Renjun Hu's Homepage

Short Bio

Renjun Hu received his Bachelor's degree in 2014 and Ph.D. in 2020 from the School of Computer Science and Engineering at Beihang University. From September 2017 to April 2018, he was a joint student in the Data Mining Group at Rutgers University. He then worked as a research intern at the Business Intelligence Lab of Baidu Research from May 2018 to September 2019. During 2020 to 2024, he served as an algorithm engineer at Alibaba Cloud, contributing to AI-driven transformations across various business domains including feed recommendation, user growth, online marketing, and LLM-as-a-Judge. Since January 2025, he has joined the School of Data Science and Engineering, East China Normal University as a junior researcher. His recent research interests include robust machine learning and the understanding, evaluation, and applications of large language models.

Publications (# indicates equal contribution)

Training an LLM-as-a-Judge Model: Pipeline, Insights, and Practical Lessons.
Renjun Hu^#, Yi Cheng^#, Libin Meng^#, Jiaxin Xia^#, Yi Zong^#, Xing Shi, and Wei Lin. The WebConf 2025 (WWW), 2025. (Industrial Track, oral)

PertEval: Unveiling Real Knowledge Capacity of LLMs with Knowledge-Invariant Perturbations. [codes and data]
Jiatong Li, Renjun Hu, Kunzhe Huang, Yan Zhuang, Qi Liu, Mengxiao Zhu, Xing Shi, and Wei Lin. The Thirty-eight Conference on Neural Information Processing Systems (NeurIPS), 2024. (Datasets and Benchmarks Track, spotlight)

CO3: Low-resource Contrastive Co-training for Generative Conversational Query Rewrite.
Yifei Yuan, Chen Shi, Runze Wang, Liyi Chen, Renjun Hu, Zengming Zhang, Feijun Jiang, and Wai Lam. Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (COLING), 2024.

A Progressively-Passing-then-Disentangling Approach to Recipe Recommendation.
Chunlai Dong, Haochao Ying, Renjun Hu, Yuyang Xu, Jintai Chen, Fuzhen Zhuang, and Jian Wu. IEEE Transactions on Multimedia (TMM), 2024. (Early Access)

Arithmetic Feature Interaction Is Necessary for Deep Tabular Learning. [codes]
Yi Cheng^#, Renjun Hu^#, Haochao Ying, Xing Shi, Jian Wu, and Wei Lin. The 38th Annual AAAI Conference on Artificial Intelligence (AAAI), 2024.

Robust Image Ordinal Regression with Controllable Image Generation.
Yi Cheng, Haochao Ying, Renjun Hu, Jinhong Wang, Wenhao Zheng, Xiao Zhang, Danny Z. Chen, and Jian Wu. The 32nd International Joint Conference on Artificial Intelligence (IJCAI), 2023.

Robust Training of Graph Neural Networks via Noise Governance. [codes]
Siyi Qian, Haochao Ying, Renjun Hu, Jingbo Zhou, Jintai Chen, Danny Z. Chen, and Jian Wu. The 16th ACM International Conference on Web Search and Data Mining (WSDM), 2023.

Competitive Relationship Prediction for Points of Interest: A Neural Graphlet Based Approach.
Jingbo Zhou, Tao Huang, Shuangli Li, Renjun Hu, Yanchi Liu, Yanjie Fu, and Hui Xiong. IEEE Transactions on Knowledge and Data Engineering (TKDE), 34(12): 5681-5692, 2022.

NCF: A Neural Context Fusion Approach to Raw Mobility Annotation.
Renjun Hu, Jingbo Zhou, Xinjiang Lu, Hengshu Zhu, Shuai Ma, and Hui Xiong. IEEE Transactions on Mobile Computing (TMC), 21(1): 226-238, 2022.

Incremental Spatio-Temporal Graph Learning for Online Query-POI Matching.
Zixuan Yuan, Hao Liu, Junming Liu, Yanchi Liu, Yang Yang, Renjun Hu, and Hui Xiong. The 30th Web Conference (WWW), 2021.

