Find Academic Supervisors

Steven Paul ReiseView profile

Research Professor

• Quantitative Psychology
• Latent Variable Modeling
• Structural Equation Modeling
• +3 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).

Chun WangView profile

Professor

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

• Numerical Cognition
• Delay of Gratification
• Metacognition
• +6 more

Professor Michael J. Beran is a faculty member at Georgia State University, specializing in Psychology and co-Director of the Language Research Center. His research explores numerical cognition, delay of gratification, metacognition, and cognitive control in humans, great apes, and monkeys. Department of Psychology, Georgia State University Co-Director, Language Research Center His work bridges comparative psychology and cognitive science, focusing on evolutionary aspects of quantitative sensitivity, self-control, and perceptual illusions across species. Recent studies address face pareidolia, reverse-reward contingency tasks, and individual differences in primate cognition. Publications from 2015 to 2025 highlight trends in animal cognition, mathematical operations by primates, and confidence assessment in memory tasks. Despite no listed awards, his editorial roles include Associate Editor for Comparative Psychology at Frontiers in Psychology .

Irwin EpsteinView profile

Professor

• Practice-Based Research
• Clinical Data-Mining (CDM)
• Social Work Professionalization
• +4 more

Irwin Epstein is a retired Professor and former Helen Rehr Chair in Applied Social Work Research (Health & Mental Health) at Hunter College School of Social Work, part of the City University of New York (CUNY). He held adjunct roles at Mount Sinai Medical Center’s Community Medicine Department and contributed to international programs like the International Enhancement of Leadership. His career spanned 50 years, including 13 years at the University of Michigan and sabbaticals at institutions such as Howard University and the University of Warwick. He specialized in practice-research integration, notably pioneering Clinical Data-Mining (CDM) to bridge clinical practice and academic research. Epstein’s research interests focused on transforming practitioners into researcher-practitioners through CDM, program evaluation, and clinical data systems. He authored/co-authored seminal works on CDM methodology, including books published by Oxford University Press and University of Sydney Press. His work earned accolades like the Miegunyah Distinguished Visiting Professor Award, the first social worker to receive it. He advised doctoral students at CUNY’s Graduate Center and mentored professionals globally through workshops in Australia, Finland, and other countries. His contributions to social work education and research continue to influence practitioner-research integration in healthcare and social services.

• Environmental Sustainability
• Children's Health
• Physical Activity Promotion
• +3 more

Dr. Clare Hume is a Senior Lecturer in the School of Public Health at the University of Adelaide, within the Faculty of Health and Medical Sciences. She serves as Program Director for the Honours program in the School and teaches courses in Infant, Child and Adolescent Health, and Communication for Health Sciences. Her research focuses on sustainable environments and children’s health, emphasizing physical activity promotion, reducing sedentary behaviors, and improving nutrition through innovative interventions in family, school, and community settings. She is an Editorial Board member for the American Journal of Health Promotion and Associate Editor for the Health Promotion Journal of Australia . Currently supervising two MPH students and an Honours student, her work bridges environmental sustainability and public health, particularly addressing waste reduction and healthy eating strategies. Key research themes include the impact of built environments on physical activity, interventions targeting screen-time reduction, and policy analysis for health and environmental co-benefits. Dr. Hume’s publications highlight school lunchbox innovations, community garden effects, and the Transform-Us! trial’s impact on children’s cardiometabolic health. Her contributions emphasize translational research to translate evidence into actionable strategies for healthier lifestyles and sustainable practices among children and families.

