Kewei Cheng, Ph.D., is an applied scientist at Amazon. She earned her Ph.D. in Computer Science from UCLA in 2024. Her main research areas include graph and network mining as well as broader interests in data mining and machine learning. Dr. Cheng’s work has been featured in various prestigious conferences across multiple domains such as KDD, VLDB, WSDM, CIKM, AAAI, ICLR, EMNLP, and ACL.Yizhou Sun, Ph.D., is a Professor in the Department of Computer Science at UCLA. Her principal research interest is on mining graphs/networks and more generally in data mining and machine learning with a recent focus on deep learning on graphs and neuro-symbolic reasoning. Dr. Sun is a recipient of multiple Best Paper Awards, two Test of Time Awards, among many other awards. She has also served as organizers of top conferences in the field, such as KDD’23, ICLR’24, and KDD’25.

• Introduction.- Preliminaries on Knowledge Graph and Symbolic Logic.- Knowledge Graph Completion.- Complex Query Answering.-Logical Rule Learning.- Incorporating Ontology to Knowledge Graph Reasoning.- Conclusion and Research Frontiers.

Kewei Cheng, Ph.D., is an applied scientist at Amazon. She earned her Ph.D. in Computer Science from UCLA in 2024. Her main research areas include graph and network mining as well as broader interests in data mining and machine learning. Dr. Cheng’s work has been featured in various prestigious conferences across multiple domains such as KDD, VLDB, WSDM, CIKM, AAAI, ICLR, EMNLP, and ACL.Yizhou Sun, Ph.D., is a Professor in the Department of Computer Science at UCLA. Her principal research interest is on mining graphs/networks and more generally in data mining and machine learning with a recent focus on deep learning on graphs and neuro-symbolic reasoning. Dr. Sun is a recipient of multiple Best Paper Awards, two Test of Time Awards, among many other awards. She has also served as organizers of top conferences in the field, such as KDD’23, ICLR’24, and KDD’25.

• Introduction.- Preliminaries on Knowledge Graph and Symbolic Logic.- Knowledge Graph Completion.- Complex Query Answering.-Logical Rule Learning.- Incorporating Ontology to Knowledge Graph Reasoning.- Conclusion and Research Frontiers.

Kewei Cheng, Ph.D., is an applied scientist at Amazon. She earned her Ph.D. in Computer Science from UCLA in 2024. Her main research areas include graph and network mining as well as broader interests in data mining and machine learning. Dr. Cheng’s work has been featured in various prestigious conferences across multiple domains such as KDD, VLDB, WSDM, CIKM, AAAI, ICLR, EMNLP, and ACL.Yizhou Sun, Ph.D., is a Professor in the Department of Computer Science at UCLA. Her principal research interest is on mining graphs/networks and more generally in data mining and machine learning with a recent focus on deep learning on graphs and neuro-symbolic reasoning. Dr. Sun is a recipient of multiple Best Paper Awards, two Test of Time Awards, among many other awards. She has also served as organizers of top conferences in the field, such as KDD’23, ICLR’24, and KDD’25.

• Introduction.- Preliminaries on Knowledge Graph and Symbolic Logic.- Knowledge Graph Completion.- Complex Query Answering.-Logical Rule Learning.- Incorporating Ontology to Knowledge Graph Reasoning.- Conclusion and Research Frontiers.