Rajat Monga

32.5k total citations · 4 hit papers
8 papers, 4.0k citations indexed

About

Rajat Monga is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Rajat Monga has authored 8 papers receiving a total of 4.0k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 1 paper in Signal Processing. Recurrent topics in Rajat Monga's work include Speech Recognition and Synthesis (2 papers), Computational Physics and Python Applications (2 papers) and Advanced Neural Network Applications (2 papers). Rajat Monga is often cited by papers focused on Speech Recognition and Synthesis (2 papers), Computational Physics and Python Applications (2 papers) and Advanced Neural Network Applications (2 papers). Rajat Monga collaborates with scholars based in United States and Canada. Rajat Monga's co-authors include Oriol Vinyals, Joe Yue-Hei Ng, Matthew Hausknecht, Sudheendra Vijayanarasimhan, George Toderici, Quoc V. Le, Greg S. Corrado, Matthieu Devin, Andrew Y. Ng and Marc’Aurelio Ranzato and has published in prestigious journals such as arXiv (Cornell University), Neural Information Processing Systems and International Conference on Machine Learning.

In The Last Decade

Rajat Monga

7 papers receiving 3.8k citations

Hit Papers

Large Scale Distributed Deep Networks 2012 2026 2016 2021 2012 2015 2012 2013 500 1000 1.5k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Large Scale Distributed Deep Networks
    2012 1.7k citations Jay B. Dean, Greg S. Corrado et al. Neural Information Processing Systems profile →
  2. Beyond short snippets: Deep networks for video classification
    2015 1.4k citations Joe Yue-Hei Ng, Matthew Hausknecht et al. profile →
  3. Building high-level features using large scale unsupervised learning
    2012 406 citations Marc’Aurelio Ranzato, Rajat Monga et al. International Conference on Machine Learning profile →
  4. On rectified linear units for speech processing
    2013 315 citations Matthew D. Zeiler, Rajat Monga et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Rajat Monga United States 6 2.3k 2.2k 486 414 344 8 4.0k
Adam Coates United States 17 2.0k 0.9× 2.5k 1.1× 404 0.8× 208 0.5× 189 0.5× 27 4.4k
Ahmed Bouridane United Kingdom 35 1.4k 0.6× 3.1k 1.4× 1.2k 2.5× 274 0.7× 400 1.2× 426 5.4k
Yi Xu China 35 901 0.4× 3.2k 1.4× 251 0.5× 350 0.8× 289 0.8× 188 5.2k
Mu Li China 23 2.0k 0.9× 1.6k 0.7× 190 0.4× 402 1.0× 127 0.4× 61 4.0k
Weiyao Lin China 32 1.8k 0.8× 3.6k 1.6× 502 1.0× 171 0.4× 245 0.7× 166 4.5k
Daijin Kim South Korea 34 1.0k 0.5× 2.9k 1.3× 473 1.0× 181 0.4× 412 1.2× 179 4.2k
Shu‐Tao Xia China 32 2.0k 0.9× 2.4k 1.1× 501 1.0× 1.0k 2.4× 263 0.8× 284 5.0k
Jianping Fan China 38 2.0k 0.9× 3.6k 1.6× 526 1.1× 264 0.6× 160 0.5× 275 5.5k
Sicheng Zhao China 40 2.2k 1.0× 3.2k 1.4× 365 0.8× 297 0.7× 182 0.5× 162 5.6k
Jingkuan Song China 47 3.5k 1.5× 7.2k 3.2× 415 0.9× 330 0.8× 394 1.1× 224 9.0k

Countries citing papers authored by Rajat Monga

Since Specialization
Citations

This map shows the geographic impact of Rajat Monga's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Rajat Monga with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rajat Monga more than expected).

Fields of papers citing papers by Rajat Monga

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rajat Monga. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Rajat Monga. The network helps show where Rajat Monga may publish in the future.

Co-authorship network of co-authors of Rajat Monga

This figure shows the co-authorship network connecting the top 25 collaborators of Rajat Monga. A scholar is included among the top collaborators of Rajat Monga based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Rajat Monga. Rajat Monga is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

8 of 8 papers shown
1.
Smilkov, Daniel, Nikhil Thorat, Ann Yuan, et al.. (2019). TensorFlow.js: Machine Learning for the Web and Beyond. arXiv (Cornell University). 1. 309–321. 5 indexed citations
2.
Agrawal, Akshay, Alexandre Passos, Ashish Agarwal, et al.. (2019). TensorFlow Eager: A Multi-Stage, Python-Embedded DSL for Machine Learning. 1. 178–189. 1 indexed citations
3.
Ng, Joe Yue-Hei, Matthew Hausknecht, Sudheendra Vijayanarasimhan, et al.. (2015). Beyond short snippets: Deep networks for video classification. 4694–4702. 1422 indexed citations breakdown →
4.
Sak, Haşim, Oriol Vinyals, Georg Heigold, et al.. (2014). Sequence discriminative distributed training of long short-term memory recurrent neural networks. 1209–1213. 96 indexed citations
5.
Zeiler, Matthew D., Rajat Monga, M. Mao, et al.. (2013). On rectified linear units for speech processing. 3517–3521. 315 indexed citations breakdown →
6.
Dean, Jay B., Greg S. Corrado, Rajat Monga, et al.. (2012). Large Scale Distributed Deep Networks. Neural Information Processing Systems. 25. 1223–1231. 1706 indexed citations breakdown →
7.
Ranzato, Marc’Aurelio, Rajat Monga, Matthieu Devin, et al.. (2012). Building high-level features using large scale unsupervised learning. International Conference on Machine Learning. 507–514. 406 indexed citations breakdown →
8.
Le, Quoc V., Rajat Monga, Matthieu Devin, et al.. (2012). Appendix: Building high-level features using large scale unsupervised learning. 22 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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