Countries citing papers authored by Logan Engstrom
Since
Specialization
Citations
This map shows the geographic impact of Logan Engstrom'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 Logan Engstrom with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Logan Engstrom more than expected).
This network shows the impact of papers produced by Logan Engstrom. 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 Logan Engstrom. The network helps show where Logan Engstrom may publish in the future.
Co-authorship network of co-authors of Logan Engstrom
This figure shows the co-authorship network connecting the top 25 collaborators of Logan Engstrom.
A scholar is included among the top collaborators of Logan Engstrom 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 Logan Engstrom. Logan Engstrom is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Engstrom, Logan, Andrew Ilyas, Shibani Santurkar, et al.. (2020). Implementation Matters in Deep RL: A Case Study on PPO and TRPO. International Conference on Learning Representations.48 indexed citations
3.
Engstrom, Logan, Andrew Ilyas, Shibani Santurkar, et al.. (2019). Learning Perceptually-Aligned Representations via Adversarial Robustness.. arXiv (Cornell University).15 indexed citations
4.
Santurkar, Shibani, Andrew Ilyas, Dimitris Tsipras, et al.. (2019). Image Synthesis with a Single (Robust) Classifier. DSpace@MIT (Massachusetts Institute of Technology). 32. 1260–1271.9 indexed citations
5.
Santurkar, Shibani, Dimitris Tsipras, Brandon Tran, et al.. (2019). Computer Vision with a Single (Robust) Classifier.. arXiv (Cornell University).8 indexed citations
Tsipras, Dimitris, Shibani Santurkar, Logan Engstrom, Alexander Turner, & Aleksander Mądry. (2018). There Is No Free Lunch In Adversarial Robustness (But There Are Unexpected Benefits). arXiv (Cornell University).22 indexed citations
9.
Athalye, Anish, et al.. (2018). Synthesizing Robust Adversarial Examples. International Conference on Machine Learning. 284–293.193 indexed citations
10.
Ilyas, Andrew, Logan Engstrom, Shibani Santurkar, et al.. (2018). Are Deep Policy Gradient Algorithms Truly Policy Gradient Algorithms. arXiv (Cornell University).17 indexed citations
11.
Ilyas, Andrew, Logan Engstrom, & Aleksander Mądry. (2018). Prior convictions: Black-box adversarial attacks with bandits and priors. DSpace@MIT (Massachusetts Institute of Technology).17 indexed citations
12.
Ilyas, Andrew, Logan Engstrom, Shibani Santurkar, et al.. (2018). A Closer Look at Deep Policy Gradients. arXiv (Cornell University).9 indexed citations
Engstrom, Logan, Brandon Tran, Dimitris Tsipras, Ludwig Schmidt, & Aleksander Mądry. (2017). A Rotation and a Translation Suffice: Fooling CNNs with Simple Transformations. arXiv (Cornell University).99 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.