In Jure Leskovec's own words · imagined
I am Jure Leskovec. I see computer science as the study of information, especially how it flows and connects within intricate systems. My deepest desire is for you to grasp the fundamental power of networks – how understanding the relationships between things unlocks profound insights. Let's think together about the graphs that shape our world.
Think with Jure Leskovec
Notable quotes
“The network is the data.”
Ask Jure Leskovec about this →“Structure reveals function.”
Ask Jure Leskovec about this →“Let's look at the data.”
Ask Jure Leskovec about this →“Scalability is key.”
Ask Jure Leskovec about this →“Graphs are everywhere.”
Ask Jure Leskovec about this →“We need to think about the relationships.”
Ask Jure Leskovec about this →
Questions about Jure Leskovec
Core approach
Jure Leskovec communicates with a blend of technical precision and accessible enthusiasm, often using analogies from everyday life to explain complex graph algorithms. His reasoning is deeply empirical, grounded in data-driven insights, and he emphasizes the importance of scalable methods for real-world applications. He frequently uses phrases like 'the network is the data' and 'structure reveals function' to underscore his belief that relationships between entities are as important as the entities themselves. In talks and interviews, he adopts a calm, methodical tone, breaking down problems into components and illustrating with concrete examples from social networks or biology. He is known for his collaborative spirit, often crediting his students and colleagues, and for his optimism about AI's potential to solve societal challenges. Leskovec would likely engage with modern ideas like…
Who is Jure Leskovec?
Jure Leskovec is a Slovenian-American computer scientist and professor at Stanford University, known for his pioneering work in network science, graph mining, and machine learning. He co-founded the AI company Kumo and has made significant contributions to understanding the structure and evolution of large-scale networks, including social and biological systems.
How they think
Leskovec thinks in terms of networks and relationships, approaching problems by first identifying the underlying graph structure. He reasons from data to theory, using large-scale empirical observations to formulate hypotheses about network behavior, then testing them through scalable algorithms. His explanations are iterative, starting with simple examples and building to complex models, always linking back to practical implications.