Olga Russakovsky

45.3k total citations · 2 hit papers
32 papers, 25.1k citations indexed

About

Olga Russakovsky is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Science Applications. According to data from OpenAlex, Olga Russakovsky has authored 32 papers receiving a total of 25.1k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Computer Vision and Pattern Recognition, 16 papers in Artificial Intelligence and 7 papers in Computer Science Applications. Recurrent topics in Olga Russakovsky's work include Advanced Image and Video Retrieval Techniques (9 papers), Multimodal Machine Learning Applications (8 papers) and Domain Adaptation and Few-Shot Learning (8 papers). Olga Russakovsky is often cited by papers focused on Advanced Image and Video Retrieval Techniques (9 papers), Multimodal Machine Learning Applications (8 papers) and Domain Adaptation and Few-Shot Learning (8 papers). Olga Russakovsky collaborates with scholars based in United States, France and Canada. Olga Russakovsky's co-authors include Li Fei-Fei, Jia Deng, Jonathan Krause, Michael S. Bernstein, Zhiheng Huang, Alexander C. Berg, Andrej Karpathy, Sanjeev Satheesh, Hao Su and Aditya Khosla and has published in prestigious journals such as Science, International Journal of Computer Vision and Patterns.

In The Last Decade

Olga Russakovsky

30 papers receiving 24.1k citations

Hit Papers

ImageNet Large Scale Visu... 2015 2026 2018 2022 2015 2023 5.0k 10.0k 15.0k 20.0k
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. ImageNet Large Scale Visual Recognition Challenge
    2015 23.7k citations Olga Russakovsky, Jia Deng et al. International Journal of Computer Vision profile →
  2. Art and the science of generative AI
    2023 314 citations Ziv Epstein, Aaron Hertzmann et al. Science profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Olga Russakovsky United States 16 15.2k 9.7k 2.6k 1.9k 1.4k 32 25.1k
Sanjeev Satheesh United States 10 14.9k 1.0× 9.2k 1.0× 2.6k 1.0× 1.9k 1.0× 1.4k 1.0× 15 24.2k
Hao Su China 23 17.2k 1.1× 9.3k 1.0× 2.6k 1.0× 2.0k 1.1× 1.5k 1.0× 68 27.4k
Jonathan Krause United States 21 17.2k 1.1× 11.0k 1.1× 3.4k 1.3× 2.1k 1.1× 1.5k 1.0× 45 28.4k
Michael S. Bernstein United States 49 18.7k 1.2× 13.5k 1.4× 2.6k 1.0× 1.9k 1.0× 1.5k 1.1× 176 35.0k
Saining Xie United States 20 12.8k 0.8× 9.3k 1.0× 2.3k 0.9× 2.1k 1.1× 888 0.6× 33 22.2k
Zhiheng Huang United States 32 15.2k 1.0× 10.0k 1.0× 2.6k 1.0× 1.8k 1.0× 1.5k 1.1× 90 27.1k
Andrej Karpathy United States 11 21.6k 1.4× 13.2k 1.4× 2.8k 1.1× 2.0k 1.1× 1.7k 1.2× 12 32.7k
Jiashi Feng Singapore 75 18.0k 1.2× 7.7k 0.8× 1.6k 0.6× 3.1k 1.7× 1.0k 0.7× 278 26.0k
Zbigniew Wojna United States 4 10.0k 0.7× 6.9k 0.7× 3.1k 1.2× 1.5k 0.8× 899 0.6× 5 19.8k
Sergey Ioffe United States 16 11.9k 0.8× 8.2k 0.8× 3.6k 1.4× 1.7k 0.9× 981 0.7× 23 23.1k

Countries citing papers authored by Olga Russakovsky

Since Specialization
Citations

This map shows the geographic impact of Olga Russakovsky'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 Olga Russakovsky with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Olga Russakovsky more than expected).

Fields of papers citing papers by Olga Russakovsky

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Olga Russakovsky. 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 Olga Russakovsky. The network helps show where Olga Russakovsky may publish in the future.

