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.

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. Jingrui He is a Professor at School of Information Sciences, University of Illinois at Urbana-Champaign. She received her PhD from Carnegie Mellon University in 2010. Her research focuses on heterogeneous machine learning, active learning, neural bandits, and self-supervised learning, with applications in security, agriculture, social network analysis, healthcare, and finance. Dr. He is the recipient of the 2016 NSF CAREER Award, the 2020 OAT Award, the 2025 Amazon Research Award, three times recipient of the IBM Faculty Award in 2018, 2015 and 2014 respectively, and was selected as IJCAI 2017 Early Career Spotlight. Dr. He has more than 190 publications at major conferences (e.g., ICML, NeurIPS, ICLR, KDD) and journals (e.g., TMLR, TKDD, JMLR), and is the author of two books. Her papers have received the Distinguished Paper Award at FAccT 2022, as well as Bests of the Conference at ICDM 2016, ICDM 2010, and SDM 2010. Dr. He is a Distinguished Member of ACM, a Senior Member of AAAI and IEEE. She is also the Program Co-chair of IEEE BigData 2023.

Danai Koutra is an Associate Professor in Computer Science and Engineering at the University of Michigan, where she leads the Graph Exploration and Mining at Scale (GEMS) Lab. She is also an Amazon Scholar. Her research focuses on principled, practical, and scalable methods for large-scale real networks, and her interests include graph learning, graph neural networks, graph summarization, knowledge graph mining, graph learning, similarity and alignment, and anomaly detection. She has won a Presidential Early Career Award for Scientists and Engineers (PECASE), an NSF CAREER award, an ARO Young Investigator award, the 2024 IBM Early Career Data Mining Research Award, the 2023 Tao Li Award, the 2020 SIGKDD Rising Star Award, research faculty awards from Google, Amazon, Facebook and Adobe, a Precision Health Investigator award, the 2016 ACM SIGKDD Dissertation award, and an honorable mention for the SCS Doctoral Dissertation Award (CMU). She holds a patent on bipartite graph alignment, and has multiple papers in top data mining conferences, including 9 award-winning papers and the 2022 IEEE ICDM Test-of-Time Award. She is Program co-Chair for ACM KDD 2024 and an Associate Editor of ACM TKDD. She was a Program co-Chair for ECML/PKDD 2023, a track co-chair for The Web Conference 2022, a co-chair of the Deep Learning Day at KDD 2022, the Secretary of the new SIAG on Data Science in 2021, and has also routinely served in the organizing committees of all the major data mining conferences. She has worked at IBM, Microsoft Research, and Technicolor Research. She earned her Ph.D. and M.S. in Computer Science from CMU, and her diploma in Electrical and Computer Engineering at the National Technical University of Athens.