College of Education and Human Development

Family Social Science

Xiaoran Sun

  • Pronouns: she/her/hers

  • Assistant Professor

Xiaoran Sun

Areas of interest

Technology and families
Adolescent mental health & well-being
Young adulthood
Educational achievement
Quantitative methods
Data science

Learn more at her Technology, Teens, and Families Lab

Degrees

Ph.D., Human Development and Family Studies, the Pennsylvania State University
M.S., Human Development and Family Studies, the Pennsylvania State University
B.S., Psychology, Zhejiang University, Hangzhou, China
 

Biography

Advising statement

As a developmental and family psychologist, I conduct research on the interplay between family systems processes and well-being across adolescence and young adulthood, situated in the larger socio-ecological context--including the cultural context and digital context. With my data science background, I am also interested in applying innovative methods and data to family and developmental research.

Currently, I study how adolescents and parents use smartphones, and how their digital behaviors influence their well-being and relationships. For this research, I use high-intensity, passive sensing data collected from participants' smartphones (every 5 seconds over up to 6 months) to objectively observe and examine their digital behaviors across multiple time-scales. This project is titled the Family Screenome Project, which is being conducted in collaboration with the Stanford Human Screenome Project. This work is supported by the University of Minnesota's Grant-in-Aid of Research, Artistry, and Scholarship. Here's more about this grant in this story

Further, I am also leading the research on applying machine learning to the analysis of large-scale, national longitudinal datasets to build predictive models based on adolescent experiences in predicting their developmental outcomes, including educational and career achievements and well-being. See a research article published on this topic. This work is supported by the Spencer Foundation. Read more about this work in this story

I strongly believe in team science and interdisciplinary collaborations. Beyond my appointment at Family Social Science, I am also a core faculty member at the Learning Informatics Lab in the College of Education and Human Development, and a faculty affiliate at the Data Science Iniative in the College of Science and Engineering and at the Minnesota Population Center.

Teaching and mentoring undergraduate and graduate students are extremely important to me.  I hope every student can walk out of my classroom by using the knowledge learned to be a better or happier partner, parent, caregiver, sibling, and/or friend. I see building agency and self-efficacy in students an important part of my teaching, especially for research methods classes. I believe it is important to create a supportive and inclusive classroom environment for students from diverse backgrounds to learn knowledge and skills. 

Publications

Selected publications

Sun, X. (2024). Supervised machine learning for exploratory analysis in family. Journal of Marriage and Family: Mid-Decade Special Issue on Theory and Methods. (online first). https://onlinelibrary.wiley.com/doi/10.1111/jomf.12973

McHale, S.M., Sun, X., Updegraff, K.A., & Whiteman, S.D. (2024). Patterns and correlates of changes in sibling intimacy and conflict from middle childhood through young adulthood. Developmental Psychology. (online first). https://doi.org/10.1037/dev0001750 (*co-first authors).  

Dworkin, J., Sun, X., LeBouef, S., & Keyzers, A. (2023). Associations among parent technology use, locus of control, and child problem behaviors. Family Relations, 72(2), 443-457.

Sun, X., Haydel, K. F., Matheson, D., Desai, M., & Robinson, T. N. (2023). Are mobile phone ownership and age of acquisition associated with child adjustment? A 5-year prospective study among low-income Latinx children. Child development, 94(1), 303-314. (Media mentions: Stanford Medicine NewsCTV NewsInc. MagazineFuturityCNN IndonesiaThe Good Men ProjectGigazine [in Janpanese]Before It’s News, reason)

Sun, X., Ram, N., Reeves, B., Cho, M.-J., Fitzgerald, A., & Robinson, T. N. (2023). Connectedness and independence of young adults and parents in the digital world: Observing smartphone interactions at multiple timescales using Screenomics. Journal of Social and Personal Relationships, 40(4), 1126–1150. https://doi.org/10.1177/02654075221104268

For the full list of Dr. Xiaoran's publications, please see her Google Scholar page

Presentations

Selected Talks:

Sun, X. (2024, May). Using Screenomics to Study Adolescents’ and Parents’ Smartphone Use and Well-being. Invited talk for the Health Psychology Interest Group (H-PIG), Department of Psychology, University of Minnesota, Minneapolis, MN.

Sun, X. (2024, May). Introduction to Machine Learning for Developmental Psychology and Family Research. Invited talk for the Department of Psychology and Behavioral Sciences, Zhejiang University, virtual.

Sun, X. (2023, June). Smartphone Behaviors and Youth Mental Health: Two Longitudinal Studies. Invited talk for the 3rd Wenqin Child Development Forum, Zhejiang University, Hangzhou, China.

Sun, X. (2023, April). Machine Learning for Human Development and Family Research. Talk for the Minnesota Population Center.

Sun, X. (2022, November). Machine Learning for Human Development and Family Research: An Overview and an Example. Talk for the Machine Learning Seminar Series, Data Science Initiative, College of Science and Engineering, University of Minnesota.

Sun, X. (2022, February). Introduction to Machine Learning for Human Development and Family Research. Talk delivered at NICHD SBSBeat (Social and Behavioral Sciences Branch Education and Training) Seminar.

Love, B. & Sun, X. (2021, July). Big Data & Data Mining Approaches for Psychology Research. Invited talk for the UCL (University College London)-PKU (Peking University) Summer School in Experimental Design in Psychology.

Sun, X. (2020, November). Introduction to Machine Learning for Family Research: Basic Concepts, Common Algorithms, and Application Examples. Workshop delivered at the National Council on Family Relations, virtual conference. (137 registered attendees).

Honors and Awards

2022 – 2024 Grant-in-Aid of Research, Artistry and Scholarship, University of Minnsota
2021 – 2022 Microsoft Azure Computing Award, Stanford Data Science
2020 – 2021 Scholarship, Stanford Data Science Scholars Program
2017 – 2018 Traineeship, Integrative Graduate Education and Research Training – Big Data Social Science (BDSS-IGERT) Training Program, National Science Foundation (Grant DGE-1144860) 2015 – 2016 University Graduate Fellowship, The Pennsylvania State University
2014 Li & Fung Scholarship, University of Hong Kong
2013 Outstanding Undergraduate Scholarship (First-class), Zhejiang University
2012 National Academic Scholarship, Ministry of Education of P. R. China