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Jure Leskovec

Jure Leskovec

Professor of Computer Science / Co-Founder and Chief Scientist / Stanford University / Kumo.AI

Jure Leskovec is a Professor of Computer Science at Stanford University, specializing in machine learning, deep learning, and graph neural networks. He is also the Co-Founder and Chief Scientist of Kumo.AI, a company focused on applying AI to enterprise data. Previously, he served as Chief Scientist at Pinterest and has made significant contributions to the field of large-scale network analysis and graph representation learning.

Ph.D. in Machine Learning, Carnegie Mellon University
United States
TwitterTwitter44.3K
InstagramInstagram1,014
LinkedInLinkedIn83.9K
TechnologyAcademiaArtificial Intelligence
83.9K
LinkedIn Followers
44.3K
Twitter Followers
>5,330 (for SNAP)
Google Scholar Citations
15+
Years at Stanford
Search More

Career

Kumo.AI
Kumo.AI

Co-Founder and Chief Scientist

Apr 2022 - Present
Position
Co-Founder and Chief Scientist
Stanford University
Stanford University

Professor

Sep 2009 - Present
Responsibilities
Me and my students work on machine learning, deep learning and graph neural networks. More at http://cs.stanford.edu/~jure/
Chan Zuckerberg Biohub
Chan Zuckerberg Biohub

Investigator

2017 - 2022
Position
Investigator
Pinterest
Pinterest

Chief Scientist

2015 - 2022
Position
Chief Scientist
Kosei
Kosei

Co-founder

2014 - 2015
Responsibilities
Smarter, personalized mobile ads. Acquired by Pinterest.
Cornell University
Cornell University

Post-doc

Sep 2008 - Sep 2009
Position
Post-doc
Carnegie Mellon University
Carnegie Mellon University

PhD in Machine Learning

Aug 2004 - Sep 2008
Position
PhD in Machine Learning
Yahoo Research
Yahoo Research

Intern

May 2007 - Aug 2007
Responsibilities
Worked with Ravi Kumar and Andrew Tomkins on microscopic evolution of social networks.
Microsoft Research
Microsoft Research

Intern

May 2006 - Aug 2006
Responsibilities
Worked with Eric Horvitz and Susan Dumais on web search query modeling, and the dynamics of a instant messenger network of 240 million people.
Hewlett Packard Laboratories
Hewlett Packard Laboratories

Intern

Jun 2005 - Aug 2005
Responsibilities
Worked with Bernardo Huberman and Lada Adamic on the dynamics of person-to-person product recommendations in a large social network.
Jozef Stefan Institute
Jozef Stefan Institute

Researcher

May 1997 - Aug 2004
Responsibilities
Research projects on: machine learning, data mining, text and web mining large graphs and networks, applications of machine learning and data mining.
Carnegie Mellon Univeristy
Carnegie Mellon Univeristy

Visiting scholar

Jun 2003 - Aug 2003
Responsibilities
Worked with Christos Faloutsos on problems posed by large graphs.
Royal Holloway University of London,
Royal Holloway University of London,

Intern

Jun 2002 - Aug 2002
Responsibilities
With John Shawe-Taylor on text classification on uneven training datasets.
Microsoft Research, Cambridge, UK
Microsoft Research, Cambridge, UK

Intern

Jun 2001 - Sep 2001
Responsibilities
With Natasa Milic-Frayling on web browser user navigation and search.

Education

Carnegie Mellon University
Carnegie Mellon University

Ph.D.

2004 - 2008
Field of Study
Ph.D. - Machine Learning
Cornell University
Cornell University

Postdoc

2008 - 2009
Field of Study
Postdoc - Computer Science
University of Ljubljana
University of Ljubljana

Diploma [B.Sc.]

1999 - 2004
Field of Study
Diploma [B.Sc.] - Computer Science
Gimnazija Bezigrad
Gimnazija Bezigrad
Education
N/A

Skills

Core technical and professional competencies derived from academic research, industry leadership, and startup experience.

Technical & Research Skills
Machine LearningGraph Neural Networks (GNNs)Deep LearningData MiningNetwork Science
Programming & Tools
PythonC++JavaHadoopMatlab

Domains

Primary Focus

Artificial Intelligence, Machine Learning, Graph Learning, Network Science

Industry Domains

Academia (Stanford), Enterprise AI (Kumo.AI), Social Media (Pinterest), Biomedical Research (CZ Biohub)

Tags

Personality & Approach

Pioneering, Academic, Data-Driven, Innovative, Educator, Entrepreneurial

Key Focus Areas

AI, Graph Learning, Large-Scale Systems, Research, Technology Transfer

Audience Metrics

Gender

Male 65.7%, Female 34.3%

Age Distribution

25-34 (64.5%), 35-54 (17.8%), 18-24 (12.4%)

Top Countries

US (13.1%), BR (11.7%), IR (8.6%), IN (7.0%)

Top Cities

Tehran (2.7%), Baghdad (2.2%), New York (1.5%)

Social Metrics

Instagram

1,014 followers

Twitter/X

44.3K followers

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