World's Best Scientists 2026 revealed!
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Computer Science
USA
2026

D-Index & Metrics

Computer Science

D-Index
116
Citations
162513
World Ranking
170
National Ranking
100

Research.com Recognitions

  • 2026 - Research.com Computer Science in United States Leader Award
  • 2025 - Research.com Computer Science in United States Leader Award
  • 2013 - Fellow of Alfred P. Sloan Foundation

Overview

Ruslan Salakhutdinov is affiliated with Carnegie Mellon University in the United States. Their research primarily focuses on the field of Computer Science, with a substantial number of publications spanning Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Management Science and Operations Research, and Control and Systems Engineering.

The subfields Salakhutdinov has contributed to include:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Management Science and Operations Research
  • Control and Systems Engineering

Key topics covered in their work are:

  • Topic Modeling
  • Multimodal Machine Learning Applications
  • Reinforcement Learning in Robotics
  • Natural Language Processing Techniques
  • Domain Adaptation and Few-Shot Learning
  • Speech Recognition and Synthesis
  • Music and Audio Processing

Salakhutdinov's recent papers encompass a range of subjects and publication venues:

  • "Xlnet: Generalized Autoregressive Pretraining for Language Understanding," 2025, arXiv (Cornell University)
  • "CAWET: Context-Aware Worst-Case Execution Time Estimation Using Transformers," 2023, arXiv (Cornell University)
  • "HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units," 2021, IEEE/ACM Transactions on Audio Speech and Language Processing
  • "Importance weighted autoencoders," 2024, arXiv (Cornell University)
  • "Think Locally, Act Globally: Federated Learning with Local and Global Representations," 2020, arXiv (Cornell University)

Frequent coauthors collaborating with Salakhutdinov include:

  • Louis-Philippe Morency
  • Paul Pu Liang
  • Benjamin Eysenbach
  • Yao-Hung Hubert Tsai
  • Sergey Levine

The most common publication venues where Salakhutdinov's work appears are:

  • arXiv (Cornell University)
  • Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  • IEEE/ACM Transactions on Audio Speech and Language Processing
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION

Among distinctions received, Salakhutdinov was named a Fellow of the Alfred P. Sloan Foundation in 2013.

Best Publications

  • Dropout: a simple way to prevent neural networks from overfitting

    Nitish Srivastava;Geoffrey Hinton;Alex Krizhevsky;Ilya Sutskever

  • Reducing the Dimensionality of Data with Neural Networks

    G. E. Hinton;R. R. Salakhutdinov

  • Improving neural networks by preventing co-adaptation of feature detectors

    Geoffrey E. Hinton;Nitish Srivastava;Alex Krizhevsky;Ilya Sutskever

  • XLNet: Generalized Autoregressive Pretraining for Language Understanding

    Zhilin Yang;Zihang Dai;Yiming Yang;Jaime G. Carbonell

  • Probabilistic Matrix Factorization

    Andriy Mnih;Ruslan R Salakhutdinov

  • Siamese Neural Networks for One-shot Image Recognition

    Gregory Koch;Richard Zemel;Ruslan Salakhutdinov

  • Transformer-XL: Attentive Language Models beyond a Fixed-Length Context.

    Zihang Dai;Zhilin Yang;Yiming Yang;Jaime G. Carbonell

  • Human-level concept learning through probabilistic program induction.

    Brenden M. Lake;Ruslan Salakhutdinov;Joshua B. Tenenbaum

  • Multimodal learning with deep Boltzmann machines

    Nitish Srivastava;Ruslan Salakhutdinov

  • Show, Attend and Tell: Neural Image Caption Generation with Visual Attention

    Kelvin Xu;Jimmy Ba;Ryan Kiros;Kyunghyun Cho

  • Neighbourhood Components Analysis

    Jacob Goldberger;Geoffrey E. Hinton;Sam T. Roweis;Ruslan R Salakhutdinov

  • Restricted Boltzmann machines for collaborative filtering

    Ruslan Salakhutdinov;Andriy Mnih;Geoffrey Hinton

  • Aligning Books and Movies: Towards Story-Like Visual Explanations by Watching Movies and Reading Books

    Yukun Zhu;Ryan Kiros;Rich Zemel;Ruslan Salakhutdinov

  • Skip-thought vectors

    Ryan Kiros;Yukun Zhu;Ruslan Salakhutdinov;Richard S. Zemel

  • Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models

    Ryan Kiros;Ruslan Salakhutdinov;Richard S. Zemel

  • Bayesian probabilistic matrix factorization using Markov chain Monte Carlo

    Ruslan Salakhutdinov;Andriy Mnih

  • Deep Boltzmann machines

    Ruslan Salakhutdinov;Geoffrey E. Hinton

  • HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

    Zhilin Yang;Peng Qi;Saizheng Zhang;Yoshua Bengio

  • HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units

    Wei-Ning Hsu;Benjamin Bolte;Yao-Hung Hubert Tsai;Kushal Lakhotia

  • Semantic hashing

    Ruslan Salakhutdinov;Geoffrey Hinton

  • Unsupervised Learning of Video Representations using LSTMs

    Nitish Srivastava;Elman Mansimov;Ruslan Salakhutdinov

  • Supporting Online Material for Reducing the Dimensionality of Data with Neural Networks

    G. E. Hinton;R. R. Salakhutdinov

  • Supplementary Material for Human-level concept learning through probabilistic program induction

    Brenden M. Lake;Ruslan Salakhutdinov;Joshua B. Tenenbaum

Frequent Co-Authors

William W. Cohen
William W. Cohen Carnegie Mellon University
Eric P. Xing
Eric P. Xing Mohamed bin Zayed University of Artificial Intelligence
Louis-Philippe Morency
Louis-Philippe Morency Carnegie Mellon University
Geoffrey E. Hinton
Geoffrey E. Hinton University of Toronto
Zhiting Hu
Zhiting Hu University of California, San Diego
Nathan Srebro
Nathan Srebro Toyota Technological Institute at Chicago
Barnabás Póczos
Barnabás Póczos Carnegie Mellon University
Roger Grosse
Roger Grosse University of Toronto
Simon S. Du
Simon S. Du University of Washington

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