Nina Taft

7.2k total citations
83 papers, 3.9k citations indexed

About

Nina Taft is a scholar working on Computer Networks and Communications, Artificial Intelligence and Statistical and Nonlinear Physics. According to data from OpenAlex, Nina Taft has authored 83 papers receiving a total of 3.9k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Computer Networks and Communications, 31 papers in Artificial Intelligence and 17 papers in Statistical and Nonlinear Physics. Recurrent topics in Nina Taft's work include Network Traffic and Congestion Control (30 papers), Network Security and Intrusion Detection (16 papers) and Complex Network Analysis Techniques (15 papers). Nina Taft is often cited by papers focused on Network Traffic and Congestion Control (30 papers), Network Security and Intrusion Detection (16 papers) and Complex Network Analysis Techniques (15 papers). Nina Taft collaborates with scholars based in United States, France and Switzerland. Nina Taft's co-authors include Christophe Diot, Konstantina Papagiannaki, Supratik Bhattacharyya, Kavé Salamatian, Udi Weinsberg, Stratis Ioannidis, Anukool Lakhina, Mark Crovella, A. M. Gago and Ling Huang and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Information Theory and IEEE Journal on Selected Areas in Communications.

In The Last Decade

Nina Taft

83 papers receiving 3.7k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Nina Taft United States 33 2.3k 1.9k 782 526 414 83 3.9k
Anukool Lakhina United States 19 4.1k 1.8× 2.6k 1.4× 540 0.7× 372 0.7× 699 1.7× 25 4.8k
Konstantina Papagiannaki United States 39 5.0k 2.1× 1.8k 0.9× 2.4k 3.0× 696 1.3× 532 1.3× 98 5.9k
Matthew Roughan Australia 34 4.5k 2.0× 1.9k 1.0× 1.5k 1.9× 376 0.7× 449 1.1× 139 5.9k
Adam Meyerson United States 23 1.6k 0.7× 1.6k 0.8× 427 0.5× 286 0.5× 662 1.6× 61 3.6k
Amos Fiat Israel 34 2.8k 1.2× 1.5k 0.8× 381 0.5× 745 1.4× 285 0.7× 116 4.7k
Steve Uhlig United Kingdom 34 6.8k 2.9× 1.8k 1.0× 2.0k 2.5× 1.1k 2.0× 403 1.0× 162 7.9k
Ting He United States 31 3.4k 1.5× 2.1k 1.1× 1.4k 1.8× 997 1.9× 91 0.2× 181 5.2k
Paul Barford United States 35 6.0k 2.6× 2.4k 1.2× 1.4k 1.8× 1.1k 2.2× 753 1.8× 151 6.9k
Allan Borodin Canada 33 2.9k 1.2× 1.4k 0.7× 584 0.7× 494 0.9× 251 0.6× 105 5.2k
David Peleg Israel 51 5.9k 2.5× 1.6k 0.8× 876 1.1× 219 0.4× 319 0.8× 305 8.5k

Countries citing papers authored by Nina Taft

Since Specialization
Citations

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

Fields of papers citing papers by Nina Taft

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nina Taft

This figure shows the co-authorship network connecting the top 25 collaborators of Nina Taft. A scholar is included among the top collaborators of Nina Taft based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Nina Taft. Nina Taft is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Peddinti, Sai Teja, et al.. (2021). A Large Scale Study of User Behavior, Expectations and Engagement with Android Permissions. USENIX Security Symposium. 803–820. 7 indexed citations
2.
Peddinti, Sai Teja, et al.. (2017). Exploring decision making with android's runtime permission dialogs using in-context surveys. Document Server@UHasselt (UHasselt). 195–210. 24 indexed citations
3.
Taft, Nina, et al.. (2016). Intuitions, Analytics, and Killing Ants: Inference Literacy of High School-educated Adults in the {US}. Symposium On Usable Privacy and Security. 271–285. 15 indexed citations
4.
Salamatian, Salman, Nadia Fawaz, Branislav Kveton, & Nina Taft. (2014). SPPM: sparse privacy preserving mappings. Uncertainty in Artificial Intelligence. 712–721. 3 indexed citations
5.
Salamatian, Salman, Amy Zhang, Flávio P. Calmon, et al.. (2013). How to hide the elephant- or the donkey- in the room: Practical privacy against statistical inference for large data. 269–272. 45 indexed citations
6.
Agosta, John Mark, Jaideep Chandrashekar, Mark Crovella, Nina Taft, & Daniel Ting. (2013). Mixture models of endhost network traffic. 2744. 225–229. 4 indexed citations
7.
Mokryn, Osnat, et al.. (2012). Finding a needle in a haystack of reviews. 115–122. 94 indexed citations
8.
Weinsberg, Udi, Smriti Bhagat, Stratis Ioannidis, & Nina Taft. (2012). BlurMe. 195–202. 102 indexed citations
9.
Fall, Kevin, et al.. (2010). A disruption-tolerant architecture for secure and efficient disaster response communications.. ISCRAM. 37 indexed citations
10.
Rubinstein, Benjamin I. P., Blaine Nelson, Ling Huang, et al.. (2009). ANTIDOTE. 1–14. 189 indexed citations
11.
Rubinstein, Benjamin I. P., Blaine Nelson, Ling Huang, et al.. (2008). Evading Anomaly Detection through Variance Injection Attacks on PCA (Extended Abstract). 5230. 2 indexed citations
12.
Guha, Saikat, Jaideep Chandrashekar, Nina Taft, & Konstantina Papagiannaki. (2008). How healthy are today's enterprise networks?. 145–150. 19 indexed citations
13.
Koushanfar, Farinaz, Nina Taft, & Miodrag Potkonjak. (2006). Sleeping Coordination for Comprehensive Sensing Using Isotonic Regression and Domatic Partitions. 29. 1–13. 39 indexed citations
14.
Taft, Nina, et al.. (2005). A Fast Lightweight Approach to Orgin-Destination IP Traffic Estimation Using Partial Measurements. eScholarship (California Digital Library). 2 indexed citations
15.
Papagiannaki, Konstantina, et al.. (2005). Long-Term Forecasting of Internet Backbone Traffic. IEEE Transactions on Neural Networks. 16(5). 1110–1124. 100 indexed citations
16.
Nucci, Antonio, Nina Taft, Patrick Thiran, Hui Zang, & Christophe Diot. (2005). Increasing the Link Utilization in IP over WDM Networks Using Availability as QoS. Photonic Network Communications. 9(1). 55–75. 5 indexed citations
17.
Nucci, Antonio, Rene L. Cruz, Nina Taft, & Christophe Diot. (2004). Design of IGP Link Weights for Estimation of Traffic Matrices.. 2341–2351. 6 indexed citations
18.
Nucci, A., Nina Taft, Chadi Barakat, & Patrick Thiran. (2004). Controlled Use of Excess Backbone Bandwidth for Providing New Services in IP-Over-WDM Networks. IEEE Journal on Selected Areas in Communications. 22(9). 1692–1707. 15 indexed citations
19.
Medina, Andrés Muñoz, Kavé Salamatian, Nina Taft, Ibrahim Matta, & Christophe Diot. (2004). A Two-step Statistical Approach for Inferring Network TrafficDemands (Revises Technical Report BUCS-2003-003). OpenBU (Boston University). 1 indexed citations
20.
Lakhina, Anukool, Konstantina Papagiannaki, Mark Crovella, et al.. (2003). Analysis of OD Flows (Raw Data). OpenBU/Boston University Institutional Repository (Boston University). 2 indexed citations

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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