Yi-Shin Lin

Ph.D.

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About Me

Quantitative researcher in psychological and educational measurement. Research Assistant Professor at the Centre for Information Technology in Education, Faculty of Education, The University of Hong Kong. I work on psychometric modelling (item response theory, cognitive diagnosis, Bayesian methods) for large-scale educational assessment. Earlier research: experimental psychology and open-source software for hierarchical Bayesian inference.

Contact Information

  • Location: Hong Kong

Expertise & Skills

Methods

Item response theory, cognitive diagnostic models, hierarchical Bayesian inference, generalised linear mixed and multilevel models; large-scale assessment data (TIMSS, PISA, ICILS, PIRLS, ICCS).

Programming

R (package development), C, C++/Rcpp, Python, MATLAB, CUDA; high-performance computing and reproducible analysis pipelines.

Professional Experience

Research Assistant Professor at The University of Hong Kong

April 2026–Current
  • Psychometric design and analysis for a longitudinal study of students' learning in a digital world (CITE, Faculty of Education).
  • Item response theory calibration, field-trial design and assessment-platform integration for school-based data collection.

Postdoctoral Researcher at National Academy for Educational Research, Taiwan

July 2025–December 2025
  • Bayesian cognitive diagnostic modelling for large-scale educational assessment, with open-source software (ggdmc).
  • Cross-national study of mathematics confidence in TIMSS across 49 countries (GLMM, Bayesian multilevel mediation).
  • Reproducible analysis infrastructure for TIMSS, ICILS, ICCS, PIRLS and PISA.

Research Fellow at University of Leeds

March 2020–September 2023
  • Laboratory and video-based naturalistic studies of road-user decision-making.
  • Stochastic differential equation software (C++ with an R interface) and toolkits for extracting traffic trajectories from video.
  • Machine-learning models of driver behaviour; student supervision and manuscript review.

Postdoctoral Research Fellow at University of Tasmania

September 2015–August 2018
  • High-performance computing software for hierarchical Bayesian inference, including parallel PDA estimation.
  • Managed an 8-GPU computing server for the lab's modelling work.
  • Bayesian inference workshops in Taiwan and Australia.

Achievements

PhD

University of Birmingham

Experimental Psychology. Thesis: a hierarchical Bayesian decision-making model of visual search.

Master of Arts

The City University of New York

Cognitive Neuroscience

BSc

National Taiwan University

Psychology. Dean's List.

Hobbies & Interests

Water sports, mountaineering and cycling; entry-level black belt in Shotokan karate.