Research
Research Interests
Humans understand the world by establishing entities, concepts, and their mutual connections. My research aims to understand human knowledge and teach machines to “understand” how the world is interconnected. To achieve this, I am conducting fundamental research in two primary areas:
Machine learning for structured/relational data
- Learning on graph-structured data [NeurIPS’22a,ACL’23,AAAI’24]
- Neuro-symbolic learning [NeurIPS’22b, ISWC’22, ICDE’24]: imposing structure and knowledge in machine learning
- Geometric representation learning [NeurIPS’22a, NeurIPS’22b, KDD’22], e.g., exploiting data geometry for machine learning
Neural & symbolic knowledge representation
- Knowledge graphs [KDD’22, ACL’23, AAAI’24]: embedding, construction, and reasoning
- Semantic web and ontologies [ISWC’22, ISWC’23]: Description logic and ontology reasoning
- Symbolic knowledge meets large language models [NAACL’24, Arxiv’24]: combining structured knowledge with language models
- Applications: healthcare, biomedicine, etc.
Selected Publications (google scholar)
Tutorial
-
CIKMReasoning beyond Triples: Recent Advances in Knowledge Graph EmbeddingsACM International Conference on Information and Knowledge Management 2023
-
KDDHyperbolic Graph Neural Networks: A Tutorial on Methods and ApplicationsThe 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2023
Preprint
-
arXivChatRule: Mining Logical Rules with Large Language Models for Knowledge Graph ReasoningarXiv preprint 2024
-
arXivHow Expressive are Spectral-Temporal Graph Neural Networks for Time Series Forecasting?arXiv preprint 2024
-
SurveyGeometric Relational Embeddings: A SurveyarXiv preprint 2023
Conference & Journal
-
NAACLzrLLM: Zero-Shot Relational Learning on Temporal Knowledge Graphs with Large Language ModelsAnnual Conference of the North American Chapter of the Association for Computational Linguistics 2024
-
ICDELogical Relation Modeling and Mining in Hyperbolic Space for RecommendationThe 40th IEEE International Conference on Data Engineering 2024
-
SIGIRHiPrompt: Few-Shot Biomedical Knowledge Fusion via Hierarchy-Oriented PromptingThe 46th International ACM SIGIR Conference on Research and Development in Information Retrieval-Short Paper 2023
-
ISWCTowards Statistical Reasoning with Ontology EmbeddingsThe 21st International Semantic Web Conference (Poster & Demo Track) 2023
-
ISWCCan Pattern Learning Enhance Complex Logical Query Answering?The 21st International Semantic Web Conference (Poster & Demo Track) 2023
-
WWWTime-Aware Entity Alignment using Temporal Relational AttentionACM The Web Conference 2022