Jonathan Ullman

2.9k citations
47 papers · 749 · h-index 15

Impact in

    • Privacy-Preserving Technologies in Data
    • Cryptography and Data Security
    • Adversarial Robustness in Machine Learning
    • Stochastic Gradient Optimization Techniques
    • Mobile Crowdsensing and Crowdsourcing

Papers in

Jonathan Ullman

44 papers receiving 695 citations

Peers

Jonathan Ullman
Comparison fields: 5 of 61
  • Artificial Intelligence 588
  • Computer Science Applications 66
  • Health Informatics 12
  • Management Science and Operations Research 95
  • Computational Theory and Mathematics 113
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Citations per field
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Citations per year

Countries citing papers authored by Jonathan Ullman

Since Specialization
Citations

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

Fields of papers citing papers by Jonathan Ullman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jonathan Ullman, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jonathan Ullman Line = papers co-authored together Jonathan Ullman links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017124
2 201460
3 201559
4 201057
5 201650
6 196746
7 201142
8 196632
9 201429
10 201622
11 201420
12 201320
13 201619
14 201415
15 201314
16 201514
17 20239
18 20119
19 20189
20 20188

About Jonathan Ullman

Jonathan Ullman is a scholar working on Artificial Intelligence, Management Science and Operations Research, Computational Theory and Mathematics, Sociology and Political Science and Computer Science Applications, having authored 47 papers that have together received 749 indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (35 papers), Cryptography and Data Security (21 papers), Privacy, Security, and Data Protection (7 papers), Auction Theory and Applications (6 papers), Complexity and Algorithms in Graphs (6 papers), Mobile Crowdsensing and Crowdsourcing (5 papers), Internet Traffic Analysis and Secure E-voting (5 papers) and Machine Learning and Algorithms (3 papers). The work is most often cited by research in Artificial Intelligence (588 citations), Computer Science Applications (66 citations), Health Informatics (12 citations), Management Science and Operations Research (95 citations) and Computational Theory and Mathematics (113 citations). Jonathan Ullman has collaborated with scholars based in United States, Mexico and Israel. Frequent co-authors include Adam Smith, Thomas Steinke, Aaron Roth, Cynthia Dwork, Moritz Hardt, Salil Vadhan, Mallesh M. Pai, Michael Kearns, Mark Rudelson and Shiva Prasad Kasiviswanathan. Their work appears in journals such as SIAM Journal on Computing, IEEE Transactions on Information Theory, Communications of the ACM, IEEE Transactions on Visualization and Computer Graphics and Journal of Cryptology.

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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