Yidan Sun

Hi! My name is Yidan Sun, and I am a PhD student in the Daniel J. Epstein Department of Industrial & Systems Engineering at the Viterbi School of Engineering, University of Southern California. I am a member of the Artificial Intelligence and Complex Systems (AICS) group at USC Information Sciences Institute, working under the supervision of Dr. Mayank Kejriwal.

My research interests span network science, complex systems, computational social science, text analytics, and statistical modeling of network data. I am particularly interested in analyzing large-scale complex systems, with my current primary focus on using computational approaches to study human trafficking. My other ongoing research projects explore science of science topics, including collaboration networks focusing on scholarly publications and grant proposals, and broader social science topics, such as internal migration in the United States and financial inequities among vulnerable populations.

Prior to my doctoral studies, I earned my master’s degree in Analytics from USC in 2022 and my bachelor’s degree in Statistics from The Chinese University of Hong Kong, Shenzhen, in 2020.

Feel free to reach out to me at yidans@usc.edu / yidans@isi.edu

News

May 13, 2026: Our paper, “Structural modeling of campaign finance decisions in the U.S. House of Representatives,” was published in PLOS Complex Systems.
Mar. 26, 2026: Our paper, “Examining persistent inequities in financial complaint resolution for older Americans and veterans in the United States,” was published in PNAS Nexus.
Feb. 24, 2026: Our preprint, “Beyond the Star Rating: A Scalable Framework for Aspect-Based Sentiment Analysis Using LLMs and Text Classification,” is available on arXiv.
Nov. 6-9, 2025: Presented the poster, “Mapping Collaboration in AI-Driven Firms: A Co-Inventor Dataset (2020-2025),” at the International Conference of the Computational Social Science Society of the Americas (CSSSA) in Washington, D.C.
Sep. 3-5, 2025: Presented our abstract, “Reviewer Rating Variability and Confidence and Language Model Sentiment Prediction of Machine Learning Conference Papers,” at The 10th International Congress on Peer Review and Scientific Publication in Chicago, IL.
Jun. 23, 2025: Presented our abstract, “Collaboration Diversity and Paper Success: Network Analysis of Co-authorship in a Major Machine Learning Conference” virtually at The Annual International Social Networks Conference (Sunbelt) in Paris, France.
Apr. 30, 2025: Presented two papers at The 2025 ACM Web Conference in Sydney, Australia.
Apr. 11, 2025: Presented our work, “AI Reveals Systemic Financial Inequities: A Study of CFPB Complaints for Older Adults and Veterans” at USC’s ShowCAIS Symposium.
Mar. 11, 2025: Presented our work, “Understanding the Drivers of Human Trafficking Using Massive Multi-Partite Network Modeling and Analytics,” at USC’s Cloudwalkers Premiere.
Dec. 24, 2024: My study, “A Study of Firm-Switching of Inventors in Big Tech Using Public Patent Data,” has been published as Chapter 12 in Springer’s Social Network Analysis and Mining Applications in Healthcare and Anomaly Detection.
Sep. 3, 2024: Passed the ISE PhD screening exam with my presentation titled “Structural Modeling of Campaign Money Flow in the United States House of Representatives.”
May 2, 2024: Received the Jenny Wang Excellence in Teaching Award from the USC Viterbi School of Engineering.
Apr. 28, 2024: Honored as the Outstanding Teaching Assistant of the Year by the Daniel J. Epstein Department of Industrial and Systems Engineering.
Nov. 6, 2023: Presented two papers at The 2023 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining in Kusadasi, Turkey.
Nov. 4, 2023: A press article on our work about patent networks in Big Tech is published. Read: Big Tech Inventor Mobility Leads to Higher Productivity.