RESPONSIBLE MACHINE LEARNING IN CHILD WELFARE AND DIGITAL MENTAL HEALTH - A DISSERTATION

Aug 2, 2026

A dissertation submitted to the University of Minnesota Graduate School presents an in-depth study of responsible machine learning in the context of child welfare and digital mental health. It frames technical work around ethical practice, human-centered considerations, and the responsible handling of sensitive, high-stakes domains. The document emphasizes mentorship, guidance, and scholarly collaboration that supported the research development from early exploration through publication. It concludes with formal acknowledgements and institutional requirements for the Doctor of Philosophy degree.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages294

Reading Time12 h 21 min

AccessFree to download

Acknowledgements

RESPONSIBLE MACHINE LEARNING IN CHILD WELFARE AND DIGITAL MENTAL HEALTH A DISSERTATION SUBMITTED TO THE FACULTY OF THE GRADUATE SCHOOL OF THE UNIVERSITY OF MINNESOTA BY Logan Stapleton IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY Haiyi Zhu, Zhiwei Steven Wu May, 2025 © Logan Stapleton 2025 ALL RIGHTS RESERVED Acknowledgements This PhD been quite an arduous journey. I couldn’t have done it without the support of many people in my life. First, I thank my undergraduate advisor, Diane Michelfelder. The first class I ever took in undergrad was Ethics and the Internet with Diane. Diane advised me. I took every class I could with her. I TAed for her whenever I could. I wrote my undergrad thesis with her. I did summer research on ethics of machine learning with her. And even now, long after I’ve graduated from college and she’s retired, we still regularly exchange long emails and meet to chat whenever we can. She’s offered me so much mentorship, guidance, and friendship throughout the last decade of my life. I can’t thank Diane enough for seeing me, caring about me, taking an interest in me and my education, and inspiring me to pursue a life and career that I model very much after her. Next, I thank my advisors, Haiyi Zhu and Steven Wu. I started this PhD about 6 years ago as a much younger, very different person. I remember emailing Steven on awhim in 2018 to see if he’d be interested in doing research with a recent graduate with no computer science degree and admittedly little actual knowledge of machine learning. At the time, I was working the dumbest job in the world. After work, I would take the train to a large concrete building to go to Steven’s nearly window-less office and work on proofs that turned into my first published paper. This also turned into a path towards a different direction in my life—a direction that I enjoy a whole lot more than working the dumbest job in the world. I thank Steven for giving me this opportunity. I also thank Steven for giving me the support and flexibility throughout my PhD to explore what I was interested in. After my first year, he asked me to join a side project asa middle author. That led to my second published paper. It led me to human-computer interaction, which was a different direction of research than I started my PhD on. And it led me to working with Haiyi as my advisor. I thank Haiyi. She has been an enormous support in my work and life for the past five years. She’s taught me how to combine my technical and humanistic interests in my work. She’s worked with me and pushed me to publish research that I feel proud of. She’s entertained most of my more stubborn ideas. Ultimately, she taught how to bethe researcher I am today. More importantly, though, she’s always shown me immense patience, kindness, and friendship through many moments of stress and personal turmoil over the past six years. Next, I thank everyone at GroupLens. After the lockdown portion of the pandemic was lifted, I was left with two advisors who lived across the country from me, who I only met with over Zoom. I was stressed and alone, left with little other PhD students to talk to. I thought very seriously about leaving my home in Minneapolis to move to Pittsburgh—at great personal sacrifice for myself and my partner. Fortunately, however, I went toa cookout at Joe Konstan’s apartment to introduce myself to GroupLens folks. I thank Loren Terveen for immediately offering me a desk in the lab (and for serving on my committee) . That desk became my home for the remainder of my PhD. I was introduced to Stevie, who took me in and acted as a close mentor and moreor-less de facto third advisor. I thank Stevie for her time, labor, guidance, and the scholarly community she included me in. Even when she had more than enough on her plate between her own advisees and her literal family, she took time to care for me. I also thank her for her friendship, laugh

FAQs

What is the document type and academic context?

It is a dissertation submitted to the University of Minnesota Graduate School in partial fulfillment of the requirements for the Doctor of Philosophy degree.

Who are the listed advisors?

The dissertation lists Haiyi Zhu and Zhiwei Steven Wu as advisors.

What themes are emphasized through the content provided?

The acknowledgements highlight ethical, human-centered guidance for research, particularly relating to machine learning in child welfare and digital mental health.

Aug 2, 2026

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