Serkan ArıkanView profile

Associate Professor

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

David ClingingsmithView profile

Associate Professor

• Economic History
• Social Economics
• Labor Economics
• +6 more

David Clingingsmith is an Associate Professor in the Department of Economics at the Weatherhead School of Management, Case Western Reserve University, where he has been faculty since 2007. His research integrates economic theory with empirical analysis across diverse domains including automation, entrepreneurship, and social behavior. Education: PhD in Economics, Harvard University (2007) MA in Anthropology, University of Chicago (1998) BA, University of Toronto (1994) His research program explores the socioeconomic impacts of technological change, particularly how automation transforms manufacturing work and entrepreneurship. He employs mixed methodologies spanning causal inference econometrics, lab/field experiments, and qualitative analysis, with recent work developing AI techniques for analyzing interview corpora. Current projects examine job design in craft entrepreneurship and historical automation effects. Publication trends reveal strong focus on automation's economic consequences (2022-2024), pitch dynamics in entrepreneurship (2018-2023), and crisis policy responses (2020). His work consistently bridges economic history with contemporary issues, showing particular interest in behavioral mechanisms underlying status, consumption, and charitable behavior. Scientific Awards: Academy of Management Prize for Best Paper in Organizational Neuroscience (2021) Academy of Management Lewis-Progressive Fellowship (2016) Weatherhead School of Management Explorations Prize (2009) Dr. Clingingsmith serves as reviewer for top journals including Journal of Political Economy and Quarterly Journal of Economics, and participates in institutional governance through the Academic Integrity Board. While no specific grants are detailed in source materials, his research appears in leading outlets like Management Science and Experimental Economics. He also contributed COVID-19 policy analysis through Economic Policy Ideas for COVID-19 initiatives. He collaborates with interdisciplinary teams including healthcare economists (Helper, Shane) and development researchers (Khwaja, Kremer), and maintains an active ceramics practice at Brick Ceramic + Design studio since 2023.

Sanford R. StudentView profile

Assistant Professor

• Educational Measurement
• Psychometrics
• Quantitative Methods
• +3 more

Dr. Sanford R. Student is an Assistant Professor in the School of Education at the University of Delaware and a Resident Faculty member of the Data Science Institute. His research focuses on connecting psychometric methodologies with practical educational implications, particularly in academic growth measurement, large-scale science assessments, and instrument design. He holds a Ph.D. in Research and Evaluation Methodology from the University of Colorado Boulder (2023) and dual B.A.s in Philosophy and Computer Science from Brown University (2013). Dr. Student’s professional experience includes roles as a Research Associate at Lyons Assessment Consulting (2021–2023), Doctoral Researcher at the Center for Assessment Design, Research and Evaluation (2018–2023), and Lead Researcher for the American Bar Association’s Bar Exam study (2019–2020). Prior to academia, he worked as a Software Engineer at edX (2016–2018). His awards include selection for the 2020 AIR/NCES NAEP Data Training Workshop. Current research trends in his publications emphasize Bayesian methods, vertical scaling, and crosscutting concepts in science education. He actively contributes to educational policy discussions through work with state agencies and assessment developers. Dr. Student advises graduate students and collaborates on grants related to growth measurement and educational data systems. He is affiliated with the National Council on Measurement in Education and maintains a lab focusing on applied psychometric challenges in K-12 systems.

• Experimental Psychopathology
• Anxiety Disorders
• Obsessive-Compulsive Disorder (OCD)
• +7 more

Nader Amir, Ph.D. , is a Professor in the Department of Psychology at San Diego State University (SDTSU), College of Sciences. He is a leading researcher in experimental psychopathology, specializing in anxiety disorders, obsessive-compulsive disorder (OCD), and cognitive bias modification (CBM) interventions. His research focuses on understanding and modifying cognitive processes such as attentional and interpretation biases, with a strong emphasis on translating laboratory findings into scalable, computerized, and home-based clinical interventions. His work has demonstrated that attention bias modification (ABM) can be as effective as medication or CBT for social anxiety and has explored neural mechanisms like error-related negativity (ERN) and reward processing in anxiety and OCD. Dr. Amir's recent publications highlight his focus on adolescent mental health, neural biomarkers, and the development of novel neurocognitive therapeutics. His studies frequently employ electrophysiological (ERP) methods and are published in high-impact journals including Clinical Psychological Science , Psychophysiology , and Behaviour Research and Therapy . His research program reflects a clear trajectory toward identifying and targeting core mechanisms of anxiety and OCD using innovative, technology-driven approaches. He is actively funded by major agencies including the National Institute of Mental Health (NIMH) and private institutions, with grants supporting mechanistic studies of exposure therapy, neurofeedback, and large-scale effectiveness trials of remotely delivered interventions for anxiety and OCD. Dr. Amir mentors numerous graduate students and serves on multiple thesis committees, advising on topics such as anxiety, OCD, ecological momentary assessment, and neurocognitive mechanisms. He is also an active presenter at national conferences including the Association for Behavioral and Cognitive Therapies (ABCT) and the Association for Psychological Science (APS).

