Knowledge graphs have emerged as a compelling abstraction for organizing world’s structured knowledge over the internet, capturing relationships among key entities of interest to enterprises, and a way to integrate information extracted from multiple data sources.

Knowledge graphs have also started to play a central role in machine learning and natural language processing as a method to incorporate world knowledge, as a target knowledge representation for extracted knowledge, and for explaining what is being learned.

On May 27, 2021, Causality Link co-founder and CEO, Pierre Haren, joined Professor Alex Bolotov and Dr. Natalia Yerashania to discuss knowledge graphs in fintech for Stanford’s CS 520 course.

The class is a graduate-level research seminar and includes lectures on knowledge graph topics (e.g., data models, creation, inference, access) and invited lectures from prominent researchers and industry practitioners. The seminar emphasizes synthesis of AI, database systems and HCI in creating integrated intelligent systems centered around knowledge graphs.

Watch the full seminar below.