Attention developers and data scientists! Do you have an exciting project or technique that involves graphs? If the answer is yes, we encourage you to present at NODES 2024, an online conference focused on graph-driven innovation.
It’s a great opportunity to share your knowledge, connect with others, and showcase your expertise.
Submit your proposals by June 15th and pick one of these talk tracks:
Applications: Libraries, Frameworks, and Platforms
Discover how developers use Neo4j to power inventive solutions across software stacks, cloud providers, and programming languages.
AI: Generative AI, Knowledge Graphs, and Retrieval-Augmented Generation
Explore the intersection of groundbreaking research and real-world applications using graph technologies and techniques.
Data Science: Machine Learning, Graph Data Science, and AI Models
Learn advanced techniques in data curation and maintenance designed to fuel AI models.
Graphs: Visualization, Data Integrations, and Tips & Tricks
Unlock the power of graphs, connect knowledge graphs to broader data systems, and uncover expert tips and tricks.
Need help crafting a presentation? Take a look at these notable talks from NODES 2023 for some inspiration:
1. Using LLMs to Convert Unstructured Data to Knowledge Graphs
Noah Mayerhofer, Software Engineer at Neo4j, generates knowledge graphs from unstructured data using LLMs for entity extraction, semantic relationship recognition, and context inference.
2. Create Graph Dashboards With LLM Powered Natural Language Queries
Niels de Jong, Consulting Engineer at Neo4j, uses LLM-powered queries in NeoDash to create Neo4j dashboards using text instead of Cypher.
3. Fine-Tuning an Open-Source LLM for Text-to-Cypher Translation
Enabling users to interact with Neo4j databases intuitively, Jonas Nolde, Machine Learning Engineer at berrybeat, fine-tunes an LLM to generate Cypher statements from natural language input.
4. Create Awesome Graph Visualizations From Your Data
Illustrating the awesomeness of graph visualizations, Sebastian Mueller, CTO of yWorks, explores different tools to generate impressive and meaningful results.
5. Build Apps with the New GenAI Stack from Docker, LangChain, Ollama, and Neo4j
Look inside the containers of the GenAI Stack from Docker, LangChain, Ollama, and Neo4j that add generative AI capabilities to your applications with Harrison Chase, CEO & Founder of LangChain, and Oskar Hane, Sr. Staff Software Engineer at Neo4j.
6. Knowledge Graph-Based Chatbot
Tomas Bratanic, a Graph & LLM enthusiast, demonstrates the use of a knowledge graph as a storage object to take control of the answers provided by the chatbot and avoid hallucinations.
7. Graph Machine Learning for 2024
Watch this forward-looking, technical overview of GML by Zach Blumenfeld, Product Specialist DS/ML at Neo4j, as he lays out a graph-centric AI architecture for predictive tasks.
8. Using Graph Theory to Model a Production Line and Predict Delivery Dates
Identifying bottlenecks and patterns in a production line, José Diogo Viana, Backend Engineer at Remote, demonstrates the usage of graph theory to improve production line processes.
9. NeoGenAI: Ontology Guided Loading of Business Data in Graph Database
Dattaraj Rao, Chief Data Scientist at Persistent Systems uses LLMs to load business data from disparate sources and schemas into graph databases based on a standard ontology.
10. Entity Resolution and Deduping: Best Practices From Neo4j’s Field Team
Mark Quinsland, Senior Field Engineer at Neo4j, describes common entity resolution and deduplication techniques for use cases in financial, health care, and others, with tools like GDS and Cypher.
Need more ideas? You can check out the complete NODES 2023 playlist on YouTube. Additionally, you can share your ideas with the community in the conference and event forum thread. You might even find someone interested in collaborating on a presentation.
The deadline to submit is June 15th. We’re excited to review your proposals!