Chia-Yi ChiuView profile

Associate Professor

• Educational Measurement
• Nonparametric Cognitive Diagnosis
• STEM Assessments
• +3 more

Chia-Yi Chiu is an Associate Professor in Applied Statistics at Teachers College, Columbia University. She specializes in educational measurement and psychometrics, focusing on nonparametric cognitive diagnosis and small data applications in STEM assessments. Her work emphasizes real-time classroom monitoring and innovative algorithms for diagnostic testing. PhD: Quantitative Methodology, Measurement, and Evaluation (University of Illinois at Urbana-Champaign) MS: Statistics (University of Illinois at Urbana-Champaign) MA: Mathematics in Teaching (University of Northern Colorado) BS: Mathematics (National Taiwan Normal University) Her research advances classroom-level assessments through methods like the restricted DINA model and nonparametric CD-CAT, addressing challenges in small-sample settings. She collaborates widely, with notable contributions to Q-matrix theory and cognitive diagnosis algorithms. Recent publications explore method selections in cognitive diagnosis and Q-matrix optimization. Awards: John P. Yackel Professorship (2022-2024), Chancellor’s Scholar Award (2017-2022), and NCME Dissertation Award (2010). Dr. Chiu advises students on topics like diagnostic testing algorithms and adaptive assessment systems. Her grants include innovations in education technology and small-data psychometric methods.

Chan Jeong ParkView profile

Assistant Professor

• Vocational Psychology
• Positive Psychology
• Career Counseling
• +3 more

CJ Park is an Assistant Professor in the Department of Educational and Counseling Psychology, and Special Education at the University of British Columbia (UBC), Faculty of Education. A licensed psychologist with international experience, she previously served as Assistant Professor at New Mexico State University and maintains an active clinical and research practice from her Scarfe Library Block 280 office. Her academic credentials include: Bachelor of Psychology from the University of Hong Kong Master of Counseling Psychology from Ewha Womans University (South Korea) PhD in Counseling Psychology from the University of Missouri-Columbia (2021) Dr. Park's research integrates vocational and positive psychology with critical social justice frameworks, examining career development through lenses of diversity, critical consciousness, and cross-cultural identity. Her clinical work employs Interpersonal Psychotherapy and Multicultural-Feminist Therapy to address systemic barriers in educational and career settings. Analysis of her 15 recent publications reveals dominant themes in career psychology (particularly STEM pathways for women of color), microaggression dynamics, and health behavior intersections with sleep/alcohol use. Her work consistently centers marginalized populations while advancing measurement tools like the Career Futures Inventory. Currently accepting graduate students for 2026-27, Dr. Park maintains active research collaborations across counseling psychology, education, and health sciences, with recent publications demonstrating interdisciplinary grant-funded work on social determinants of health and career development.

• Cognitive Science
• Psycholinguistics
• Multilingualism
• +4 more

Jon Andoni Duñabeitia is a Full Professor at the School of Languages and Education of Universidad Nebrija in Madrid. He serves as Director of the Centro de Investigación Nebrija en Cognición (CINC) and the International Chair in Cognitive Health . With an h-index of 43 (Scopus), he has published 170+ articles across psycholinguistics, multilingualism, cognitive training, and virtual reality applications in education. His research examines how language processing interacts with cognitive load, emotional modulation, and technological innovation. Principal Investigator for 8+ projects funded by Spanish Government, Basque Government, BBVA Foundation Associate Editor and Editorial Board Member of high-impact journals Recognized among Spain's top 3% scientists across all disciplines Recent publications span topics including: Second-language reading dynamics in VR environments Multilingual cognitive interactions in neurological conditions Emoji/typographic effects on word processing Computerized cognitive assessment and training systems He actively contributes to scientific meetings as invited speaker across Europe, Asia, and Americas. His work bridges basic research in psycholinguistics with applied technologies for cognitive health.

• Sports Medicine
• Cardiovascular Health
• Health Services Research
• +7 more

Hilde Moseby Berge is an Associate Professor in the Department of General Practice at the University of Oslo. Her research focuses on cardiovascular health in athletes, injury and illness prevention in elite sports, and the psychological and social impacts of cardiac arrest survival among young exercisers. She has collaborated extensively with institutions like the Norwegian Olympic and Paralympic committees, contributing to longitudinal health monitoring programs for athletes. Her work includes evaluating automated external defibrillator (AED) availability in sports clubs and analyzing post-surgical outcomes for musculoskeletal injuries. Berge is also affiliated with the Clinical General Practice Research (Allmix) and General Practice Health Services Research (ALHF) groups, emphasizing her commitment to practical healthcare solutions. Key research themes include: 1) Cardiac events in sports contexts, 2) Health disparities affecting Paralympic athletes, and 3) Long-term health surveillance for Olympic/Paralympic participants. Her studies often use systematic reviews and multi-year cohort analyses, with findings published in journals like British Journal of Sports Medicine and Resuscitation . Berge’s contributions to healthcare systems include designing prevention protocols for sudden cardiac arrest and investigating bone density issues in elite Para athletes. She has co-authored over 15 peer-reviewed articles since 2014, addressing topics such as ECG interpretation in athletes, post-cardiac arrest quality of life, and the epidemiology of sports-related injuries. Her work bridges clinical research and real-world healthcare applications, particularly in sports medicine and emergency preparedness.

