Jure Leskovec
Also known as Jurij Leskovec
Jure Leskovec is a Stanford computer scientist whose work includes learning representations for networks. He earned computer science degrees at the University of Ljubljana and Carnegie Mellon, spent a postdoctoral year at Cornell, and joined Stanford faculty in 2009. His work includes node2vec for network representation learning and SNAP for analysis of large networks. ACM SIGKDD gave him its 2023 Innovation Award, and in 2025 he coauthored CollabLLM, a framework for multiturn human-LLM collaboration that received an ICML Outstanding Paper Award. As of October 2026, he is Professor of Computer Science at Stanford, affiliated with the Stanford AI Lab, Machine Learning Group, and Center for Research on Foundation Models.
- Now at
- Stanford University
- Works
- 588
- Citations
- 112,256
- h-index
- 140
Publication numbers from OpenAlex, as of 14 October 2026.
Timeline
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2004–2008
Computer science degrees
He earns a bachelor's degree in computer science at the University of Ljubljana in 2004 and a computer science PhD at Carnegie Mellon University in 2008.
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2009
From Cornell to Stanford
He spends a postdoctoral year at Cornell University before joining Stanford faculty in 2009.
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2016
Learning from network walks
With Aditya Grover, he introduces node2vec in 2016, a framework that learns node representations by exploring network neighborhoods with biased random walks.
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2016
A platform for large networks
In 2016, he coauthors the SNAP paper with Rok Sosic, describing a system for analysis and manipulation of large networks.
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2023
An ACM SIGKDD award
ACM SIGKDD names him the winner of its 2023 Innovation Award.
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2025
Training language models to collaborate
He coauthors CollabLLM, a training framework for multiturn human-LLM collaboration. The paper receives an ICML 2025 Outstanding Paper award.
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As of October 2026
A Stanford professorship
He is Professor of Computer Science at Stanford University and is affiliated with the Stanford AI Lab, Machine Learning Group and the Center for Research on Foundation Models.
Sources and credits
Photo: Yerpo, via Wikimedia Commons. License: CC BY-SA 4.0. Source: commons.wikimedia.org. Cropped to a square and resized. Ask us to remove or replace this photo.
- Jure Leskovec's Profile | Stanford Profiles
- Stanford University Explore Courses
- [1607.00653] node2vec: Scalable Feature Learning for Networks
- [1606.07550] SNAP: A General Purpose Network Analysis and Graph Mining Library
- SIGKDD Awards : 2023 SIGKDD Innovation Award: Jure Leskovec
- [2502.00640] CollabLLM: From Passive Responders to Active Collaborators
- ICML 2025 Awards ICML 2025