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HAOTENG YIN

PhD in CS @ Purdue

I am Haoteng Yin (殷浩腾), a PhD in CS@Purdue, advised by Prof. Pan Li. Prior to this study, I attained MPhil in Data Science at Peking University and received BEng in Computer Science from Taishan College (honors school), Shandong University.

My research interests focus on efficient, scalable, and trustworthy learning algorithms and applications in,

- Computation & Learning on Graphs [C1-7, P1-2]
- LLMs & Foundation Models for Structured Data [C1, P1-3]
- Trustworthy ML (Privacy & Fairness) [P1-3]
- Spatiotemporal Data Analysis [J1, C7]

CV · Projects & Talks · YouTube · Github

Selected Publications [Google Scholar]

* indicates equal contribution.

[P1] Haoteng Yin, Rongzhe Wei, Eli Chien, Pan Li. (2024) Privately Learning from Graphs with Applications in Fine-tuning Large Language Models. In BuildTrust-ICLR'25. Workshop. [Poster, Code, News Article] (RCAC CI Symposium Best Poster Award)

[P2] Yinan Huang*, Haoteng Yin*, Eli Chien, Rongzhe Wei, Pan Li. (2025) Differentially Private Relational Learning with Entity-level Privacy Guarantees. [Code]

[P3] Rongzhe Wei, Peizhi Niu, Hans Hao-Hsun Hsu, Ruihan Wu, Haoteng Yin, Mohsen Ghassemi, Yifan Li, Vamsi K. Potluru, Eli Chien, Kamalika Chaudhuri, Olgica Milenkovic, Pan Li. (2025) Do LLMs Really Forget? Evaluating Unlearning with Knowledge Correlation and Confidence Awareness.

[C1] Haoteng Yin, Jinha Kim, Prashant Mathur, Krishanu Sarker, Vidit Bansal. (2025) How to Talk to Language Models: Serialization Strategies for Structured Entity Matching. In NAACL'25. Findings. [Poster, Code] (Intern Project@Amazon AGI)

[C2] Tianyi Zhang*, Haoteng Yin*, Rongzhe Wei, Pan Li, Anshumali Shrivastava. (2024) Learning Scalable Structural Link Representations with Bloom Signatures. In WWW'24. [Code]

[C3] Haoteng Yin, Muhan Zhang, Jianguo Wang, Pan Li. (2023) SUREL+: Moving from Walks to Sets for Scalable Subgraph-based Graph Representation Learning. In VLDB'23. [Code]

[C4] Haoteng Yin, Muhan Zhang, Yanbang Wang, Jianguo Wang, Pan Li. (2022) Algorithm and System Co-design for Efficient Subgraph-based Graph Representation Learning. In VLDB'22. [Code]

[C5] Rongzhe Wei, Haoteng Yin, Junteng Jia, Austin R. Benson, Pan Li. (2022) Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective. In NeurIPS'22. [Code]

[C6] Haorui Wang, Haoteng Yin, Muhan Zhang, Pan Li. (2022) Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks. In ICLR'22. [Code]

[C7] Bing Yu*, Haoteng Yin*, Zhanxing Zhu. (2018). Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting. In IJCAI'18. [Dataset (PeMSD7-M/L)] [Code]

[T1] Haoteng Yin, Beatrice Bevilacqua, Bruno Ribeiro, Pan Li. (2024) Enhancing Graph Representation Learning through Subgraph Strategies. In IJCAI'24. Tutorial Track. [Website][SubG Library]

[J1] Haoteng Yin, Yang Liu. (2017). Semantic analysis of spatial temporal trajectory in LBSNs. (in Chinese) SCIENTIA SINICA Informationis, 47(8), 1051-1065. (SMP'16 Best Paper Award)

Professional Service

Reviewer: [C] NeurIPS'22-25, ICML'22-25, ICLR'24-25, BigData'25 (PC), WWW'22 '24, LoG'22-23.

[J] Nature Machine Intelligence; ACM Transactions on Spatial Algorithms and Systems; IEEE Transactions on Neural Networks and Learning Systems, Cybernetics, Knowledge and Data Engineering, Internet of Things Journal, Intelligent Transportation Systems, Big Data, Information Forensics & Security, Emerging Topics in Computing, Signal Processing.

Volunteer: ICML'18, USRN'16, CIH A '16
Student Membership: AAAI, ACM, SIAM

Research & Experience

Aug 2019 ~ Graduate Assistantship, GCoM@CS, Purdue
May 2024 ~ Aug 2024 Applied Scientist Intern, AGI@Amazon
June 2023 ~ Sep 2023 Applied Scientist Intern, Search@Amazon
Oct 2016 ~ July 2019 Research Assistant, Center for Data Science, PKU
June 2018 ~ Sep 2018 Research Intern, École Polytechnique (Inria), France
Oct 2014 ~ Oct 2015 Research Assistant, Interdisciplinary Research Center, SDU

Honors & Awards

Best Poster Award at the 3rd Annual RCAC Cyberinfrastructure Symposium, W. Lafayette, USA
2023 - 2024 Purdue Teaching Academy Graduate Teaching Award (2%), W. Lafayette, USA
2024 AI 2000 Most Influential Scholar Award in AAAI/IJCAI (Honorable Mention, #60), AMiner.org
Top Reviewer (8%) Award at the 36th Conference on Neural Information Processing Systems (NeurIPS '22), New Orleans, USA
Purdue University Graduate School Summer Research Grants '21, W. Lafayette, USA
Peking University Academic Excellence Scholarship (~8%) '16 / '17 / '18, Beijing, China
Runner-up at the 9th Karakal Peking University Squash Open - Group B, Beijing, China
Extraordinary Potential Award (2/39) at the DiDi-IEEE Elite Forum 2018, Beijing, China
Best Paper Award (1/25) at the 5th National Conference of Social Media Processing (SMP '16), Nanchang, China

Contact

Address : RM3133, LWSN, 305 N. University Street, West Lafayette, IN 47907
E-Mail : yinht [AT] acm.org

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