• Business Analytics
• Operations Research
• Machine Learning
• +5 more

Dr. Hong Ming Tan is a Senior Lecturer at the Department of Analytics and Operations, NUS Business School, and a Research Fellow at the Institute of Operations Research and Analytics (IORA) at National University of Singapore. He holds a PhD in Operations Research and Analytics (2021), MSc in Mathematics (2017), and BSc (Hons) in Applied Mathematics and Economics (2013) from NUS. Doctor of Philosophy, Operations Research and Analytics (2021) Master of Science, Mathematics (2017) Bachelor of Science (Hons), Applied Mathematics and Economics (2013) His research spans Business Analytics , Machine Learning , Operations Research , and Pharmacogenetics . Recent work includes: EcoVal Framework for efficient data valuation in ML Personalized Mental Health through adaptive testing and clustering Antibiotic Resistance modeling using antiresistic strategies CYP2D6 Methylation prediction for precision medicine His publications demonstrate expertise in ML optimization , healthcare informatics , behavioral analytics , and decision science . Current projects include AI-led Smart Data Centre Management and SIA Corp Lab research. He serves as Chair of the Department Finance Committee and advisor to student clubs like Business Analytics Consulting Team. His work addresses real-world challenges in industrial operations, healthcare diagnostics, and educational innovation.

Ulrich SchroedersView profile

Professor

• Psychological Diagnostics
• Technology-based Competency Diagnostics
• Measurement of Cognitive Abilities
• +5 more

Ulrich Schroeders is a Professor of Psychological Diagnostics at the University of Kassel, where he has been employed since October 2017. His work focuses on developing and validating psychological assessment tools, with particular expertise in cognitive diagnostics and educational measurement. He teaches various programs for approximately 500 students annually and serves as a supervisor for teacher training students preparing for their oral state examinations in Pedagogy/Psychology. Dr. Schroeders earned his PhD from Humboldt University of Berlin in 2010 with a dissertation titled "Measurement of Cognitive Abilities Using Modern Technologies: Artifacts, Equivalence, and New Constructs." Prior to that, he completed his Diploma in Psychology at Julius-Maximilians-University Würzburg in 2004 with a thesis on diagnosing dyscalculia in first-grade students. His research spans several key areas in psychological assessment. He specializes in technology-based competency diagnostics, developing innovative methods for measuring cognitive abilities and school competencies. A significant portion of his work involves applying Machine Learning and metaheuristics to psychometric problems, particularly in structural equation modeling. His methodological expertise includes advancing techniques in Local Structural Equation Modeling (LSEM) and Meta-Analytic Structural Equation Modeling (MASEM), with applications across educational and clinical psychology contexts. Analysis of Dr. Schroeders' recent publications reveals a strong focus on computational approaches to psychological assessment. His work frequently employs optimization algorithms like Ant Colony Optimization and Bee Swarm Optimization to address challenges in test construction and validation. There's a clear trajectory toward game-based and technology-enhanced assessment methods, as seen in studies using Mastermind and Wordle as assessment tools. His research also demonstrates growing interest in applying machine learning to predict behavioral outcomes, including juvenile delinquency, suicide risk, and psychotherapy outcomes. Dr. Schroeders has secured significant research funding, including projects funded by the German Research Foundation (DFG) and the Hector Foundation. His current projects include "Facing the Replication Crisis in Machine Learning Modeling" (2025-2027) and "PINGUIN: Potenzialidentifikation IN der GrUndschule" (2024-2027), which focuses on identifying elementary students' initial competencies. He leads the development of the BEFKI assessment system (Berliner Test zur Erfassung fluider und kristalliner Intelligenz), which includes versions for different age groups (5-7, 8-10, and 11+). His methodological toolbox includes specialized approaches for test construction and validation, particularly focusing on optimization algorithms applied to psychological measurement problems.