Ruslan Salakhutdinov
UPMC Professor of Computer Science in Carnegie Mellon's Machine Learning Department; co-author of dropout
- UPMC Professor of Computer Science, Machine Learning Department, Carnegie Mellon University12
- Listed with Meta Superintelligence Labs on the Thinking Before Thinking paper (September 2026), Meta Superintelligence Labs5
Ruslan Salakhutdinov is a UPMC Professor of Computer Science in the Machine Learning Department at Carnegie Mellon University, which Salakhutdinov joined in February 2016 after serving as an assistant professor at the University of Toronto. Salakhutdinov's homepage lists research interests in deep learning, probabilistic graphical models, and large-scale optimization. Salakhutdinov co-authored the 2014 JMLR paper introducing dropout, a training technique that randomly drops units during training to reduce overfitting, and more recently co-authored VisualWebArena, a benchmark for evaluating multimodal agents on realistic visual web tasks. Salakhutdinov is also listed with Meta Superintelligence Labs on a September 2026 paper about agentic meta-reasoning at inference time.12345
Work
Dropout: A Simple Way to Prevent Neural Networks from Overfitting (external site: jmlr.org)Published research
Co-author, with Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, and Ilya Sutskever, of the 2014 Journal of Machine Learning Research paper describing dropout.3
VisualWebArena (external site: arxiv.org)Published research
Co-author of the 2024 paper introducing VisualWebArena, a benchmark for evaluating multimodal agents on realistic visual web tasks; the homepage links the paper and its code.41
Other documented roles
Roles the sources document but that are not confirmed as current.
- Assistant Professor, Department of Computer Science and Department of Statistics (2011–2016), University of Toronto2
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