PhD Candidate @ Purdue

I am Haoteng Yin (殷浩腾), a PhD candidate at CS@Purdue, supervised 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 privacy-preserving machine learning algorithms and applications in,

 CV  ·  Projects & Talks  ·  Google Scholar  ·  Github

Selected Publications [more]

* indicates equal contribution. 

[C1] Tianyi Zhang*, Haoteng Yin*, Rongzhe Wei, Pan Li, Anshumali Shrivastava. (2024) Learning Scalable Structural Link Representations with Bloom Signatures. In WWW'24. [Code]

[C2] 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]

[C3] 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]

[C4] 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]

[C5] Haorui Wang, Haoteng Yin, Muhan Zhang, Pan Li. (2022) Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks. In ICLR'22. [Code]

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

[W1] Prasita Mukherjee, Haoteng Yin. (2023) OCTAL: Graph Representation Learning for LTL Model Checking. In DLG-KDD'23. Workshop. (Contributed Talk)

[W2] Haoteng Yin, Yanbang Wang, Pan Li. (2020) Revisiting graph neural networks and distance encoding from a practical view. In DLG-AAAI'21. Workshop. [Code]

[W3] Rongzhe Wei, Eleonora Kreačić, Haoyu Wang, Haoteng Yin, Eli Chien, Vamsi K Potluru, Pan Li. (2023) On the Inherent Privacy Properties of Discrete Denoising Diffusion Models. In WSDAIF-ICAIF'23. Workshop. (Oral)

[C6] Wei Xiang*, Haoteng Yin*, He Wang, Xiaogang Jin. (2024) SocialCVAE: Predicting Pedestrian Trajectory via Interaction Conditioned Latents. In AAAI'24. [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]

[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

Research & Experience

Honors & Awards