Leiden University

• Bhangale, Aditi Manoj: Latent variable models for prediction
• Brystowski, Zino: Stacked Domain Learning for Interdisciplinary Theory Development
• Kloos, Kevin: Improving the Accuracy of Aggregate Statistics with Quantification Learning
• Liu, Yuqi: Stepwise estimation approaches of growth mixture models
• Rieble, Carlotta: Early Warning Signals of Depression Onset
• Spadaccini, Giorgio: Enhancing the use and interpretation of tree-based prediction models

University of Amsterdam

• Bilici, Zeynep: Dependent effect sizes in meta-analytical structural equation modeling (MASEM)
• Boot, Jesse: Cascading Transitions in the psychosocial sciences (addiction)
• Ende, van den, Maarten: Computational modelling of psychological and social dynamics and urban mental health conditions
• Ertekin, Seyma:  Cognitive Modeling Meets Educational Data Science
• Groot, Lennert: Winner takes all: Applying MASEM with raw data”, part of the NWO VIDI research project “No data left behind. New meta-analytic structural equation models for complex data structures.
• Finneman, Adam: Theory Construction in Complex Psychological Systems
• Johansson, Annie: Optimizing Personalized Learning at Scale by Setting Up Failure for Success
• Jonge, Hannelies: Meta-Analytic Structural Equation Modeling with Group Data
• Keetelaar, Sara: Bayesian Psych:ometric Network Modelling for Longitudinal Data
• Kucharsky, Simon: Inferring cognitive strategies from eye movements: A Bayesian model-based approach
• Laskar, Pritam: Cascading Transitions in Learning
• Nak, Jason: Connecting Phenomena to Theories in Psychological Science
• Ron, de, Jill: A Formal Theory of Fear
• Smal, Iris: Cascading Transitions in Opinions
• Sekulovski, Nikola: Bayesian Psychometric Network Modelling for Cross-sectional Data
• Veldkamp, Karel: Towards Psychometrically Interpretable Neural Networks: Bridging the Gap between Latent Variable Models from Psychometrics and Neural Networks from Deep Learning
• Waaijers, Meike: AI-Assisted Network Construction Methods
• Wit, de, Kay: Defining intimidation: empirical evidence for an aggressive interpersonal phenomenon

University of Groningen

• Heister, Hannah: What is normal? Accurate norms and their use for psychological tests
• Linde, Maximilian: Back to Bayesics: Solving the Reproducibility Crisis in Biomedicine
• Peringa, Ilse Petra: Predicting Performance in the Complex Soccer Environment
• Petersen, Fridtjof: Stress in Action: Modeling and Predicting the effects of stress
• Rimpler, Alioscha: Model Complexity in Psychology
• Stadel, Marie: Capturing a Patient’s Context: Developing experience sampling tools for personalised patient feedback in psychotherapy
• Vries, de, Klazien: What is normal? Accurate norms and their use for psychological tests
• Zhang, Yong: Quality assessment of network models in clinical research and practice using predictive accuracy analysis

University of Twente

Tilburg University

• Bouma, Anouk: How trustworthy are simulation studies? A meta-research perspective
• Constantin, Mihai: Tools for Aiding Empirical Research Based on Intensive Longitudinal Data
• Failenschmid, Jan: Non-Linear Intensive Longitudinal Methods
• Goos, Cas: Improving the Robustness of Science using Evidence-Based Journal Level Interventions
• Hoesel, Tijn van: Spin – Questionable Research Practices in Scientific Reporting
• Kao, Hsin: SEM 2.0 – Towards personalized multi-disciplinary treatment plans
• Kolesnikova, Diana: Reasoning machine in social science
• Kretzler, Ben: Testing Causal Effects Variation
• Kuchina, Angelina: Psychometric innovations in monitoring learning progress in students
• Le, Tra: SEM 2.0: Towards personalized multi-disciplinary treatment plans
• Liu, Anne: Correcting for selectivity in datasets
• Norouzi, Rasoul: Reasoning machine in social science
• Peereboom, Sanne: Assessing the artificial mind through natural language processing and psychometrics
• Peng, Dennis: From Degrees of Freedom to Robustness: Strengthening the Evidence Base for Psychological Interventions
• Perez Alonso, Andres: Mixture multigroup Structural Equation Modeling for comparing latent variable relations among many groups
• Rüffer, Franziska: Moderator Analysis in Meta-Analysis
• Rein, Manuel: New SEM methods for validly comparing structural relations over individuals and time
• Schoenmaker, Martijn: Modeling Response Styles Behaviors in a Cross-cultural Context
• Sibbald, Lisette: Prevention is Better Than Cure: Predicting the Onset of Postpartum Depression Using Early Warning Signals
• Tkachenko, Irina: Addressing Validity Threats in Models with Response Times for International Large-Scale Assessment
• Willigers, Iris: Examining Variation in Causal Effects in Psychology
• Wong, Tsz Keung: Modelling Multiverses and Correcting for P-hacking
• Yang, Pengyuan (Travis): Embracing the complexity of contemporary research: The next generation of structural equation modelling tools

Utrecht University

• Andresen, Pia: Coming-of-Age of Process Research: Connecting Theory with Measurement and Modelling (OPTIMAL)
• Arts, Ingrid: Increasing MI by introducing webprobing into a BSEM
• Barragan Ibanez, Camila: Bayesian sample size calculation for trials with multilevel data
• Behbahani, Mohammad: Exploring Hidden Patterns in Relational Event History Data: an extension of Hidden Markov Model for the Relational Event Model
• Berkhout, Sophie: Intensive Longitudinal Methodology
• Carrière, Thijs: Data quality in app based data collection
• Chvojka, Edita: Rethinking Model Fit Guidelines for Longitudinal Structural Equation
  Modeling (LSEM) in Research on Youth
• Dvoriak, Vira: Advanced Network Approaches to Enhance Youth Mental Health
• Edmar, Alfons: Bayesian Evidence Synthesis for informative hypotheses: Aggregating evidence from conceptual replications
• Haqiqatkhah, Manuel: Methodology of Psychological Processes
• Leeuwen, van, Florian: Getting the best predictions from complex data sets: Balancing scalability and interpretability
• Leplaa, Hidde: Replication in the behavioural sciences
• Lösener,Ulrich: Bayesian Sample Size Calculation for Multilevel Trials
• Mildiner Moraga, Sebastián: The multilevel explicit-duration hidden Markov model for real time behavioural data
• Moazeni, Mehran: Developing and applying machine learning algorithms to improve prediction in patients with heart failure
• Mohammadi, Hadi: Explainable NLP with Human-AI Collaboration in Social Science
• Oberman, Hanne: Computational Evaluation for Dark Data Science
• Orrizonte, Giuliana: Accelerating the development of effective psychological treatments for traumatized refugees using Bayesian methodology
• Remmerswaal, Danielle: Push-to-app: Effective recruitment and retention in smart surveys
• Sayed, Khadiga: Studies into Non-Saturated Randomized Response Models
• Sukpan, Chuenjai: Inequality-constrained model selection (for dynamical models)
• Vink, Pepijn: Personalized depression dynamics in emerging adults: towards a real-time alert system
• Volker, Thom: Private yet accessible: advancing privacy-aware synthetization of sensitive microdata

KU University Leuven

• Chiara Carlier: Capturing similarity in multivariate dyadic time series: a statistical framework.
• Cloos, Leonie: Improving the measurement of mood and mood disorder
• Dickson, Shannon: Measuring the dynamic structure of affect
• Dou, Zhiwei: Statistical methods for intensive longitudinal dyadic data
• Guay, Jennifer Dang: Comparing Relations among Psychological Constructs Across Groups
• Ji, Yuanyuan: Using measurement bursts in ESM to capture affect regulation
• Kunc, Benjamin: Developing optimal experience sampling measures of psychological processes 
• Lin, Tzu-Yao: Can we trust our numbers? Quantification of measurement reliability for intensive longitudinal data
• Nowicki, Lucas: New structural equation modeling methods to find and account for measurement non-invariances
• Peeters, Lisa: Developing adaptive sampling schemes for improving the design of intensive longitudinal studies.
• Pihlajamäki, Milla: The Who, How, and What of Experience Sampling – Building an Evidence-Based Methodological Foundation for Experience-Sampling Research in Different Populations
• Piot, Maarten: Improving the user experience of the innovative blended care platform m-Path
• Revol, Jordan
• Szűcs, Tamás: Affectometrics – Examining and improving the validity of the measurement of affect
• Vermeiren, Hanke: Statistical /Psychometrical techniques for digital learning applications
• Wang, Shiyao: Statistical methods for capturing transmission and synchronization processes in triads
• Wu, Yufei: Validity of Self-Reported Affect Ratings
• Yao, Meijun: Capturing Relations among Psychological Constructs and Comparing Them Within Groups
• Yu, Kenny
• Zhao, Hongwei: Novel mixture SEM methods for comparing structural relations among many groups

Statistics Netherlands (CBS)

VU University Amsterdam

• Gómez-Echeverry, Santiago: Measuring the Quality of Big Data and Administrative Data

Maastricht University

Wageningen University

Erasmus University Rotterdam

In Memoriam

Janneke de Kort