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Dr. Daniel J. Bauer is a Professor and Director of the Quantitative Psychology Program and L.L. Thurstone Psychometric Laboratory at the University of North Carolina at Chapel Hill. His research focuses on advancing quantitative modeling techniques for studying negative social behaviors, health outcomes, and psychopathology, with expertise in generalized and nonlinear latent variable models, including multilevel models, structural equation models, and mixture models. His work emphasizes methodological innovations such as Bayesian regularization, measurement invariance evaluation, and the integration of deep learning with psychometrics. Bauer advises doctoral students in quantitative psychology and collaborates with developmental psychology programs. He leads the Thurstone Laboratory, one of the oldest quantitative psychology training programs in the U.S., emphasizing rigorous methodological training and applications in behavioral sciences. Bauer’s research trends span computational advancements in latent variable analysis, regularization for bias detection, and dynamic modeling of developmental processes. His advising includes over a dozen doctoral students now in academia and industry roles. He contributes to labs and initiatives like the Center for Developmental Science, advancing interdisciplinary research in psychological measurement and intervention evaluation.

• Quantitative Psychology
• Latent Variable Models
• Developmental Psychopathology
• +6 more

Timothy Riley is a Professor in the Department of Mathematics at Cornell University, affiliated with the College of Arts and Sciences. His research focuses on geometric group theory, studying infinite discrete groups through geometric lenses such as Riemannian manifolds, graphs, and cell complexes. Key interests include curvature, geometric features of group presentations, and algorithmic complexity. He holds a D.Phil. from Oxford University (2002). Research spans geometric aspects of the word problem, hyperbolic groups, Dehn functions, and applications to cryptography and topology. His work integrates algebraic, topological, and computational perspectives. Notable collaborations include studies on hydra groups, Cayley graphs, and asymptotic cones. Publications emphasize geometric topology and group theory, with contributions to understanding filling invariants and geometric algorithmic properties. His office is 403 Malott Hall, and he maintains an active personal web page. No explicit awards are listed in the provided text, though he was part of news items related to teaching honors in 2024.

• Geometric Group Theory
• Geometric Topology
• Algorithmic Complexity
• +3 more

Golnoosh Farnadi is an Associate Professor at the Department of Computer Science and Operational Research at the University of Montreal and an Assistant Professor at the School of Computer Science at McGill University. She holds a Canada-CIFAR Chair in Artificial Intelligence and serves as a Senior Academic Member at Mila - Quebec Institute for Artificial Intelligence. Her interdisciplinary work bridges computer science, operations research, and ethical AI considerations. Her educational background includes a Ph.D. in Computer Science from KU Leuven and Ghent University (2017), followed by postdoctoral positions at the University of Montreal/MILA (2018-2020) and the University of California, Santa Cruz (2017-2018). Her research focuses on algorithmic fairness, responsible AI, deep learning, and probabilistic models, with applications spanning healthcare, recommender systems, and public policy. Farnadi's recent publications demonstrate a strong emphasis on addressing fairness in machine learning systems, with particular attention to cultural diversity in recommender systems, fairness in healthcare optimization (particularly kidney exchange programs), and mitigating hallucinations in large language models. Her work consistently combines theoretical rigor with practical applications, often employing novel mathematical frameworks to tackle complex ethical challenges in AI. Among her notable recognitions are the Google Scholar Award (2021), Facebook Research Award (2021), Google Award for Inclusion Research (2023), and being named one of the 100 Brilliant Women in AI Ethics (2023). She was also recognized as a Rising Star in AI Ethics in 2021. Farnadi supervises numerous graduate students through her EQUAL Lab (EQuity & EQuality Using AI and Learning algorithms), which focuses on developing AI systems that promote fairness and equity. Her teaching includes courses on Responsible AI, Machine Learning, and Trustworthy Machine Learning at both McGill University and HEC Montreal.

