Hi, I am a first-year Ph.D. student at 
UNC-Chapel Hill advised by Prof. Zhun Deng. Before joining UNC, I completed my Master’s degree in Computer Science at 
Georgia Tech. I am also fortunate to collaborate with researchers of 
UIUC, 
Microsoft, and 
NEC Laboratories America. Currently, I study how foundation models reason, acquire supervision, and adapt through structured interaction—while remaining robust and trustworthy, with the goal of building scalable and reliable intelligent systems under real-world uncertainty.
I am actively seeking 2026 summer internships. If you have or know of any opportunities that align with my interests, I would be grateful if you could contact me at ruomeng@cs.unc.edu.
🔥 News
- [02/2026] New arXiv preprint: Rubrics as an Attack Surface: Stealthy Preference Drift in LLM Judges. [paper] [code]
- [02/2026] New arXiv preprint: Whom to Query for What: Adaptive Group Elicitation via Multi-Turn LLM Interactions. [paper] [code]
- [01/2026] I will serve as a reviewer for AIMS @ ICLR 2026.
- [01/2026] I will serve as a reviewer for ICML 2026.
- [01/2026] I will serve as a reviewer for KDD 2026.
- [11/2025] A paper is accepted by AAAI 2026 (Oral).
📄 Preprint
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Preprint Rubrics as an Attack Surface: Stealthy Preference Drift in LLM Judges, Ruomeng Ding*, Yifei Pang*, He Sun, Yizhong Wang, Zhiwei Steven Wu, and Zhun Deng [paper] [code]
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Preprint Whom to Query for What: Adaptive Group Elicitation via Multi-Turn LLM Interactions, Ruomeng Ding*, Tianwei Gao*, Thomas P. Zollo, Eitan Bachmat, Richard Zemel, and Zhun Deng [paper] [code]
📝 Selected Publications
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AAAI 2026 SkillGen: Learning Domain Skills for In-Context Sequential Decision Making, Ruomeng Ding, Wei Cheng, Minglai Shao, Chen Zhao (Oral) [paper] [code]
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ACL 2024 Everything of thoughts: Defying the law of penrose triangle for thought generation, Ruomeng Ding, Chaoyun Zhang, Lu Wang, Yong Xu, Minghua Ma, Wei Zhang, Si Qin, Saravan Rajmohan, Qingwei Lin, Dongmei Zhang [paper] [code]
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NeurIPS 2024 Regularizing Hidden States Enables Learning Generalizable Reward Model for LLMs, Rui Yang, Ruomeng Ding, Yong Lin, Huan Zhang, Tong Zhang [paper] [code]
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ESEC/FSE 2023 TraceDiag: Adaptive, Interpretable, and Efficient Root Cause Analysis on Large-Scale Microservice Systems, Ruomeng Ding, Chaoyun Zhang, Lu Wang, Yong Xu, Minghua Ma, Xiaomin Wu, Meng Zhang, Qingjun Chen, Xin Gao, Xuedong Gao, Hao Fan, Saravan Rajmohan, Qingwei Lin, Dongmei Zhang [paper]
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KDD 2023 Root cause analysis for microservice systems via hierarchical reinforcement learning from human feedback, Lu Wang, Chaoyun Zhang, Ruomeng Ding, Yong Xu, Qihang Chen, Wentao Zou, Qingjun Chen, Meng Zhang, Xuedong Gao, Hao Fan, Saravan Rajmohan, Qingwei Lin, Dongmei Zhang [paper]
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VLDB 2023 Imdiffusion: Imputed diffusion models for multivariate time series anomaly detection, Yuhang Chen, Chaoyun Zhang, Minghua Ma, Yudong Liu, Ruomeng Ding, Bowen Li, Shilin He, Saravan Rajmohan, Qingwei Lin, Dongmei Zhang [paper] [code]
💻 Internships
- 2024.05 - 2024.08, Microsoft Research, Redmond, WA.
- 2022.11 - 2023.08, Microsoft Research Asia, Beijing, China.
🎖 Honors and Fellowships
- Doctoral Merit Fellowship, University of North Carolina at Chapel Hill, 2025–2026
- Merit Scholarship, Georgia Institute of Technology, 2022-2023