Jonathan Ullman

2.9k citations
57 papers · 1.1k · h-index 19

Impact in

    • Privacy-Preserving Technologies in Data
    • Cryptography and Data Security
    • Stochastic Gradient Optimization Techniques
    • Internet Traffic Analysis and Secure E-voting
    • Adversarial Robustness in Machine Learning
    • Mobile Crowdsensing and Crowdsourcing

Papers in

Jonathan Ullman

53 papers receiving 1.0k citations

Peers

Jonathan Ullman
Comparison fields: 5 of 63
  • Artificial Intelligence 893
  • Computer Science Applications 109
  • Computational Theory and Mathematics 219
  • Management Science and Operations Research 119
  • Health Informatics 11
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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 57 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017141
2 201299
3 201066
4 201566
5 201463
6 201655
7 201155
8 196751
9 201243
10 201142
11 196636
12 201435
13 201334
14 201624
15 201422
16 201420
17 201619
18 201419
19 201318
20 201516

About Jonathan Ullman

Jonathan Ullman is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Management Science and Operations Research, Sociology and Political Science and Economics and Econometrics, having authored 57 papers that have together received 1.1k indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (42 papers), Cryptography and Data Security (27 papers), Complexity and Algorithms in Graphs (12 papers), Auction Theory and Applications (7 papers), Privacy, Security, and Data Protection (7 papers), Internet Traffic Analysis and Secure E-voting (5 papers), Mobile Crowdsensing and Crowdsourcing (5 papers) and Game Theory and Voting Systems (4 papers). The work is most often cited by research in Artificial Intelligence (893 citations), Computer Science Applications (109 citations), Computational Theory and Mathematics (219 citations), Management Science and Operations Research (119 citations) and Health Informatics (11 citations). Jonathan Ullman has collaborated with scholars based in United States, Mexico and Israel. Frequent co-authors include Aaron Roth, Adam Smith, Thomas Steinke, Salil Vadhan, Cynthia Dwork, Anupam Gupta, Moritz Hardt, Mallesh M. Pai, Justin Thaler and Michael Kearns. Their work appears in journals such as SIAM Journal on Computing, IEEE Transactions on Information Theory, IEEE Transactions on Visualization and Computer Graphics, Proceedings of the ACM on Programming Languages and Theory of Computing Systems.

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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