• Algorithmic Fairness
• Responsible AI
• Deep Learning
• +7 more

Michael C. Rodriguez is the Dean of the College of Education and Human Development (CEHD) at the University of Minnesota and holds the Campbell Leadership Chair in Education and Human Development. He has been a professor of measurement at CEHD since 1999. Education: PhD in Measurement & Quantitative Methods (Michigan State University), MA in Public Affairs (University of Minnesota Twin Cities), BA in Psychology (University of Minnesota Morris) His research focuses on test development , measurement accessibility , social-emotional learning assessment , and psychometric meta-analysis . He pioneered the use of item response models to evaluate equity in testing for students with disabilities and English language learners. Recent publications emphasize fairness in assessment , longitudinal SEL measurement , and foundational competencies in educational measurement . His work bridges psychometrics with socio-cultural youth development contexts. Scientific Awards: All My Relations Equity in Action Award (2022), C. Eugene Allen Award (2019), Robert H. Beck Teaching Award (2008) He chairs the Technical Advisory Group of the National Board of Professional Teaching Standards and contributes to the revision of the Standards for Educational and Psychological Testing . As founding director of the Minnesota Youth Development Research Group, he explores measurement frameworks for educational equity and youth wellbeing.

• Educational Measurement
• Test Development
• Measurement Accessibility
• +5 more

Justin Thaler is an Associate Professor in the Department of Computer Science at Georgetown University, researching algorithms and computational complexity with focus on probabilistic proof systems, verifiable computation, and streaming algorithms. Education: PhD Computer Science, Harvard University BS Computer Science and Mathematics, Yale University Research Interests: Develops protocols for verifying computations (including zero-knowledge proofs), analyzes the power of low-degree polynomials, and designs efficient streaming/sketching algorithms for large datasets. Publications: Research advances theoretical foundations of proof systems, with recent work on SNARKs, lookup arguments, and Fiat-Shamir security. Authored the monograph 'Proofs, Arguments, and Zero-Knowledge'. Advising & Labs: Advises PhD students in theoretical computer science. Contributes to open-source projects including DataSketches library of streaming algorithms. Currently on leave at a16z crypto research.

• Algorithms
• Computational Complexity
• Zero-Knowledge Proofs
• +3 more

Ji-young Shin serves as an Assistant Professor in the Teaching Stream within Education Studies at the University of Toronto Mississauga's Department of Language Studies. Her position integrates teaching, research, and practical application in language education with emphasis on assessment innovation and technology integration. Her academic credentials include: PhD in English / Second Language Studies & ESL from Purdue University, USA MS in Educational Psychology & Research Methodology from Purdue University, USA MA in Teaching English to Speakers of Other Languages (TESOL) from Hankuk University of Foreign Studies, South Korea BA in English Education (Japanese minor) from Hankuk University of Foreign Studies, South Korea Shin's research program focuses on language assessment, corpus linguistics, and technology-mediated pedagogy. She employs mixed methods with quantitative emphasis, utilizing corpus-informed computational analysis and latent-trait modeling complemented by qualitative discourse analysis. Her work addresses critical gaps in second language acquisition, educational measurement, and digital learning environments, particularly regarding AI applications and test validation across diverse language contexts. Her publication trajectory from 2017-2025 demonstrates consistent innovation in language assessment methodologies and technology integration. Key themes include AI-powered chatbots for L2 Korean instruction, online vocabulary testing for Spanish, and corpus-based writing pedagogy. Her work shows increasing focus on artificial intelligence applications and cross-linguistic validation studies, reflecting evolving priorities in language education research. Shin has secured competitive research funding including: Global Classrooms Grant (2025–2026) for VR-enhanced intercultural competence Black, Indigenous, and/or Racialized Scholar Grant (2025–2026) for cross-border AI language learning IRCC Engage3 Project (2022–2024) as Co-PI on VR/AI educational advancement Advancement Fund Plus (2022) for generative AI in teacher education British Council Award (2019) for technology-mediated assessment development She teaches advanced courses including 'The Future of Ed Tech: Active Learning Classrooms and Artificial Intelligence' (EDS285) and supervises community-based experiential learning (EDS388). Her grant portfolio indicates active supervision of research assistants and collaboration with international teams focused on AI implementation and assessment validation. Current projects explore generative AI for language learning across diverse contexts and virtual reality applications in teacher education. While specific laboratory infrastructure isn't documented, her collaborative publications with researchers across Korea, Spain, and the United States suggest participation in international research networks focused on language assessment technology and corpus applications.