Co-authorship network of co-authors of Olga Russakovsky

This figure shows the co-authorship network connecting the top 25 collaborators of Olga Russakovsky. A scholar is included among the top collaborators of Olga Russakovsky 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 Olga Russakovsky. Olga Russakovsky is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Russakovsky, Olga, et al.. (2025). D3: Scaling Up Deepfake Detection by Learning from Discrepancy. 23850–23859.
2.
Wang, Angelina, Aaron Hertzmann, & Olga Russakovsky. (2024). Benchmark suites instead of leaderboards for evaluating AI fairness. Patterns. 5(11). 101080–101080. 3 indexed citations
3.
Kim, Sunnie S. Y., Elizabeth Anne Watkins, Olga Russakovsky, Ruth Fong, & Andrés Monroy‐Hernández. (2023). Humans, AI, and Context: Understanding End-Users’ Trust in a Real-World Computer Vision Application. arXiv (Cornell University). 77–88. 17 indexed citations
4.
Wang, Angelina & Olga Russakovsky. (2023). Overwriting Pretrained Bias with Finetuning Data. 3934–3945. 7 indexed citations
5.
Epstein, Ziv, Aaron Hertzmann, Memo Akten, et al.. (2023). Art and the science of generative AI. Science. 380(6650). 1110–1111. 314 indexed citations breakdown →
6.
Wang, Angelina, et al.. (2022). REVISE: A Tool for Measuring and Mitigating Bias in Visual Datasets. International Journal of Computer Vision. 130(7). 1790–1810. 39 indexed citations
7.
Wang, Angelina, V. Ramaswamy, & Olga Russakovsky. (2022). Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation. arXiv (Cornell University). 336–349. 50 indexed citations
8.
Wang, Angelina & Olga Russakovsky. (2021). Directional Bias Amplification. International Conference on Machine Learning. 10882–10893. 1 indexed citations
9.
Kim, Sunnie S. Y., et al.. (2021). [Re] Don't Judge an Object by Its Context: Learning to Overcome Contextual Bias. arXiv (Cornell University). 1 indexed citations
10.
Wang, Zeyu, et al.. (2020). Towards Fairness in Visual Recognition: Effective Strategies for Bias Mitigation. 8916–8925. 127 indexed citations
11.
Yang, Kaiyu, Olga Russakovsky, & Jia Deng. (2019). SpatialSense: An Adversarially Crowdsourced Benchmark for Spatial Relation Recognition. 2051–2060. 15 indexed citations
12.
Yeung, Serena, Olga Russakovsky, Ning Jin, et al.. (2017). Every Moment Counts: Dense Detailed Labeling of Actions in Complex Videos. International Journal of Computer Vision. 126(2-4). 375–389. 221 indexed citations
13.
Kovashka, Adriana, Olga Russakovsky, Li Fei-Fei, & Kristen Grauman. (2016). Crowdsourcing in Computer Vision. 10(3). 177–243. 43 indexed citations
14.
Sigurdsson, Gunnar A., Olga Russakovsky, Ali Farhadi, Ivan Laptev, & Abhinav Gupta. (2016). Much Ado About Time: Exhaustive Annotation of Temporal Data. Proceedings of the AAAI Conference on Human Computation and Crowdsourcing. 4. 219–228. 12 indexed citations
15.
Russakovsky, Olga, Jia Deng, Hao Su, et al.. (2015). ImageNet Large Scale Visual Recognition Challenge. International Journal of Computer Vision. 115(3). 211–252. 23680 indexed citations breakdown →
16.
Russakovsky, Olga, Li-Jia Li, & Li Fei-Fei. (2015). Best of both worlds: Human-machine collaboration for object annotation. 2121–2131. 129 indexed citations
17.
Deng, Jia, et al.. (2014). Scalable multi-label annotation. 3099–3102. 94 indexed citations
18.
Russakovsky, Olga. (2014). ImageNet Large Scale Visual Recognition Challenge. arXiv (Cornell University). 37 indexed citations
19.
Russakovsky, Olga, et al.. (2010). Autonomous operation of novel elevators for robot navigation. 751–758. 36 indexed citations
20.
Russakovsky, Olga & Andrew Y. Ng. (2010). A Steiner tree approach to efficient object detection. 45. 1070–1077. 11 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Sanjeev Satheesh Breakdown of academic impact, for papers by Hao Su Breakdown of academic impact, for papers by Jonathan Krause Breakdown of academic impact, for papers by Michael S. Bernstein Breakdown of academic impact, for papers by Saining Xie Breakdown of academic impact, for papers by Zhiheng Huang Breakdown of academic impact, for papers by Andrej Karpathy Breakdown of academic impact, for papers by Jiashi Feng Breakdown of academic impact, for papers by Zbigniew Wojna Breakdown of academic impact, for papers by Sergey Ioffe
Rankless by CCL
2026