Logan Engstrom
Impact in
- Artificial Intelligence top 5%
- Adversarial Robustness in Machine Learning
- Anomaly Detection Techniques and Applications
- Reinforcement Learning in Robotics
- Signal Processing top 10%
- Advanced Malware Detection Techniques
Papers in
-
- Adversarial Robustness in Machine Learning 5
- Anomaly Detection Techniques and Applications 1
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- Cell Image Analysis Techniques 2
- Co-authors
- Andrew Ilyas (6 shared papers)Anish Athalye (1 shared paper)Aleksander Mądry (6 shared papers)Dimitris Tsipras (5 shared papers)Shibani Santurkar (4 shared papers)Larry Rudolph (1 shared paper)Firdaus Janoos (1 shared paper)Brandon Tran (4 shared papers)
- Journals
- PLoS ONE (1 paper)International Conference on Learning Representations (1 paper)International Conference on Machine Learning (1 paper)DSpace@MIT (Massachusetts Institute of Technology) (2 papers)
- Partner nations
- United States
In The Last Decade
Logan Engstrom
8 papers receiving 345 citations
Peers
Comparison fields: 5 of 57
- Artificial Intelligence 298
- Signal Processing 64
- Computer Vision and Pattern Recognition 103
- Hardware and Architecture 24
- Computer Graphics and Computer-Aided Design 4
Countries citing papers authored by Logan Engstrom
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).
Fields of papers citing papers by Logan Engstrom
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-authors
The 22 scholars most cited alongside Logan Engstrom, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Synthesizing Robust Adversarial Examples | 2018 | 241 |
| 2 | Implementation Matters in Deep RL: A Case Study on PPO and TRPO | 2020 | 69 |
| 3 | 2023 | 16 | |
| 4 | Image Synthesis with a Single (Robust) Classifier | 2019 | 16 |
| 5 | 2019 | 15 | |
| 6 | Exploring the Landscape of Spatial Robustness | 2017 | 3 |
| 7 | 2019 | 1 | |
| 8 | 2017 | 1 |
About Logan Engstrom
Logan Engstrom is a scholar working on Artificial Intelligence, Biophysics, Computer Vision and Pattern Recognition, Media Technology and Signal Processing, having authored 8 papers that have together received 362 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (5 papers), Cell Image Analysis Techniques (2 papers), Bacillus and Francisella bacterial research (1 paper), Genomics and Phylogenetic Studies (1 paper), Gene expression and cancer classification (1 paper), Anomaly Detection Techniques and Applications (1 paper), Generative Adversarial Networks and Image Synthesis (1 paper) and COVID-19 diagnosis using AI (1 paper). The work is most often cited by research in Artificial Intelligence (298 citations), Signal Processing (64 citations), Computer Vision and Pattern Recognition (103 citations), Hardware and Architecture (24 citations) and Computer Graphics and Computer-Aided Design (4 citations). Logan Engstrom has collaborated with scholars based in United States. Frequent co-authors include Andrew Ilyas, Anish Athalye, Aleksander Mądry, Dimitris Tsipras, Shibani Santurkar, Larry Rudolph, Firdaus Janoos, Brandon Tran, Hadi Salman and Sung Min Park. Their work appears in journals such as PLoS ONE, International Conference on Learning Representations, International Conference on Machine Learning and DSpace@MIT (Massachusetts Institute of Technology).
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.