• Language assessment
• Corpus linguistics
• Educational technology
• +4 more

Steven Paul Reise is a Research Professor in Quantitative Psychology at the University of California, Los Angeles (UCLA), where he has been a faculty member since 1998. He co-directs the Advanced Quantitative Methods training program, supporting graduate students in measurement, latent variable modeling, and modern experimental design. Dr. Reise earned his Ph.D. in Psychology from the University of Minnesota (1990), mentored by IRT pioneer David Weiss and personality researcher Auke Tellegen. Dr. Reise specializes in applying latent variable measurement models—including Structural Equation Modeling (SEM) and Item Response Theory (IRT)—to personality, psychopathology, and health outcomes research. His methodological work focuses on hierarchical models, MIMIC modeling, person-fit statistics, and bifactor modeling. He has been recognized with prestigious awards, including the Raymond B. Cattell Award (1998), UCLA Psychology Department Distinguished Teaching Award (2008), and University of California Campus-Wide Distinguished Teaching Award. His recent publications explore multidimensionality in SEM, bifactor modeling, person-fit indices, and applications to psychopathology and health outcomes. Dr. Reise collaborates on projects spanning gene-to-phenotype modeling, impulsivity, and advanced psychometrics. Scientific Awards : Raymond B. Cattell Award (1998), UCLA Psychology Teaching Award (2008), UC Campus-Wide Teaching Award, Outstanding Paper of the Year (2012).

• Quantitative Psychology
• Latent Variable Modeling
• Structural Equation Modeling
• +3 more

Chun Wang is a Professor in the Department of Measurement & Statistics at the University of Washington's College of Education. His research focuses on advancing quantitative methods in educational and psychological measurement, with expertise in item response theory (IRT), computerized adaptive testing (CAT), and cognitive diagnostic modeling. He holds affiliate faculty status at the Center for Statistics and the Social Sciences. Education: B.S. in Psychology, Peking University (China) M.S. and Ph.D. in Quantitative Psychology, University of Illinois at Urbana-Champaign Research Interests: Development and validation of multidimensional/mixture IRT models Computerized adaptive testing optimization Cognitive diagnostic modeling for classroom applications Health measurement and bias detection in assessments Recent Trends in Articles: His work bridges statistical innovation with practical applications, emphasizing fairness and efficiency in assessments. Notable areas include: - Healthcare : Predictive models for discharge disposition and functional outcomes - Education Technology : Adaptive learning systems and diagnostic feedback mechanisms - Methodology : Bias detection (DIF), Bayesian estimation techniques, and computational efficiency Scientific Awards : Includes the Anne Anastasi Award (2020), McKnight Presidential Fellowship (2017), and multiple best reviewer recognitions from leading psychometrics journals. Advising & Grants: Supervised students including Xiao J., Zhu R., and Lu J.* in high-impact projects. Co-led a $10M NIH grant (AmplifyGAIN Center) to advance Gen AI in STEM education. Published extensively in Psychometrika , Journal of Educational and Behavioral Statistics , and other top outlets. Labs/Teams: Directs the Pmetrics Lab ( https://sites.uw.edu/pmetrics/ ), collaborating on cutting-edge measurement tools for education and healthcare.

• Quantitative Research Methods
• Item Response Theory (IRT)
• Computerized Adaptive Testing (CAT)
• +3 more

Ethan McCormick is an Assistant Professor in the School of Education at the University of Delaware, specializing in longitudinal and psychometric modeling. He holds a Ph.D. in Psychology from the University of North Carolina at Chapel Hill (2020) and a B.S. in Biochemistry from the University of Arkansas (2013). His research focuses on integrating short-term and long-term longitudinal models to study behavioral and cognitive changes across the lifespan, with recent emphasis on educational data analysis and nonlinear random effects modeling. He is a Resident Faculty member of the University of Delaware’s Data Science Institute and previously served as an Assistant Professor of Methodology & Statistics at Leiden University (2022–2024). Dr. McCormick’s grants include the NWO Veni SSH Grant (2024–2027) for tracking educational outcomes via statistical modeling and the Jacobs Foundation Fellowship (2024–2026) for studying complex growth in math ability. His work bridges methodological rigor with applied neuroscience, examining brain-behavior relationships in developmental contexts through large-scale collaborations. Professional Experience : Assistant Professor, University of Delaware (2024–present); Assistant Professor, Leiden University (2022–2024) Key Research Themes : Longitudinal modeling, time series analysis, psychometrics, developmental cognitive neuroscience Awards : NWO Veni SSH Grant, Jacobs Foundation Fellowship His recent articles emphasize improving time-series methodologies, addressing limitations of two-time-point studies, and advancing models for asymmetric temporal dynamics. He collaborates internationally on projects simulating developmental datasets and analyzing neural correlates of behavior.

