About
Hi! I’m Swen Kuh (last name pronounced as k-oo-h). My first name actually has two words and I’ve also published under F. Swen Kuh.
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Currently:
Senior Research Officer with the Ten to Men team at the Australian Institute of Family Studies (AIFS).
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Concurrently:
Research Associate at the Royal Melbourne Institute of Technology (RMIT) University working with Dr. Anna Zhu under an ARC Linkage Grant investigating “The Intended and Unintended Impact of Policy for Adaptive Policy Management”.
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Previously:
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Postdoctoral Research Fellow in Statistics at the University of Adelaide (and Monash University with the same collaborators) with Dr. Lauren Kennedy (Adelaide University), in collaboration with Assoc. Prof. Qixuan Chen and Prof. Andrew Gelman (Columbia University).
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In addition to my research, I was also a Teaching Associate at Monash University, co-lecturing Data Visualisation and Analytics to both undergraduates and Masters students at the Monash Business School, and I taught the Data Analytics Fundamental module as part of a Professional Enhancement Program in the Faculty of Arts.
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My PhD in Statistics was obtained from the Australian National University under the supervision of Prof. Grace Chiu (now at William & Mary) and Dr. Anton Westveld as an IBISWorld PhD scholar.
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In Aoteoroa New Zealand, I graduated with Honours in Statistics from University of Auckland (home of the R software!) working under COMPASS, a quantitative social science research institute and worked as a consultant, conducting qualitative interviews in market research companies.
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Research
Research interests:
- Bayesian inference and methods
- Social science applications
- Data visualisation
My general training have been in Bayesian inference and methods in applications to the social sciences. My methodological training include multilevel regression and poststratification (MRP) method, Bayesian hierarchical (or multilevel/mixed) modelling, spatial modelling and causal inference using countries’ socio-economic data while writing and coding up our own MCMC sampling methods. I also enjoy extracting insights from data and different ways of visualising the data and results.
Here are some of my documented work:
- Using leave‑one‑out cross validation (LOO) in a multilevel regression and poststratification (MRP) workflow: A cautionary tale — joint work with Lauren Kennedy, Qixuan Chen, Andrew Gelman (Statistics in Medicine).
- A holistic Bayesian framework for modelling latent socio-economic health — PhD thesis. On supervisory panel are Grace Chiu, Anton Westveld and Timothy Higgins.
- Latent Causal Socioeconomic Health Index. — joint work with Grace Chiu and Anton Westveld (in review).
- Modeling National Latent Socioeconomic Health and Examination of Policy Effects via Causal Inference. — joint work with Grace Chiu and Anton Westveld (preprint).
- Socio-economic position and mortality risks: a sibling approach Analysis using the New Zealand Longitudinal Census (NZLC) — supervised by Barry J Milne and Alan Lee
Posters:
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The Impact of a Regional Train Fare Cap Policy on Train Patronage — joint work with Lauren Kennedy and Anna Zhu. Presented at ESOBE 2025
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Joint modelling of multiple treatment variables for a single outcome: A Bayesian approach. — presented at Bayesian Nonparametric Workshop 2023, Monash University. Keywords: extended rank likelihood; copula; generalised propensity score; dose-response surface
- LACSH index: Modelling National Latent Socioeconomic Health and Examination of Policy Effects — presented at Australian Statistical Conference 2023, University of Wollongong. Keywords: latent health; hierarchical/multilevel model; spatial; causal
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Model-Based Socio-Economic Health Measures Using Causal Modeling — SPEED poster which won the inaugural poster competition of the Social Statistics Section at JSM (Joint Statistical Meeting) 2018 held in Vancouver, Canada.
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Latent Socio-Economic Health and Causal Modelling — presented at Bayes on the Beach 2017.
- Social Network Analysis on Food Web and Dispute Data — part of ANU summer research scholarship 2014/15.
Links
Some non-exhaustive list of links:
Statistics-related
Blogs:
- Xi' an's og
- Kaiser Fung's junk chart
- Statistical Modeling, Causal Inference, and Social Science (Andrew Gelman's blog)
Social science:
For learning:
I was involved in the Magellan Program teaching mathematics and statistics to talented years 7-10 students in Canberra, ACT and came across some useful resources: