about

Ruocheng Guo is a Staff Research Scientist at Intuit AI Research. His current research interest includes LLMs as causal world models, tool-using agents, LLM reasoning, and causal machine learning.

Prior to joining Intuit, he was a ML Researcher at TikTok/ByteDance Research (London) and an Assistant Professor at City University of Hong Kong. He earned his Ph.D. degree from the Data Mining and Machine Learning Laboratory (DMML) at Arizona State University, advised by Huan Liu, MSc degree from the beautiful HKUST and BEng degree from HUST.

Research Interests:

• LLMs (Text World Models, Tool-using Agents, Reasoning)
• Causal ML
• Data Mining

News

• 01/26 We are organizing the CausalBench Workshop @ WSDM’26 with ASU and Amazon. See you in Boise, Idaho!
• 12/25 Our paper Confidence-aware Fine-tuning of Sequential Recommendation Systems via Conformal Prediction won best student paper award in IEEE BigData’25
• 09/25 A paper accepted to Neurips’25
• 05/25 Invited to serve as Senior PC for CIKM’25 demo and resource tracks
• 03/25 Joined Intuit AI Research as a Staff Research Scientist
• Gave a talk at LinkedIn Market AI on LLM Agents slides, thank Dr. Liangjie Hong for the invitation
• 11/24 Invited to serve as PC co-chair of the industry track of IEEE DSAA’25
• 11/24 Invited by Dr. Jing Ma to give a guest lecture on conformal causal inference at Case Western Reserve University slides
• 10/24 A paper accepted to NeurIPS’24
• 08/24 Invited to present at 2nd Workshop on Causal Inference and Machine Learning in Practice @ KDD’24

Interested in Causal ML? Please find our papers and algorithm/data repositories.

• Survey Papers
  • Causal Interpretability for Machine Learning–Problems, Methods and Evaluation
  • A Survey of Learning Causality with Data: Problems and Methods
• Repositories
  • Algorithm Repository: Awesome-Causality-Algorithms
  • Data Repository: Awesome-Causality-Data

Experience:

• Staff Research Scientist, Intuit AI Research, March 2025 - Now
• Senior Machine Learning Researcher, ByteDance Research, June 2022 - Jan 2025
• Assistant Professor, City University of Hong Kong, Aug 2021 - June 2022
• AI Resident, Google X, Aug 2020 - Dec 2020
  • Mentor: Hongxu Ma
• Research Intern, Microsoft Research, May 2020 - Aug 2020
  • Mentor: Emre Kiciman, Pengchuan Zhang
• Research Intern, Etsy, May 2019 - Aug 2019
  • Mentor: Liangjie Hong, Xiaoting Zhao, Adam Henderson

Students and Interns (and papers co-authored with me)

• Maolin Wang (PhD Student@City University of Hong Kong, Co-supervised w. Xiangyu Zhao and Junhui Wang)
  • Too many to show here
• Zonghao Chen (PhD Student@UCL, Intern@ByteDance Research)
  • KDD’24
• Tongxin Yin (PhD Student@UMich, Intern@ByteDance Research)
  • ICLR’24
• Qing Zhang (PhD Student@HKUST, Intern@ByteDance Research)
  • KDD’23
• Xiaohui Chen (PhD Student@Tufts, Intern@ByteDance)
  • KDD’23
• Chentao Cao (PhD Student@HKBU, Intern@ByteDance Research)
• Sichun Luo (PhD Student@CityU, Intern@ByteDance)
• Xinjian Zhao (Master Student@CityU -> PhD Student@CUHK SZ)
• Jiansheng Li (Master Student@CityU -> PhD Student@CUHK SZ)