• Longitudinal Modeling
• Psychometric Modeling
• Developmental Cognitive Neuroscience
• +3 more

Prof. Dr. Steffi Pohl holds the Chair of Methods and Evaluation/Quality Assurance at the Faculty of Education and Psychology, Freie Universität Berlin since 2019. Previously, she was a Junior Professor (2013-2019) and researcher at institutions including Friedrich-Schiller University Jena and University of Bamberg. She earned her PhD in Psychometrics from Friedrich-Schiller University Jena (2010) and holds a Diplom in Psychology (2004) from Freie Universität Berlin. Her research focuses on advanced statistical methods in educational and psychological testing, including response time modeling, missing data mechanisms, and causal inference in assessment. She has pioneered work on test engagement detection via response patterns and log数据分析. Awards include the 2020 Psychometric Society Early Career Award and 2011 Gustav A. Lienert Dissertation Prize. Pohl serves on editorial boards of Psychometrika , Journal of Educational and Behavioral Statistics , and Zeitschrift für Psychologie . She chairs the Berlin School of Mind and Brain faculty and holds governance roles in academic senates. Her research projects include the National Educational Panel Study (NEPS) and collaborations on test design innovations. Current teaching includes advanced courses in empirical research methods, multivariate statistics, and educational measurement. She actively develops methodologies for analyzing log数据 from digital testing platforms and improving assessment reliability in large-scale studies.

• Psychometrics
• Log Data Analysis
• Missing Data Methods
• +4 more

Assoc. Prof. Dr. Serkan Arıkan is a faculty member at Boğaziçi University's Faculty of Education, Department of Mathematics Education. His research focuses on educational measurement, computerized adaptive testing, non-routine problem solving, and large-scale assessment frameworks like PISA and TIMSS. He has developed psychometric tools for STEM competency evaluation and conducted bias detection studies in international exams. Education : PhD in Secondary Science and Mathematics Education (METU, 2010), Postdoc (Tilburg University, 2015) Awards : Outstanding Achievement in Teaching Award (2021-2022) Research Trends : His recent work includes psychometric validation of self-compassion scales, extending the Community of Inquiry framework for technology integration, and adaptive test design using multiple matrix sampling. He investigates how socioeconomic factors, item bias, and emotional skills intersect with academic performance. Projects : Leads TÜBİTAK-funded AI-based test design and computerized adaptive mathematics test initiatives. Conductor of Boğaziçi University Adaptive Testing Laboratory.

• Educational Measurement and Evaluation
• Computerized Adaptive Testing
• Large-Scale Educational Assessments
• +5 more

Dr. Maria Bolsinova is an Assistant Professor at Tilburg University's Department of Methodology and Statistics within the Tilburg School of Social and Behavioral Sciences. Her work focuses on psychometrics, healthcare technology, and methodological advancements in educational and clinical assessments. She holds a PhD and has contributed to over 40 research outputs since 2013. Research interests include experience sampling, patient-friendly measurement designs, differential item functioning, and extreme response style correction. Her projects often involve collaborations with organizations like the OECD and Amplify Education Inc., focusing on adaptive learning systems and PISA studies. She developed a personalized missingness design to reduce patient burden in longitudinal studies, currently being implemented in the m-Path app. Consulting roles: Curriculum Associates, LLC (2024–2024); OECD (2023–present); Amplify Education Inc. (2023) Contributions to UN Sustainable Development Goals through methodological advancements in healthcare and education Dataset: 'Assessing Life Satisfaction in Everyday Life' (2023)

