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I am Dr. Hu Chuan-Peng, a faculty member of the School of Psychology, Nanjing Normal University.

Research

I am interested in how human beings process self-related social information, with a “3M” approach: meta-science, (cognitive) modeling, and (psychological) measurement. We are also trying to apply the “3M” approach to the mental health issues in the real world.

Open Datasets

Dataset 1: Data from the Human Penguin Project (data, data descriptor, original study).

Dataset 2: A dataset of cognitive ontology for neuroimaging studies of self-reference, which meta data extracted from all published fMRI studies that employed self-referential paradigm (dataset, data descriptor). These data can be used for coordinate-based meta-analyses of fMRI (e.g., Hu et al., 2016) or other purposes.

Dataset 3: A Chinese Social Evaluative Words List (data, preprint, code), which include Chinese words that describe people's appearance,socioeconomic status, sociability, competence, and morality.

Please see the website of my lab for more about my research.

Teaching

I am teaching three courses related to statistics.

2022 ~ currently, Advanced Psychological Statistics《高级心理统计学》 for undergrads. This course focuses Bayesian statistics, I used Bayes Rules! as the textbook but PyMC as the programming language. All slide are prepared using Jupyter Notebook and are avialable here. This course is in the autumn-winter semester.

2022 ~ currently, R for Psychological Research《R语言在心理学研究中的应用》 for graduate students. This goal of this course is introducing R language to more students in psychology. All slide are prepared using RMarkdown and are avialable here. This course is in the spring-summer semester.

2021 ~ 2023: Psychological Statistics《心理统计学》 for undergrads. All slide are prepared using RMarkdown and are avialable here. This course last for two semesters.

Open science

I support Open Science and co-found the Chinese Open Science Network, please see our position paper in AMPPS or book chapter.

Hu Chuan-Peng's Projects

bayeslmmtutorial icon bayeslmmtutorial

Tutorial files to accompany Sorensen, Hohenstein, and Vasishth paper: http://www.ling.uni-potsdam.de/~vasishth/statistics/BayesLMMs.html

chuan-peng.github.io icon chuan-peng.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

dartbrains icon dartbrains

This repository is a Python package with all of the functions and python libraries required for the Dartmouth fMRI Analysis Course taught by Prof Luke Chang, PhD.

dockerhddm icon dockerhddm

A docker image for running HDDM with parallel processing in jupyter notebook.

hddm icon hddm

HDDM is a python module that implements Hierarchical Bayesian parameter estimation of Drift Diffusion Models (via PyMC).

heterogeneityproject icon heterogeneityproject

Code and data for Heterogeneity Paper - Bolger, Zee, Rossignac-Milon, & Hassin (2019), Journal of Experimental Psychology: General

hssm icon hssm

Development of HSSM package

kabuki icon kabuki

Kabuki is a Python toolbox that allows easy creation of hierarchical Bayesian models for the cognitive sciences.

labmanual icon labmanual

Lab Manual for the Aly Lab at Columbia University

moral-dilemma icon moral-dilemma

PsychoPy implementation of the Harrison 2008 Moral Dilemma task.

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