Call for Speakers for Graph + AI Summit 2021 is Open through March 28, Midnight US Pacific Time.

The Graph + AI Summit is focused on accelerating analytics, AI, and machine learning with graph algorithms and will return as a virtual conference on April 21-22, 2021. Graph + AI 2020 had over 3,000 attendees from over 56 countries, including data scientists, data engineers, architects, business and IT executives from over 100 Fortune 500 companies. Speakers for last year’s conference included UnitedHealth Group, Intel, Dell, Jaguar Land Rover, Intuit, AT&T, Xandr, Scotiabank, Accenture, KPMG, Publicis Sapient, and Xilinx, along with many innovative startups. Graph + AI 2021 will have many of these speakers and the largest banks, retailers and fintechs added to the roster.

We are looking for knowledgeable and passionate speakers to share their thought leadership in this growing field. Whether you are a data scientist, engineer, architect or an IT or business stakeholder, we encourage you to consider sharing your insights at the conference.

Have you worked on combining AI or ML with graph algorithms for analyzing customer data? To predict health outcomes? To find fraudsters or cybersecurity threats? To recommend the most suitable products or services? To optimize supply chain and route planning? To balance the energy grid? Have you built a cool prototype to combine NLP, chatbot or other AI capabilities with a graph database? Have you connected a visualization tool with a graph platform? Then we want to hear from you! 

If selected, you will join the virtual stage with fellow graph practitioners and present to an estimated audience of 6,000 at Graph + AI 2021.

Your submission may include one or more of the the following topics: 

• Artificial intelligence use cases and case studies
• Machine learning use cases and case studies
• Graph neural networks
• Combing Natural Language Processing (NLP) with Graph
• First-of-a-kind solutions combining AI, machine learning and graph algorithms
• Predictive analytics
• Customer 360, customer journey
• Hyper-personalized recommendation engine
• Fraud detection, anti-money laundering
• Supply chain optimization
• Cybersecurity
• Industry-specific applications in internet, eCommerce, banking, insurance, fintech, media, manufacturing, transportation and healthcare industries