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 machine learning algorithms and applications in,

 CV  ·  Projects & Talks · YouTube ·  Github

I am on the job market for a research position in industry or academia this Fall 2024. Please let me know if there is a good fit.

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 SFLLM-NeurIPS'24. Workshop. [Poster, Code, Media Coverage] (RCAC CI Symposium Best Poster Award)

[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. [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] Rongzhe Wei, Eleonora Kreačić, Haoyu Wang, Haoteng Yin, Eli Chien, Vamsi K Potluru, Pan Li. (2024) On the Inherent Privacy Properties of Discrete Denoising Diffusion Models. In TMLR'24.

[J2] 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

[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.

Research & Experience

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