Dr. Jiawei Han is a Michael Aiken Chair Professor in the Department of Computer Science at the University of Illinois. He has been working on research into data mining, information network analysis, data warehousing, stream mining, spatiotemporal and multimedia data mining, text and Web mining, and software bug mining, with over 400 conference and journal publications. He has chaired or served in over 100 program committees of international conferences and workshops. He is a Fellow of ACM and IEEE. His book “Data Mining: Concepts and Techniques” (Morgan Kaufmann) has been used worldwide as a textbook. Jiawei's research focuses on discovering effective methods for mining structures from massive unstructured text data and has developed practical and scalable methods.

Dr. Bryan Perozzi is a Research Scientist at Google, working at the intersection of data mining, machine learning, and language models. He received the 2024 KDD Test of Time Award and the 2017 SIGKDD Dissertation Award for his pioneering work in network representation learning, particularly in the development of DeepWalk, one of the foundational algorithms for learning embeddings from graphs. His research has been widely influential, with numerous papers published in top-tier venues such as NeurIPS, ICML, KDD, and WWW, accumulating over 19,800 citations. His recent research focuses on advancing graph reasoning capabilities in large language models (LLMs).

Dr. Xin Luna Dong is a Principal Scientist at Meta Reality Labs, leading the ML efforts in building an intelligent personal assistant. She has spent more than a decade building knowledge graphs, such as the Amazon Product Graph and the Google Knowledge Graph. She has co-authored books "Machine Knowledge: Creation and Curation of Comprehensive Knowledge Bases" and “Big Data Integration”. She was named an ACM Fellow and an IEEE Fellow for "significant contributions to knowledge graph construction and data integration", awarded the VLDB Women in Database Research Award and VLDB Early Career Research Contribution Award, and invited as an ACM Distinguished Speaker. She serves in the PVLDB advisory committee, was a member of the VLDB endowment, a PC co-chair for KDD’2022 ADS track, WSDM’2022, VLDB’2021, and Sigmod’2018.