Daniel Kifer

14.4k citations
109 papers · 9.7k · 4 hit papers · h-index 36

Impact in

Papers in

Daniel Kifer

104 papers receiving 9.1k citations

Daniel Kifer's Hit Papers

No free lunch in data privacy 2011 · 418 citations
4180+7+14Years since publication50010001.5k2.0k2.5k

Peers

Daniel Kifer
Comparison fields: 5 of 140
  • Artificial Intelligence 7.8k
  • Computer Science Applications 1.2k
  • Sociology and Political Science 3.4k
  • Transportation 468
  • Management Science and Operations Research 723
Replace Jing Gao with:
Jing Gao United States
H. Brendan McMahan United States
Yaliang Li United States
Dong Wang United States
Stan Matwin Canada
Raymond Chi-Wing Wong Hong Kong
Lars Schmidt-Thieme Germany
Jianliang Xu Hong Kong
Brian D. Davison United States
Jing He China
Daniel Kifer relative to Jing Gao United States Jing Gao's profile →
Citations per field
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Citations per year

Countries citing papers authored by Daniel Kifer

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Kifer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daniel Kifer, 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 Daniel Kifer Line = papers co-authored together Daniel Kifer links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 109 papers — load more, or switch the sort, to bring in the rest.

#Work
1
L -diversity
Hit paper breakdown →
20072705
2
L-diversity: privacy beyond k-anonymity
Hit paper breakdown →
20061834
3
Detecting Change in Data Streams
Hit paper breakdown →
2004541
4
No free lunch in data privacy
Hit paper breakdown →
2011418
5 2008345
6 2010289
7 2006220
8 2018196
9 2007182
10 2014171
11 2017160
12 2016149
13 2017134
14 2009120
15 2009114
16 2009111
17 2018102
18 201298
19 201997
20 202293

About Daniel Kifer

Daniel Kifer is a scholar working on Artificial Intelligence, Sociology and Political Science, Computer Vision and Pattern Recognition, Information Systems and Signal Processing, having authored 109 papers that have together received 9.7k indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (48 papers), Cryptography and Data Security (27 papers), Privacy, Security, and Data Protection (17 papers), Handwritten Text Recognition Techniques (10 papers), Stochastic Gradient Optimization Techniques (10 papers), Data Management and Algorithms (7 papers), Landslides and related hazards (6 papers) and Seismology and Earthquake Studies (6 papers). The work is most often cited by research in Artificial Intelligence (7.8k citations), Computer Science Applications (1.2k citations), Sociology and Political Science (3.4k citations), Transportation (468 citations) and Management Science and Operations Research (723 citations). Daniel Kifer has collaborated with scholars based in United States, Canada and China. Frequent co-authors include Ashwin Machanavajjhala, Johannes Gehrke, Muthuramakrishnan Venkitasubramaniam, C. Lee Giles, Shai Ben-David, Hongjian Wang, Qi He, Prasenjit Mitra, Jian Pei and John M. Abowd. Their work appears in journals such as Proceedings of the VLDB Endowment, ACM Transactions on Knowledge Discovery from Data, NDT & E International, Proceedings of the National Academy of Sciences and Nature Communications.

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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