Keynotes

December 11, 2024

Dr. Geoff Webb, Monash University, Australia

Abstract

Large Language Models have made extraordinary advances in recent times. On the back of the technology’s spectacular success, many voices have been forecasting doomsday outcomes whereby AI systems may subjugate humanity. This talk will give a high level overview of Large Language Models and present my thoughts on the potential benefits and likely risks of AI and what we should be doing about them.

Dr. Geoff Webb is a Professor in the Department of Data Science and Artificial Intelligence at Monash University. He was editor in chief of the Data Mining and Knowledge Discovery journal, from 2005 to 2014. He has been Program Committee Chair of both IEEE ICDM and ACM SIGKDD, as well as General Chair of ICDM and member of the ACM SIGKDD Executive. He developed many of the key mechanisms of support-confidence association discovery in the 1980s. His OPUS search algorithm remains the state-of-the-art in rule search. He pioneered multiple research areas as diverse as black-box user modelling, interactive data analytics and statistically-sound pattern discovery. He has developed many useful machine learning algorithms that are widely deployed. His translational data science research includes contributions in computational protein biology and health. His many awards include IEEE Fellow, the inaugural Eureka Prize for Excellence in Data Science (2017), the Pacific-Asia Conference on Knowledge Discovery and Data Mining Distinguished Research Contributions Award (2022), the IEEE ICDM 10-year Highest Impact Award (2023), the IEEE ICDM Research Contribution Award (2024), and membership of the Computing Research and Education Association of Australasia Academy (2024)

December 12,2024

Prof. Dr. Evgeny Kharlamov

Abstract

Integration of graph-based approaches and Retrieval-Augmented Generation (RAG) has emerged as a powerful paradigm for developing robust, context-aware industrial solutions. This keynote explores how graph structures can enrich RAG systems by providing deeper semantic relationships, improving context retrieval, and enabling dynamic knowledge representation. We will in particular discuss the topics of scalability and and how it is addressed in a EU project GraphMassivizer.

Evgeny is a Senior Expert at Bosch AI and Associate Professor at the University of Oslo. He did research at the University of Oxford, INRIA Saclay, Telecom ParisTech and Free University of Bolzano. Evgeny is an AI expert, researcher, and manager with more than 12 years of experience in academia and industry during which he was driving impactful AI innovation. Evgeny’s particular strength is in Knowledge-Centered AI, Neuro-Symbolic AI, Knowledge Graphs, Ontologies, Semantic Data Integration and GenAI. Evgeny has a strong standing and impact in the AI community, ranked among top 111 of German AI researchers, 7th World Most Influential Scholars in AI in the area of Knowledge Engineering according to AMiner. He published more than 200 papers, got best paper awards, h-index of 40. Evgeny acquired and lead 7 EU, German and UK national large scale research projects with more than 6M EUR of funding.