Ruixuan Sun

Computer Science Ph.D. candidate @ University of Minnesota

GroupLens Research

Department of Computer Science & Engineering

U of Minnesota

Hi! This is Ruixuan(Sophia), a 5th-year Computer Science Ph.D. student working with Dr. Joseph Konstan at University of Minnesota. I earned my Bachalor’s Degree of Computer Science from Georgia Institute of Technology in 2019. After graduation, I’ve worked as a Software Engineer at Yelp for two years before starting my Ph.D. journey at UMN. During my PhD, I have the privilege to intern with Dolby Lab, Amazon, and Google.

I am on the job market looking for industry research and MLE positions starting in summer 2026. Would love to connect and learn more opportunities!

My research interests include: Human-centered AI, Social Computing, Recommender Systems, and Applied Machine Learning. In particular, I’m passionate about user interest modeling, behavior understanding, beyond-accuracy evaluation and optimization. I have expertise in mixed-method study design and extensive experience in running large-scale online field experiments powered by A/B tests. In general, I love training models and conducting user evaluation to understand how we can better serve human beings with AI-powered technology!

Please see my CV for more detailed experience.

news

Apr 28, 2025 Excited to present our paper “Multi-Prompting Scenario-based Movie Recommendation with Large Language Models: Real User Case Study” at CHI 2025!
Mar 24, 2025 Excited to present our long paper “Why They Come And Go: A Case Study of Productive Flyby Users and Their Rating Integrity Challenge in Movie Recommenders” at CHIIR 2025!
Oct 14, 2024 Happy to attend my third RecSys in Bari, Italy! I will present our work “AI-based Human-Centered Recommender Systems: Empirical Experiments and Research Infrastructure” at Doctoral Symposium; “Interactive Content Diversity and User Exploration in Online Movie Recommenders: A Field Experiment” at Women In RecSys session; and “What Are We Optimizing For? A Human-centric Evaluation of Deep Learning-based Movie Recommenders” at the IntRS workshop.
Jan 18, 2024 Excited to be the course instructor of CSCI 5115: UI Design, Implementation, and Evaluation course at UMN in Spring 2024!
Oct 1, 2023 Our paper, Interactive Content Diversity and User Exploration in Online Movie Recommenders: A Field Experiment is published on International Journal of Human–Computer Interaction!