Honglin (虹霖) Bao
Innovation - AI - Computing and Society
I am a data science doctoral student at the University of Chicago, a scholar of AI + Innovation, and a computational social scientist. I am affiliated with the Knowledge Lab working with James A. Evans.
I am broadly interested in Generative AI and its societal impact. I build and use machine learning models, as well as a fair amount of econometrics and experiments. My work revolves around two main topics:
innovation, science, and (automated) discovery;
socially responsible AI, AI evals, and interpretable AI.
The research projects I lead have been published in leading venues in both computing and social sciences, including Nature Communications, Quantitative Science Studies, and WWW, among others.
Before Chicago I studied computer science and evolutionary biology at Michigan State, worked in the fintech industry, and did a research associateship in The Management Unit at Harvard Business School. Feel free to email me if you'd like to collaborate.
Recent News
[09-2025] New preprint on developing benchmark signatures to identify benchmark validity.
[06-2025] New preprint on scientific breakthroughs (deep learning) and the power structure of computer scientists.
[06-2025] My papers being presented at ICSSI 2025 and MMLS 2025.
[05-2025] One paper featured in ACM Showcases.
[05-2025] New preprint: LLMs surface the unwritten rules in scientific judgment.
[05-2025] New preprint: The missing vs. unused knowledge hypothesis in LLMs for technology judgment. Hugging Face page
[03-2025] One new paper on the diffusion of AI technology among global scientists accepted by Quantitative Science Studies.
[01-2025] One new paper on the diffusion of computational social science accepted by WWW.