Xiao HUANG

Assistant Professor Department of Computing HK Polytechnic University

I am leading the DEEP Lab at The Hong Kong Polytechnic University. We strive to develop effective algorithms for networked data to solve real-world prediction problems in social science, recommender systems, education, transportation, healthcare, etc. Our research interests span large language models, knowledge graphs, network analysis, recommender systems, and question answering. Open positions: I am actively recruiting Ph.D. students and postdocs (fully funded). Please feel free to drop me emails with your CV. Self-funded visiting students/scholars are welcome.

News and Highlights

• [2024/04] We have three papers accepted by IJCAI 2024
  

• [2024/01] We have two papers accepted by theWebConf 2024
  

• [2023/12] We will host a workshop at theWebConf2024
  

• [2023/12] We hosted a workshop at ICDM2023
  

• [2023/07] Our paper won Best Paper Award Honorable Mention at SIGIR 2023
  

• [2023/03] We hosted a workshop at WSDM2023
  

• [2022/11] Our paper has been selected as BEST PAPER presented at ICWL 2022
  

• [2022/07] Our ECS project, Error-Aware and Contrastive Knowledge Graph Learning, has been funded
  

Selected Publications (24 out of 72)

1. Shuang Zhou, Daochen Zha, Xiao Shen, Xiao Huang, Rui Zhang, Korris Chung, Denoising-Aware Contrastive Learning for Noisy Time Series, IJCAI, 2024

2. Xinrun Wang, Chang Yang, Shuxin Li, Pengdeng Li, Xiao Huang, Hau Chan, Bo An, Reinforcement Nash Equilibrium Solver, IJCAI, 2024

3. Pengdeng Li, Shuxin Li, Chang Yang, Xinrun Wang, Xiao Huang, Hau Chan, Bo An, Self-adaptive PSRO: Towards an Automatic Population-based Game Solver, IJCAI, 2024

4. Hao Chen, Yuanchen Bei, Qijie Shen, Yue Xu, Sheng Zhou, Wenbing Huang, Feiran Huang, Senzhang Wang, Xiao Huang, Macro Graph Neural Networks for Online Billion-Scale Recommender Systems, TheWebConf, 2024

5. Xuansheng Wu, Huachi Zhou, Yucheng Shi, Wenlin Yao, Xiao Huang, Ninghao Liu, Could Small Language Models Serve as Recommenders? Towards Data-centric Cold-start Recommendation, TheWebConf, 2024

6. Junnan Dong, Qinggang Zhang, Huachi Zhou, Daochen Zha, Pai Zheng, Xiao Huang, Modality-Aware Integration with Large Language Models for Knowledge-based Visual Question Answering, arXiv preprint arXiv:2402.12728, 2024

7. Qinggang Zhang, Junnan Dong, Hao Chen, Wentao Li, Feiran Huang, Xiao Huang, Structure Guided Large Language Model for SQL Generation, arXiv preprint arXiv:2402.13284, 2024

8. Zijin Hong, Zheng Yuan, Hao Chen, Qinggang Zhang, Feiran Huang, Xiao Huang, Knowledge-to-SQL: Enhancing SQL Generation with Data Expert LLM, arXiv preprint arXiv:2402.11517, 2024

9. Qinggang Zhang, Junnan Dong, Hao Chen, Daochen Zha, Zailiang Yu, Xiao Huang, KnowGPT: Knowledge Injection for Large Language Models, arXiv preprint arXiv:2312.06185, 2024

10. Hanyu Sun, Xiao Huang, Wei Ma, Beyond Prediction: On-street Parking Recommendation using Heterogeneous Graph-based List-wise Ranking, IEEE Transactions on Intelligent Transportation Systems, 2023

11. Shengyuan Chen, Yunfeng Cai, Huang Fang, Xiao Huang, Mingming Sun, Differentiable Neuro-Symbolic Reasoning on Large-Scale Knowledge Graphs, NeurIPS, 2023

12. Qinggang Zhang, Junnan Dong, Qiaoyu Tan, Xiao Huang, Integrating Entity Attributes for Error-Aware Knowledge Graph Embedding, TKDE, 2023

13. Qiaoyu Tan, Xin Zhang, Xiao Huang, Hao Chen, Jundong Li, Xia Hu, Collaborative Graph Neural Networks for Attributed Network Embedding, TKDE, 2023

