Hiπ! Iβm Xintong Li (ζ欣ζ‘). Iβm an undergraduate student in the Honors Talent Program in Statistics and Data Science at Renmin University of China. Iβm very fortunate to be advised by Prof. Xiao Zhou at the LUMOS AI Lab. I also have the incredible opportunity to work with fantastic mentors at Rutgers University. At the ARSENAL Lab, Iβm co-advised by Prof. Desheng Zhang, Prof. Guang Wang, Prof. Zhiqing Hong, and work closely with Zejun Xie. Additionally, Iβm grateful to be advised by Prof. Yifan Hu.
Starting in Spring 2027, I will join Carnegie Mellon University as a Ph.D. student, where I will be fortunate to work with Prof. Kun Zhang in the CMU CLeaR-Aether Group.
My research interests mainly lie in the intersection of Causal Inference and Discovery, Causal Representation Learning, and Spatio-temporal Modeling. I am excited about building theoretically grounded frameworks that work robustly in complex, real-world environments.
Feel free to email me if youβd like to connect!
ποΈ News
2026.04 β Iβm excited to share that I will join CMU as a Ph.D. student in Fall 2026, where I will work with Prof. Kun Zhang in the CMU-CLeaR Group π!
2026.01 β Our paper AtC was accepted to ICLR-26 π
π See you in Brazil π§π·!2025.11 β Our paper ST-HCM was accepted to AAAI-26!
π See you in Singapore πΈπ¬!2024.12 β I received the AAAI-25 Student Scholarship ($2000).
Feeling grateful and excited to attend AAAI again π₯°!2024.12 β Our paper FAP-CD was accepted to AAAI-25.
Looking forward to sharing our work with the community πΊπΈ!2023.09 β I joined LUMOS AI Lab at the GSAI, advised by Prof. Xiao Zhou.
This marked the beginning of my research journey π.
π Publications
* denotes co-first authorship.
AtC: Aggregate-then-Calibrate for Human-centered Assessment [PDF] [Code]
Zejun Xie*, Xintong Li*, Guang Wang, and Desheng Zhang.
The Fourteenth International Conference on Learning Representations (ICLR 2026).TL;DR: AtC aggregates human comparisons into a consensus and isotonic-calibrates any modelβs scores via the consensus, delivering decision-ready assessments with guarantees on efficiency, robustness, and optimality.
Spatio-Temporal Hierarchical Causal Models [PDF] [Code] [Poster] [Slides] [Video] Xintong Li, Haoran Zhang, and Xiao Zhou.
In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI 2026).TL;DR: We introduce Spatio-Temporal Hierarchical Causal Models (ST-HCMs) to perform causal inference from spatio-temporal data with unobserved, time-invariant confounders, a setting where traditional methods fail.
FAP-CD: Fairness-Driven Age-Friendly Community Planning via Conditional Diffusion Generation [PDF] [Code] [Poster]
Jinlin Li, Xintong Li, and Xiao Zhou.
In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI 2025).TL;DR: FAP-CD utilizes a conditioned graph denoising diffusion probabilistic model to learn the conditional joint probability distribution of aging facilities and their spatial relationships, and generates optimized spatial distributions of facilities.
π Education
Renmin University of China, Beijing, China (Sep. 2022 β Jul. 2026)
- Bachelor of Science in Statistics
- Honors Talent Program in Statistics and Data Science
β¨ Misc.
As a member of the Youth Volunteer Association, I organized the βReach Outβ project, a platform for international students to learn Chinese and explore local culture. π [Intro] [Summary] [Recruitment]
Iβm currently volunteer to help stray cats in my community. ππ₯° (Hereβs one of my buddies!)