Nathan Dowlin
Impact in
- Artificial Intelligence top 2%
- Privacy-Preserving Technologies in Data
- Cryptography and Data Security
- Adversarial Robustness in Machine Learning
- Stochastic Gradient Optimization Techniques
- Cryptographic Implementations and Security
- Health Informatics top 10%
Papers in
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- Homotopy and Cohomology in Algebraic Topology 2
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- Geometric and Algebraic Topology 2
- Co-authors
- John Wernsing (2 shared papers)Kristin Lauter (2 shared papers)Michael Naehrig (2 shared papers)Ran Gilad-Bachrach (2 shared papers)Kim Laine (2 shared papers)
- Journals
- Journal of the American Mathematical Society (1 paper)Proceedings of the IEEE (1 paper)The Michigan Mathematical Journal (1 paper)International Conference on Machine Learning (1 paper)
- Partner nations
- United StatesIsrael
In The Last Decade
Nathan Dowlin
3 papers receiving 800 citations
Nathan Dowlin's Hit Papers
Peers
Comparison fields: 5 of 62
- Artificial Intelligence 735
- Health Informatics 15
- Computer Vision and Pattern Recognition 182
- Information Systems 130
- Computational Theory and Mathematics 78
Countries citing papers authored by Nathan Dowlin
This map shows the geographic impact of Nathan Dowlin'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 Nathan Dowlin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nathan Dowlin more than expected).
Fields of papers citing papers by Nathan Dowlin
This network shows the impact of papers produced by Nathan Dowlin. 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 Nathan Dowlin. The network helps show where Nathan Dowlin may publish in the future.
Co-authors
The 5 scholars most cited alongside Nathan Dowlin, 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 | CryptoNets: applying neural networks to encrypted data with high throughput and accuracy Hit paper breakdown → | 2016 | 766 |
| 2 | 2017 | 64 | |
| 3 | 2023 | 3 | |
| 4 | 2025 | 0 |
About Nathan Dowlin
Nathan Dowlin is a scholar working on Mathematical Physics, Geometry and Topology, Computer Vision and Pattern Recognition, Artificial Intelligence and Discrete Mathematics and Combinatorics, having authored 4 papers that have together received 833 indexed citations. Recurring topics across this work include Geometric and Algebraic Topology (2 papers), Cryptography and Data Security (2 papers), Homotopy and Cohomology in Algebraic Topology (2 papers), Chaos-based Image/Signal Encryption (2 papers), Privacy-Preserving Technologies in Data (1 paper), Cryptographic Implementations and Security (1 paper), Advanced Combinatorial Mathematics (1 paper) and semigroups and automata theory (1 paper). The work is most often cited by research in Artificial Intelligence (735 citations), Health Informatics (15 citations), Computer Vision and Pattern Recognition (182 citations), Information Systems (130 citations) and Computational Theory and Mathematics (78 citations). Nathan Dowlin has collaborated with scholars based in United States and Israel. Frequent co-authors include John Wernsing, Kristin Lauter, Michael Naehrig, Ran Gilad-Bachrach and Kim Laine. Their work appears in journals such as Journal of the American Mathematical Society, Proceedings of the IEEE, The Michigan Mathematical Journal and International Conference on Machine Learning.
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.