Computational psychiatry & mental health

Understanding minds,
through computational science.

My name is Yuan Minghao (袁明昊). I am a Ph.D. student in the Depression and Anxiety Computational Neuroscience Lab (DACN Lab), mentored by Dr. Yujia Peng at Peking University. My research focuses on computational psychiatry and mental health, with particular interests in computational modeling, network analysis, and quantitative approaches to understanding human behavior and mental health. I am also interested in research methods on complex psychological systems, including causal inference, computational modeling, network science, behavioral data science, and large language model (LLM).

I welcome collaboration opportunities on research related to mental health, computational psychiatry, quantitative methods, LLM, and related interdisciplinary topics.

Education

Publications

† Equal contribution · * corresponding author. Full list on Google Scholar.

Projects

psychHypergraph

psychHypergraph implements information-theoretic hypergraph analysis for psychometric data, based on Marinazzo et al. (2024) and Possenti et al. (2026). The package provides tools for constructing psychometric hypergraphs, identifying synergistic and redundant higher-order interactions, centrality analysis, clustering, and visualization.
Project homepage →
View on GitHub →

Services

Teaching Experience

Awards & Honors

Blog · Notes

Getting started with psychHypergraph

An introductory guide to using psychHypergraph for psychometric hypergraph analysis in R.
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Meta-Analysis Tutorial in R

A Chinese Meta-analysis tutorial in R language, based on Doing Meta-Analysis with R: A Hands-On Guide.
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RStan: the R interface to Stan

Chinese translation of RStan: the R interface to Stan, a vignette providing an introduction to fitting a model in RStan.
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Interests

Get in touch

I welcome research collaborations in mental health, computational psychiatry, quantitative methods, and LLMs.

rheniumyuan@foxmail.com
Beijing, China

Last updated October 2026.