Computational Psychology &
Computational Methods Lab

Bennett Kleinberg

Computational methods · ML for behaviour · CSS foundations

Computational methods in psychology, machine learning for behavioural data, and methodological foundations of computational social science.

Riccardo Loconte

Opportunities and challenges of automated verbal deception detection

This project investigates how and to what extent computational approaches stemming from machine learning and natural language processing can advance verbal deception detection at large-scale.

Sanne Peereboom

Assessing the artificial mind through the marriage of natural language processing and psychometrics

My project is focused on understanding generative language models through psychological measurement frameworks. My work focuses on if – and how – psychometric approaches can be used to validly assess the behaviour of these models.

John Caffier

Computational methods to measure, understand, and influence prosocial behavior and trust

In our project, we apply and develop methods and tools to measure and model the dynamics of trust and prosocial behaviors - individually and at scale. Also, we explore how LLMs, apps, and other technologies, as well as humans, can actively influence these behaviors in potentially harmful or potentially constructive directions.

Rasoul Norouzi Nikjeh

Text-mining methods for theory development in psychological and social science research

My PhD project develops text mining methods to automatically detect and parse causal claims in social science texts. It turns unstructured prose into structured who-causes-what representations and encodes them as Directed Acyclic Graphs (DAGs). This lets researchers identify recurring causal patterns, generate testable hypotheses, and conduct transparent evidence synthesis and theory refinement.

Jennifer Chen

Adolescent-Specific Assessment and Psychotherapy (ASAP): Innovating Idiographic Methods for Youth-Tailored Care

Tijn van Hoesel

Spin: Questionable Research Practices in Scientific Reporting

Investigating the concept of spin (primarily found in biomedicine) and relating it to the concept of questionable research practices (primarily found in psychology). Investigating the prevalence and impact of spin in psychological research.

Weng Lam Ao

Understanding decision-making in transport behaviour through social media data

Lucca Pfründer

Human adversarial machine learning on text data for psychological inference

This project investigates how research designs from adversarial machine learning - when applied to NLP tasks, and when extended to human adversaries and human targets - can inform psychological theory for “wicked” problems such as deception.

Qian Chen

Decoding distorted interpretations of ambiguity from text data

Everyday life is full of ambiguous social situations, and biased / inflexible interpretations of these situations are linked to depression and anxiety. Our work focuses on leveraging linguistic indicators of interpretation processes to improve understanding, measurement, and intervention methods that are more ecologically valid and translatable to real-world mental health.

Nicola Rossberg

Ad-Hoc Machine Learning Explainability through Psychometrics

I aim to improve the quality of explanations generated by machine learning models through an interpretability by design approach. I am designing and testing a scale to measure understandability at feature level in order to favour understandable features during machine learning model training and hence create better explanations ad-hoc.

Jari Zegers

Psychological theories of deception and deception detection

As part of my master’s thesis, this project aims to improve our understanding of deception and deception detection from a psychological perspective.

Jonas Festor

Simulated vs. genuine empathy

This project tries to disentangle human perceptions of LLM generated empathetic text from the ‘objective’ convincingness. This study builds on and tries to extend the investigation of stochastic empathy.

Ivo Snels

Simulated vs. genuine empathy

This project tries to disentangle human perceptions of LLM generated empathetic text from the ‘objective’ convincingness. This study builds on and tries to extend the investigation of stochastic empathy.

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