working Group (2015-2016), with visiting positions at the University of Sheffield (2015) and Royal Institute of Technology (2008). PhD in Urban and Regional Planning, Istanbul Technical University (2002) MA in Urban Design, Istanbul Technical University (1999) Licence in Urban and Regional Planning, Istanbul Technical University (1995) His research interests span Urban Planning , Information Technologies in Planning , Conservation , and Urban Archaeology , with a focus on heritage data platforms, urban regeneration, and socio-spatial inequalities. Recent work includes digital twin models for heritage sites , residential mobility under large-scale projects , and smart solutions for historical preservation . Key trends in his recent publications include heritage site monitoring (2025, 2023), urban food systems (2025), residential displacement (2023), and transport equity (2020). His work often integrates GIS , digital twins , and spatial analysis to address urban challenges. Scientific Awards TÜBİTAK Support and Award Programs to Encourage Participation in International Collaborations (2024) He has led projects such as the Spatial Segregation Characteristics of Household Housing Preferences (2018-2021) and contributed to international initiatives like Urban-Ist (2006-2012) and Solar Decathlon Europe 2021 . Contact: koramaz@itu.edu.tr

Official University Profile

Hans BaumgartnerView profile

Professor

Pennsylvania State UniversityUnited States

Hans Baumgartner is Smeal Chair Professor of Marketing at Pennsylvania State University, specializing in consumer psychology and research methodology. His work develops advanced measurement techniques for cross-cultural consumer research, including structural equation modeling approaches for scale validation and response bias correction. Professor Baumgartner's research examines pathological buying behaviors, cross-cultural response patterns, and pro-environmental decision-making. Recent publications focus on improving measurement validity in international marketing studies through methodological innovations addressing common method variance and careless responding. He has authored foundational texts on marketing measurement and serves on editorial boards of major marketing journals.

Official University Profile

Brian KellerView profile

Assistant Professor

University of Missouri , ColumbiaUnited States

Brian Keller is an Assistant Professor in the Department of Educational, School & Counseling Psychology at the University of Missouri's College of Education & Human Development. His research focuses on statistical methodologies, particularly missing data analysis, Bayesian statistics, structural equation modeling, and multilevel modeling. He is the developer of Blimp statistical software, which supports advanced statistical computing methods. Key areas of expertise include missing data imputation techniques, Bayesian computational methods, and the application of statistical models to educational and psychological data. His work emphasizes methodological innovation, software development, and the rigorous analysis of complex datasets. Recent research trends in his articles highlight advancements in latent variable modeling, nonlinear effects, and the integration of computational tools like Blimp. His contributions address challenges in multilevel models, missing data mechanisms, and model comparison criteria such as DIC and WAIC. No specific scientific awards are listed for Brian Keller in the provided information. His professional affiliations include the College of Education & Human Development and the Blimp Statistical Software initiative. He advises students in the department but no specific advisee names are provided. Research grants and funding details are not explicitly mentioned in the text. Blimp Statistical Software is a key collaborative project, reflecting his commitment to advancing statistical methods and software solutions for researchers.

Official University Profile

Seongho SongView profile

Professor

University of CincinnatiUnited States

Seongho Song is a Professor and Undergraduate Program Director in the Department of Mathematical Sciences at the University of Cincinnati. He holds a Ph.D. in Statistics from the University of Connecticut (2005). His research focuses on Bayesian statistical methods, biostatistics, and computational biology, with applications in genetics, environmental science, and healthcare. Song has led or collaborated on grants totaling over $4.7M, including projects funded by DARPA, NIH, and the Korea Institute of Ocean Science and Technology. Education: Ph.D. in Statistics, University of Connecticut (2005) Positions: Assistant (2005-2011) → Associate (2011-2019) → Full Professor (2019–Present) Research interests include Bayesian hierarchical models, longitudinal data analysis, and bioinformatics. He has published over 30 peer-reviewed articles in journals like Biostatistics , Frontiers in Genetics , and Journal of Productivity Analysis . Recent work involves modeling circadian rhythms, lung disease progression, and oceanographic systems. Teaching responsibilities include graduate courses in Bayesian analysis, statistical computing, and linear models. He has served on editorial boards for Sankhya Series B and IEEE Transactions on Computational Biology , and chairs the EAC-ISBA Special Interest Group.

Official University Profile

H. Metin AktulgaView profile

Associate Professor

Michigan State UniversityUnited States

H. Metin Aktulga is an Associate Professor in the Department of Computer Science and Engineering at Michigan State University's College of Engineering. His research focuses on high-performance computing, parallel algorithms, and numerical methods for large-scale scientific applications. He leads interdisciplinary projects involving collaborations with computational physicists and materials scientists to develop scalable software systems. His work includes the development of PuReMD, a reactive molecular dynamics code, and DOoC+LAF, a task-based middleware for data analytics. He explores parallel computing on emerging architectures, emphasizing energy efficiency and performance optimization. His research spans applications in molecular modeling, nuclear physics, and computational biology. Awards and grants are not explicitly listed, but his contributions are highlighted through collaborations with projects like MFDn (nuclear structure) and SHINES (electronic structure computations). He advises students in computational methods and leads efforts to automate force field optimization using machine learning and big data analytics. Labs and teams include the High-Performance Computing group at MSU, with active participation in interdisciplinary initiatives to bridge simulation and data-driven discovery in materials science and quantum systems.

Official University Profile

Leung TsangView profile

Professor

University of Michigan-Ann ArborUnited States

Leung Tsang is a Professor of Electrical Engineering and Computer Science at the University of Michigan, Ann Arbor, holding the Robert J. Hiller Professorship of Engineering. He received his SB, SM, EE, and Ph.D. from MIT. His academic career includes positions at Texas A&M University (1980-1983), University of Washington (1983-2014) as Professor and Department Chair (2006-2011), and a visiting Professorship at City University of Hong Kong (2001-2004). He has served as Editor-in-Chief of IEEE Transactions on Geoscience and Remote Sensing and President of the Electromagnetics Academy and IEEE Geoscience and Remote Sensing Society. His research focuses on microwave remote sensing , multiple scattering theory , electromagnetic wave propagation in random media , photonic crystals , and signal integrity . His work spans theoretical advancements (e.g., radiative transfer theory, UV multi-level methods) and practical applications (e.g., snow parameter retrieval, ocean foam modeling, via coupling analysis). Key trends include Development of computational techniques for large-scale scattering problems Integration of neural networks for inversion in remote sensing Investigation of backscattering enhancement and polarimetric signatures Notable awards include Fellow of IEEE and Optical Society of America William T Pecora Award (2012) Van De Hulst Light Scattering Award (2018) Membership in the National Academy of Engineering (2020) His group utilizes high-performance computing resources, including the Flux HPC cluster at the University of Michigan and XSEDE allocations, with specialized nodes for electromagnetic modeling. Current students include Ruoxing Gao (electromagnetic theory), Firoz Borah (snow remote sensing), Jongwoo Jeong (forest scattering), and Zhenming Huang (snow modeling).

Official University Profile