14. Zirui Liu, Shengyuan Chen, Kaixiong Zhou, Daochen Zha, Xiao Huang, Xia Hu, RSC: Accelerating Graph Neural Networks Training via Randomized Sparse Computation, ICML 2023

15. Huachi Zhou, Hao Chen, Junnan Dong, Daochen Zha, Chuang Zhou, Xiao Huang, Adaptive Popularity Debiasing Aggregator for Graph Collaborative Filtering, SIGIR, 2023 (ACM version)

16. Feiran Huang, Zefan Wang, Xiao Huang, Yufeng Qian, Zhetao Li, Hao Chen, Aligning Distillation For Cold-start Item Recommendation, SIGIR, 2023 (ACM version)

17. Junnan Dong, Qinggang Zhang, Xiao Huang, Keyu Duan, Qiaoyu Tan, Zhimeng Jiang, Hierarchy-Aware Multi-Hop Question Answering over Knowledge Graphs, TheWebConf, 2023 (ACM version)

18. Qinggang Zhang, Junnan Dong, Keyu Duan, Xiao Huang, Yezi Liu, Linchuan Xu, Contrastive Knowledge Graph Error Detection, CIKM, 2022 (ACM version)

19. Kaixiong Zhou, Xiao Huang, Daochen Zha, Rui Chen, Li Li, Soo-Hyun Choi, Xia Hu, Dirichlet Energy Constrained Learning for Deep Graph Neural Networks, NeurIPS 2021

20. Kaixiong Zhou, Xiao Huang, Yuening Li, Daochen Zha, Rui Chen, Xia Hu, Towards Deeper Graph Neural Networks with Differentiable Group Normalization, NeurIPS 2020

21. Xiao Huang, Qingquan Song, Yuening Li, Xia Hu, Graph Recurrent Networks With Attributed Random Walks, KDD 2019 (Slides, Code)

22. Xiao Huang, Jingyuan Zhang, Dingcheng Li, Ping Li, Knowledge Graph Embedding Based Question Answering, WSDM 2019 (ACM version, Slides, Code)

23. Xiao Huang, Jundong Li, Xia Hu, Accelerated Attributed Network Embedding, SDM, 2017 (Full version, Slides, Code)

24. Xiao Huang, Jundong Li, Xia Hu, Label Informed Attributed Network Embedding, WSDM, 2017 (ACM version, Slides, Code)

Service

• PC member: ICLR 2022-2024, IJCAI 2020-2024, NeurIPS 2021-2023, AAAI 2021-2023, KDD 2019-2023, TheWebConf 2022-2023, ICML 2021-2023, CIKM 2019-2022, WSDM 2021-2023, SDM 2022, ICKG 2020-2021

• Reviewer: TPAMI (2023-), IEEE TKDE (2018-2023), ACM TKDD, ACM Computing Surveys, ACM TOIS, IEEE Transactions on Cybernetics, IEEE Transactions on Big Data, IEEE TCSS, ACM TIST, International Journal of Machine Learning and Cybernetics - Springer

• Session Chair: WSDM 2023, IJCAI 2023

• Editorial board member: Computers & Education: X Reality

• Topical Advisory Panel and Guest editor: Algorithms - MDPI

Awards and Patents

• Best Paper Award Honorable Mention at SIGIR 2023

• Best Poster Presentation Award at PolyU Academy for Interdisciplinary Research Conference 2023

• BEST PAPER at the International Conference On Web-Based Learning (ICWL 2022), Tenerife, Spain

• United States Patent, KNOWLEDGE-GRAPH-EMBEDDING-BASED QUESTION ANSWERING,
  US 2020/0242444 A1

• 2019 INFORMS QSR Best Student Paper Finalist, Seattle, USA

• 2019 INFORMS QSR Best Refereed Paper Finalist, Seattle, USA

• SDM 2017 Doctoral Forum Best Poster Runner-Up Award, Houston, USA

Talks

• [2023/03] Keynote on Machine Learning on Graphs on WSDM 2023 workshop, Singapore

• [2022/08] Talk on Trustworthy Graph Neural Networks on SMP 2022 workshop

• [2019/08] Tutorial on learning from networks on KDD 2019, Alaska

Background

I received Ph.D. from Texas A&M University in 2020, under the supervision of Dr. Xia Hu. I received M.S. from Illinois Institute of Technology in 2015, and B.S. from Shanghai Jiao Tong University in 2012. Before my current position, I worked as a research intern at Microsoft Research and Baidu USA.