Assistant Professor
Computing Department PolyU
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I am leading the DEEP Lab at The Hong Kong Polytechnic University. We strive to develop effective and efficient large language model (LLM)-based algorithms for real-world applications. Our research interests span graph retrieval augmentation, text-to-SQL, knowledge graphs, LLM evaluation, network analysis, and recommender systems.
[2024/09] We have three papers accepted by NeurIPS 2024
[2024/07] Welcome to attend our PhD Symposium at ICDE 2025
[2024/07] We released a survey of LLM-based text-to-SQL
[2024/05] We have three papers accepted by ACL 2024
Open positions: I am actively recruiting Ph.D. students and postdocs (fully funded). Please feel free to drop me emails with your CV.
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Selected Publications (12 out of 84)
Graph Retrieval Augmentation
KnowGPT: Knowledge Graph based PrompTing for Large Language Models, Qinggang Zhang, Junnan Dong, Hao Chen, Daochen Zha, Zailiang Yu, Xiao Huang, NeurIPS 2024.
Text-to-SQL based on LLMs
Next-Generation Database Interfaces: A Survey of LLM-based Text-to-SQL, Zijin Hong, Zheng Yuan, Qinggang Zhang, Hao Chen, Junnan Dong, Feiran Huang, Xiao Huang, arXiv.2406.08426, 2024.
Knowledge-to-SQL: Enhancing SQL Generation with Data Expert LLM, Zijin Hong, Zheng Yuan, Hao Chen, Qinggang Zhang, Feiran Huang, Xiao Huang, ACL Findings, 2024.
Structure Guided Large Language Model for SQL Generation, Qinggang Zhang, Junnan Dong, Hao Chen, Wentao Li, Feiran Huang, Xiao Huang, arXiv:2402.13284, 2024.
Knowledge-Graph-based Question Answering
Cost-efficient Knowledge-based Question Answering with Large Language Models, Junnan Dong, Qinggang Zhang, Chuang Zhou, Hao Chen, Daochen Zha, Xiao Huang, NeurIPS 2024.
Modality-Aware Integration with Large Language Models for Knowledge-based Visual Question Answering, Junnan Dong, Qinggang Zhang, Huachi Zhou, Daochen Zha, Pai Zheng, Xiao Huang, ACL, 2024.
Hierarchy-Aware Multi-Hop Question Answering over Knowledge Graphs, Junnan Dong, Qinggang Zhang, Xiao Huang, Keyu Duan, Qiaoyu Tan, Zhimeng Jiang, TheWebConf, 2023 (ACM version).
Knowledge Graph Embedding Based Question Answering, Xiao Huang, Jingyuan Zhang, Dingcheng Li, Ping Li, WSDM 2019 (ACM version, Slides, Code).
Graph Neural Networks
Macro Graph Neural Networks for Online Billion-Scale Recommender Systems, Hao Chen, Yuanchen Bei, Qijie Shen, Yue Xu, Sheng Zhou, Wenbing Huang, Feiran Huang, Senzhang Wang, Xiao Huang, TheWebConf, 2024 (ACM version).
RSC: Accelerating Graph Neural Networks Training via Randomized Sparse Computation, Zirui Liu, Shengyuan Chen, Kaixiong Zhou, Daochen Zha, Xiao Huang, Xia Hu, ICML 2023.
Adaptive Popularity Debiasing Aggregator for Graph Collaborative Filtering, Huachi Zhou, Hao Chen, Junnan Dong, Daochen Zha, Chuang Zhou, Xiao Huang, SIGIR, 2023 (ACM version).
Towards Deeper Graph Neural Networks with Differentiable Group Normalization, Kaixiong Zhou, Xiao Huang, Yuening Li, Daochen Zha, Rui Chen, Xia Hu, NeurIPS 2020.
Service
Organization committee member: ICDE 2025 (PhD Symposium Chair)
PC member: ICLR 2022-2024, IJCAI 2020-2024, NeurIPS 2021-2024, 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, IEEE TKDE, ACM TKDD, ACM Computing Surveys, ACM TOIS, IEEE Transactions on Cybernetics, IEEE Transactions on Big Data, IEEE TCSS, ACM TIST
Session Chair: WSDM 2023, IJCAI 2023
Editorial board member: Computers & Education: X Reality
Awards and Patents
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.
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