Sotabase

Career

· Director, MIT CSAIL2026–
· Member of CSAIL, Researcher in Machine Learning Group, MIT CSAIL2026–
· Associate Professor (on leave), MIT EECS2026–
· Associate Professor (on leave), MIT CSAIL2019–
· X-Consortium Career Development Associate Professor, MIT EECS2019–
· X-Consortium Career Development Assistant Professor, Massachusetts Institute of Technology (MIT)2015–
· Postdoctoral Researcher, MIT Department of EECS2012–
· Postdoctoral Researcher, University of California Berkeley2012–
· PhD Student, Max Planck Institute & ETH Zurich2008–
· PhD in Computer Science, Max Planck Institute for Intelligent Systems and ETH Zurich2008–

Publications (172)

How Powerful are Graph Neural Networks?
International Conference on Learning Representations · 2018
9,180
cited
Representation Learning on Graphs with Jumping Knowledge Networks
International Conference on Machine Learning · 2018
2,264
cited
Deep Metric Learning via Lifted Structured Feature Embedding
Computer Vision and Pattern Recognition · 2015
1,748
cited
Contrastive Learning with Hard Negative Samples
International Conference on Learning Representations · 2020
940
cited
Debiased Contrastive Learning
Neural Information Processing Systems · 2020
668
cited
Max-value Entropy Search for Efficient Bayesian Optimization
International Conference on Machine Learning · 2017
449
cited
How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks
International Conference on Learning Representations · 2020
351
cited
Generalization and Representational Limits of Graph Neural Networks
International Conference on Machine Learning · 2020
347
cited
Deep Metric Learning via Facility Location
Computer Vision and Pattern Recognition · 2016
297
cited
What Can Neural Networks Reason About?
International Conference on Learning Representations · 2019
275
cited
On learning to localize objects with minimal supervision
International Conference on Machine Learning · 2014
252
cited
ResNet with one-neuron hidden layers is a Universal Approximator
Neural Information Processing Systems · 2018
244
cited
Batched Large-scale Bayesian Optimization in High-dimensional Spaces
International Conference on Artificial Intelligence and Statistics · 2017
242
cited
Submodularity beyond submodular energies: Coupling edges in graph cuts
Computer Vision and Pattern Recognition · 2011
218
cited
Sign and Basis Invariant Networks for Spectral Graph Representation Learning
International Conference on Learning Representations · 2022
187
cited
Virtual screening of inorganic materials synthesis parameters with deep learning
npj Computational Materials · 2017
167
cited
Weakly-supervised Discovery of Visual Pattern Configurations
Neural Information Processing Systems · 2014
166
cited
Can contrastive learning avoid shortcut solutions?
Neural Information Processing Systems · 2021
163
cited
Debiasing Vision-Language Models via Biased Prompts
arXiv.org · 2023
153
cited
Distributionally Robust Optimization and Generalization in Kernel Methods
Neural Information Processing Systems · 2019
146
cited
Sotabase
Stefanie Jegelka | Researcher Profile | Sotabase | Sotabase