• Psychometrics
• Healthcare Technology
• Item Response Theory
• +7 more

GÜÇLÜ ŞEKERCİOĞLU is an Associate Professor at Akdeniz University, Faculty of Education, Department of Educational Sciences. Currently serving as Director of the Center for Measurement, Evaluation, Certification Research and Application and Director of the Institute of Educational Sciences since 2022, they also hold the position of Vice Dean of the Faculty of Education (2022-2025). Their academic career spans over 15 years at Akdeniz University, progressing from Research Assistant (2010-2011) to Assistant Professor (2011-2019) and currently Associate Professor (2019-present). Academic background includes: Doctorate (2003-2009): Ankara University, Institute of Educational Sciences, Measurement and Evaluation Postgraduate (1998-2001): Ankara University, Institute of Educational Sciences, Measurement and Evaluation Undergraduate (1993-1997): Ankara University, Faculty of Educational Sciences, Psychological Services in Education Dr. Şekercioğlu's research focuses on the intersection of psychometrics, educational measurement, and statistical analysis in educational contexts. Their work demonstrates deep expertise in measurement invariance, differential item functioning, scale development and validation, and advanced statistical methods in education. They have developed specialized knowledge in analyzing international assessments like PISA and TIMSS, with particular attention to cross-cultural measurement equivalence. Their research methodology combines rigorous quantitative approaches with practical applications in educational settings, contributing significantly to the understanding of how psychological constructs can be reliably measured across diverse populations. Analysis of their publication record reveals a strong emphasis on measurement theory and its practical applications in educational contexts. Their work consistently addresses critical issues in cross-cultural assessment, scale adaptation, and the psychometric properties of educational instruments. A notable trend is the application of advanced statistical techniques to solve practical measurement problems in education, particularly focusing on how tests function across different language groups and cultural contexts. They have made significant contributions to understanding measurement invariance in international assessments like PISA, with implications for fair and valid cross-national comparisons. Dr. Şekercioğlu has supervised 8 theses at various levels and serves on numerous doctoral and master's thesis committees. Their research is supported by multiple grants, including several TÜBİTAK projects addressing critical educational issues such as child sexual abuse prevention, nursing education assessment, and language acquisition among immigrant children. They actively contribute to the academic community through peer review activities for journals like Educational Sciences: Theory & Practice and Hacettepe Education Faculty Journal.

• Educational Measurement and Assessment
• Psychometrics
• Statistics in Education
• +6 more

Michael Russell is a Professor in the Department of Measurement, Evaluation, Statistics & Assessment at Boston College's Lynch School of Education and Human Development. His expertise spans educational measurement, systemic racism in testing, and accessibility in assessment design. He holds a Ph.D. and M.Ed. from Boston College and a B.A. from Brown University. Russell leads research addressing racism in educational measurement, including his book Systemic Racism and Educational Measurement (2023), which critiques the influence of systemic racism on testing practices. His work emphasizes anti-racist methodologies, intersectionality, and equitable assessment design. Key research interests include innovative uses of computer-based technologies, large-scale assessment design, and Universal Design principles. Russell has published extensively on topics like differential item functioning, deficit narratives in quantitative research, and the social justice implications of testing. He collaborates on redesigning graduate programs to prepare scholars for anti-racist research. His courses include Foundations in Research Methodology and Assessment Programs . Russell's work bridges critical theory with practical assessment tools, advocating for equitable educational practices.

• Educational Measurement
• Systemic Racism
• Social Justice in Education
• +5 more

Jared Izumi, Ph.D., is an Assistant Professor in the School Psychology program at the Attallah College of Educational Studies, Chapman University. He is also appointed to the faculty of the Ph.D. in Education program and serves as an associate researcher with FastBridge Learning. His professional credentials include being a licensed psychologist and a Nationally Certified School Psychologist, with prior practice experience in Missouri and California. University: Chapman University School: Attallah College of Educational Studies Department: School Psychology Academic Rank: Assistant Professor Dr. Izumi's research centers on school mental health, with a focus on universal screening for social-emotional and behavioral (SEB) risks. He investigates the psychometric properties of screening tools like the SAEBRS, particularly examining differential item functioning by race, gender, and grade level. His work also explores the effectiveness of dialectical behavioral therapy (DBT)-based social-emotional learning curricula in high schools and the use of virtual reality to assess SEL skills in youth. These efforts aim to improve early identification and equitable support for students at risk. His recent publications reveal a strong trend in educational assessment, particularly in SEB screening and reading interventions. He examines both behavioral and academic domains, emphasizing data-driven decision-making, equity in assessment, and personalized intervention strategies. His work often involves large-scale datasets and collaborative research with experts in school psychology and special education. Dr. Izumi has not been mentioned with specific scientific awards in the provided texts. However, his active research collaborations and publications in high-impact journals indicate scholarly recognition. He advises students within the School Psychology and Ph.D. in Education programs, though specific advisee names are not listed. His research has been supported through academic and research partnerships, including FastBridge Learning. His current projects include implementing universal screening systems and evaluating innovative SEL curricula. Dr. Izumi is involved in research teams focused on school-based mental health and academic interventions. His collaboration with FastBridge Learning suggests engagement with a larger research and assessment development team aimed at improving educational outcomes through evidence-based tools.

• School Psychology
• School Mental Health
• Social-Emotional Learning (SEL)
• +7 more