Research Master's Student in Behavioural Science
Radboud University, Nijmegen
I study how decision-makers adapt to stochastic environments through continuous interaction. My work bridges computational cognitive modelling, risky decision-making, and dynamic systems—using tools like hierarchical Bayesian statistics, state-space models, and particle filters.
Course Project · Radboud University · 2026
Analyzed prediction market accuracy using 116,000+ resolved Polymarket markets from 2025. Evaluated forecast calibration across seven domains (Sports, Crypto, Politics, etc.) via Brier Score decomposition.
Master's Thesis · Radboud University · 2025 – present
Challenging the assumption of risk-taking as a static trait. Developed a computational pipeline using Auxiliary Particle Filters to recover individual trial-by-trial trajectories of latent risk sensitivity.
Research Project Co-Lead · Radboud University · 2024 – 2025
Engineered a continuous joystick-based Approach-Avoidance Task in PsychoPy with millisecond precision to investigate cognitive mechanisms underlying academic anxiety.
Position Paper (Course Project) · Radboud University · 2024
Proposed a predictive coding account to reconcile conflicting evidence on whether naming emotions dampens or intensifies them. Argued that prediction uncertainty is the key mechanism, modulated by label-experience intensity mismatch and labeling freedom.
Research Project Lead · Sun Yat-sen University · 2022 – 2024
Applied NLP to extract sentiment from 53,000+ crowdfunding texts. Constructed a novel Emotional Co-expression Network framework to quantify structural properties of emotional information.