Atanas Kiryakov, Graphwise, President
Peio Popov, Graphwise, VP of Business Operations

Knowledge graphs transform how businesses manage data, develop AI applications, and gain insights. This presentation will showcase three applications where graph and GenAI bring real difference: (i) self-servi...

Brian Martin, AbbVie, Chief AI Product Owner, Senior Research Fellow

The potential impact of AI - notwithstanding the hype and hyperbole - is nothing less than evolutionary. As companies begin to evolve themselves, the direction of that evolution is toward companies beginning more and more to a...

Tara Raafat, Bloomberg, Head of (Semantic) Metadata and Knowledge graph Strategy

Building a knowledge graph (KG) in an enterprise is more than just a technical endeavor — it is a strategic, organizational, and technological transformation. Enterprises embarking on this journey face a multitude o...

Javid Huseynov, Columbia University, Associate Professor of Practice

In financial markets, corporate ownership structures influence short selling risks. To assess this impact, we present Firmographica, a knowledge graph that integrates ownership information and relationships for publicly traded ...

Dan Bennett, S&P Global, Head of Technology, Enterprise Data Organization

We have made good progress with formatting our unstructured, textual, data for AI consumption with the RAG pattern. Yet, here in early 2025, the industry has not centered on a definition of what AI ready data means for str...

SQL Users Have IDEs - Why Don’t We?

Entity Resolution for Graph Practices Across Many Business Verticals

Automated Knowledge Graphs for Synchronized Building Operations

Oracle Database 23ai: The Complete Data Platform Powered by AI

Building Agentic Flows: From Data and Apps to Knowledge and A...

Sebastian Schmidt, Metaphacts, CEO

Charles Ivie, AWS, Sr Graph Architect
Tony Seale, The Knowledge Graph Guys, Founder
Branimir Rakić, OriginTrail, Founder and CTO
Ben Clinch, Ortecha, Partner

Background: Data Products deliver higher ROI for data management and lower costs of ownership. Yet, implementations are often hard, expen...

Žiga Drev, Origintrail, Founder and Managing Director
Tomaž Levak, OriginTrail, Founder and Managing Director
Branimir Rakić, OriginTrail, Founder and CTO
Dr. Bob Metcalfe, University of Texas at Austin, Retired Professor
Chris Rynning, AMYP Ventures, Managing Partner
Fady Mansour, Ethical Capita...

Brian O'Keefe, Amazon Web Services, Principal Neptune (Graph) Specialist Solutions Architect

In this hands-on learning tutorial, we will experiment with various strategies for using GenAI models to automate extracting and transforming raw data into a knowledge graph, and understanding and analyz...

Eliud Polanco, Fluree, President
Doug Beeson, Semantic Arts, Associate Ontologist

Pharmaceutical and BioTechnology companies must comply with regulatory requirements, resulting in months of labor spent to produce textbooks of documentation that could be riddled with human errors or misinterpreta...

William Lyon, Hypermode, Director of Developer Experience

The true power of LLMs isn’t in building chatbots, but rather leveraging AI models for implementing agentic workflows in the applications we build, adding features to our apps powered by LLMs that interact with APIs and data sources direc...

Giuseppe Futia, CSI - Piedmontese Consortium for Information Systems (Italy), Data Engineer

Graphs provide a powerful framework for modeling relationships between entities, making Graph Neural Networks (GNNs) a crucial tool for applying machine learning to graph-structured data. However, impleme...

Peio Popov, Graphwise, VP of Business Operations

Empowering Business Users with AI Agent-Driven Insights based on an Enterprise Knowledge Graph providing Trusted and Explainable Answers: A Hands-on Tutorial
Daniel H, Metaphacts, COO

Decision-makers and business users must trust the data that informs their decisions. Collecting and integrating ...

Anirban Acharya
Johnny Sun
Abhirup Dasgupta
Dominic Iadevaia
Danielle Villa
Elisa Kendall
Deborah L. McGuinness

Adriana Carolina Gonzalez Cavazos, Scripps Research Institue, PhD student

Drug repurposing offers a cost-effective alternative to traditional drug development by identifying new uses for existing drugs. Recent advances leverage Graph Neural Networks (GNN) to model complex biological data, showin...

Umesh Bhatt

This presentation explores the evolution of knowledge graph initiatives within Bristol Myers Squibb (BMS), contrasting past large-scale projects (BE-FAIR, Project Spartan) with current, more agile approaches. I present factors contributing to the limited success of earlier "big graph...

Ying Ding, School of Information, University of Texas at Austin, Professor

Conventional medical communication has been fundamentally broken, placing an increasing burden on healthcare professionals and significantly contributing to burnout and inefficiency. Physicians, nurses, and administrative...

Pooja Arora, ThoughtWorks Inc, HCLS Advisory & Strategy lead
Ganesh Kumar Sathiyamoorthi, Thoughtworks Inc, Principal Data Engineer

Clinical trials face a high failure rate, with 90% of drugs failing to progress due to challenges in translating preclinical results into clinical outcomes. Sydney ...

Moderator
Jamie McCusker, Rensselaer Polytechnic Institute, Research Director

Panelist
Mark Musen, Stanford Medicine Professor of Biomedical Informatics Research, Stanford University
Ted Slater, EPAM Systems, Managing Principal, Scientific Informatics Knowledge Engineering

The proliferation of diverse data model formats, represented in relational databases, RDF graphs and labeled property graphs, frequently leads to semantic fragmentation, hindering deep data integration and shared understanding for humans and machines. Unified semantics is an approach to define c...

Biomedical researchers generate experimental data at prodigious rates. There are widespread dreams that these data can be studied and re-explored to enable third parties to verify the published claims of the original investigators and to make new discoveries themselves through secondary analyses....