Self-Supervised Prototype Representation Learning for Event-Based Corporate Profiling.
Zixuan Yuan, Hao Liu, Renjun Hu, Denghui Zhang, and Hui Xiong. The 35th AAAI Conference on Artificial Intelligence, 2021.

Exploiting User Preference and Mobile Peer Influence for Human Mobility Annotation.
Renjun Hu, Yanchi Liu, Yanyan Li, Jingbo Zhou, Shuai Ma, and Hui Xiong. ACM Transactions on Knowledge Discovery from Data (TKDD), 14(6), 1-18, 2020.

Why We Go Where We Go: Profiling User Decisions on Choosing POIs. [NYC data]
Renjun Hu^#, Xinjiang Lu^#, Chuanren Liu, Yanyan Li, Hao Liu, Jingjing Gu, Shuai Ma, and Hui Xiong. The 29th International Joint Conference on Artificial Intelligence (IJCAI), 2020.

An Efficient Approach to Finding Dense Temporal Subgraphs. [codes and data]
Shuai Ma, Renjun Hu, Luoshu Wang, Xuelian Lin, and Jinpeng Huai. IEEE Transactions on Knowledge and Data Engineering (TKDE), 32(4): 645-658, 2020. (extended version of the ICDE 2017 paper)

Athena: A Ranking Enabled Scholarly Search System.
Junfeng Liu, Shuai Ma, Renjun Hu, Chunming Hu, and Jinpeng Huai. The 13th ACM International Conference on Web Search and Data Mining (WSDM), 2020. (Demo paper of ICDE'18)

A Collaborative Learning Framework to Tag Refinement for Points of Interest.
Jingbo Zhou, Shan Gou, Renjun Hu, Dongxiang Zhang, Jin Xu, Xuehui Wu, Airong Jiang, and Hui Xiong. The 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2019. (Applied Data Science Track)

Joint Representation Learning for Multi-modal Transportation Recommendation. [slides]
Hao Liu, Ting Li, Renjun Hu, Yanjie Fu, Jingjing Gu, and Hui Xiong. The 33rd AAAI Conference on Artificial Intelligence, 2019.

Query Independent Scholarly Article Ranking. [slides] [benchmark]
Shuai Ma, Chen Gong, Renjun Hu, Dongsheng Luo, Chunming Hu, and Jinpeng Huai. The 34th IEEE International Conference on Data Engineering (ICDE), 2018.

Fast Computation of Dense Temporal Subgraphs. [slides] [poster] [codes and data]
Shuai Ma, Renjun Hu, Luoshu Wang, Xuelian Lin, and Jinpeng Huai. The 33rd IEEE International Conference on Data Engineering (ICDE), 2017.

An Embedding Approach to Anomaly Detection. [slides] [poster] [codes]
Renjun Hu, Charu Aggarwal, Shuai Ma, and Jinpeng Huai. The 32nd IEEE International Conference on Data Engineering (ICDE), 2016.

Scaling up Link Prediction with Ensembles. [slides] [poster]
Liang Duan, Charu Aggarwal, Shuai Ma, Renjun Hu, and Jinpeng Huai. The 9th ACM International Conference on Web Search and Data Mining (WSDM), 2016.

Experience and Professional Services

Junior Researcher, East China Normal University, January 2025 - present
Algorithm engineer, Alibaba Group, July 2020 - January 2025
Research intern, Baidu Business Intelligence Lab, May 2018 - September 2019
Visiting student, Rutgers University, September 2017 - April 2018

Journal reviewers: IEEE Transactions on Big Data (TBD), IEEE Transactions on Cybernetics, IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Conference reviewers: AAAI 2021, IJCAI (2021-2025), ACL ARR (Feb 2025)

Honors and Awards

Excellent Graduate Student of Beihang University, 2020
Visiting Scholarship granted by China Scholarship Council, 2017
China National Scholarship for Graduates, 2017
WSDM Cup 2016 - Entity Ranking Challenge, 6/30 in the first round and the 2nd place (2/8) in the final ranking, 2016

Misc

My Google Scholar