Season 1 | Episode 3

Graph Neural Networks and Generative AI with Jure Leskovec

On this episode, we’re joined by Jure Leskovec, Stanford professor and co-founder at

Graph neural networks (GNNs) are gaining popularity in the AI community, helping ML teams build advanced AI applications that provide deep insights to tackle real-world problems. Stanford professor and co-founder at Kumo.AI, Jure Leskovec, whose work is at the intersection of graph neural networks, knowledge graphs, and generative AI, will explore how organizations can incorporate GNNs in their generative AI initiatives. 

About the guest
Parul Pandey has a background in Electrical Engineering and currently works as a Principal Data Scientist at Prior to this, she was working as a Machine Learning Engineer at Weights & Biases. She is also a Kaggle Grandmaster in the notebooks category and was one of Linkedin’s Top Voices in the Software Development category in 2019. Parul has written multiple articles focused on Data Science and Software development for various publications and mentors, speaks, and delivers workshops on topics related to Responsible AI. She is currently part of the “The 2023 Kaggle AI Report” as an area chair and section editor, focusing on the section dedicated to the theme of continued studies of AI ethics.