Sotabase

Career

· Chief Scientist, Kumo.AI2022–
· Professor, Stanford University2009–
· Postdoctoral Researcher, Cornell University2008–2009
· Research Intern, Microsoft Research2006–
· Research Intern, Yahoo Research2006–
· Research Intern, HP Labs2005–
· Ph.D. in Computational and Statistical Learning, Carnegie Mellon University2004–2008
· Research Intern, Carnegie Mellon University2003–
· Research Intern, Royal Holloway University of London2002–
· Intern, European Commission Joint Research Centre2000–
· Diploma (B.Sc.) in Computer Science, University of Ljubljana1999–2004
· Intern, Lionhearth Technologies1998–
· Research Assistant, University of Ljubljana1998–1999
· Software Engineer, Hermes Softlab1996–1997
· Investigator, Chan Zuckerberg Biohub
· Chief Scientist, Pinterest

Publications (889)

Inductive Representation Learning on Large Graphs
Neural Information Processing Systems · 2017
18,379
cited
node2vec: Scalable Feature Learning for Networks
Knowledge Discovery and Data Mining · 2016
11,801
cited
How Powerful are Graph Neural Networks?
International Conference on Learning Representations · 2018
9,182
cited
On the Opportunities and Risks of Foundation Models
arXiv.org · 2021
5,795
cited
{SNAP Datasets}: {Stanford} Large Network Dataset Collection
2014
4,191
cited
Graph Convolutional Neural Networks for Web-Scale Recommender Systems
Knowledge Discovery and Data Mining · 2018
3,947
cited
Open Graph Benchmark: Datasets for Machine Learning on Graphs
Neural Information Processing Systems · 2020
3,309
cited
Friendship and mobility: user movement in location-based social networks
Knowledge Discovery and Data Mining · 2011
3,265
cited
Graph evolution: Densification and shrinking diameters
TKDD · 2006
2,847
cited
Graphs over time: densification laws, shrinking diameters and possible explanations
Knowledge Discovery and Data Mining · 2005
2,741
cited
Cost-effective outbreak detection in networks
Knowledge Discovery and Data Mining · 2007
2,699
cited
The dynamics of viral marketing
ACM Conference on Economics and Computation · 2005
2,486
cited
Hierarchical Graph Representation Learning with Differentiable Pooling
Neural Information Processing Systems · 2018
2,388
cited
Defining and evaluating network communities based on ground-truth
Knowledge and Information Systems · 2012
2,297
cited
Learning to Discover Social Circles in Ego Networks
Neural Information Processing Systems · 2012
2,231
cited
Representation Learning on Graphs: Methods and Applications
IEEE Data Engineering Bulletin · 2017
2,099
cited
Community Structure in Large Networks: Natural Cluster Sizes and the Absence of Large Well-Defined Clusters
Internet Mathematics · 2008
2,032
cited
Hidden factors and hidden topics: understanding rating dimensions with review text
ACM Conference on Recommender Systems · 2013
1,928
cited
Predicting positive and negative links in online social networks
The Web Conference · 2010
1,679
cited
GNNExplainer: Generating Explanations for Graph Neural Networks
Neural Information Processing Systems · 2019
1,675
cited
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