John Wernsing

1.9k citations
13 papers · 1.1k · 1 hit paper · h-index 8

Impact in

    • Privacy-Preserving Technologies in Data
    • Cryptography and Data Security
    • Adversarial Robustness in Machine Learning
    • Stochastic Gradient Optimization Techniques
    • Parallel Computing and Optimization Techniques

Papers in

John Wernsing

13 papers receiving 1.0k citations

John Wernsing's Hit Papers

CryptoNets: applying neural networks to encrypted data with high throughput and accuracy 2016 · 762 citations
7620+3+6Years since publication250500750

Peers

John Wernsing
Comparison fields: 5 of 66
  • Artificial Intelligence 781
  • Hardware and Architecture 109
  • Health Informatics 15
  • Computer Networks and Communications 252
  • Computer Vision and Pattern Recognition 216
Replace Kim Laine with:
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John Wernsing relative to Kim Laine United States Kim Laine's profile →
Citations per field
00.5×7.8×
Kim Laine · 1×
Citations per year

Countries citing papers authored by John Wernsing

Since Specialization
Citations

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

Fields of papers citing papers by John Wernsing

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 15 scholars most cited alongside John Wernsing, 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 John Wernsing Line = papers co-authored together John Wernsing links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1
CryptoNets: applying neural networks to encrypted data with high throughput and accuracy
Hit paper breakdown →
2016762
2 2014115
3 201762
4 201047
5 201326
6 201016
7 201212
8 200910
9
Tempe: An Interactive Data Science Environment for Exploration of Temporal and Streaming Data
20146
10 20125
11 20103
12
The Trill Incremental Analytics Engine
20143
13 20122

About John Wernsing

John Wernsing is a scholar working on Computer Networks and Communications, Hardware and Architecture, Information Systems, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 13 papers that have together received 1.1k indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (8 papers), Embedded Systems Design Techniques (5 papers), Interconnection Networks and Systems (5 papers), Cloud Computing and Resource Management (4 papers), Advanced Database Systems and Queries (3 papers), Distributed and Parallel Computing Systems (2 papers), Chaos-based Image/Signal Encryption (2 papers) and Cryptography and Data Security (2 papers). The work is most often cited by research in Artificial Intelligence (781 citations), Hardware and Architecture (109 citations), Health Informatics (15 citations), Computer Networks and Communications (252 citations) and Computer Vision and Pattern Recognition (216 citations). John Wernsing has collaborated with scholars based in United States, United Kingdom and Israel. Frequent co-authors include Michael Naehrig, Ran Gilad-Bachrach, Nathan Dowlin, Kim Laine, Kristin Lauter, Greg Stitt, Robert DeLine, John Platt, Danyel Fisher and Mike Barnett. Their work appears in journals such as Proceedings of the IEEE, Parallel Computing, ACM SIGPLAN Notices, Proceedings of the VLDB Endowment and ACM Transactions on Architecture and Code Optimization.

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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