Daniela Tuninetti

3.8k total citations
153 papers, 2.0k citations indexed

About

Daniela Tuninetti is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Daniela Tuninetti has authored 153 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 114 papers in Electrical and Electronic Engineering, 111 papers in Computer Networks and Communications and 16 papers in Artificial Intelligence. Recurrent topics in Daniela Tuninetti's work include Cooperative Communication and Network Coding (86 papers), Wireless Communication Security Techniques (75 papers) and Advanced MIMO Systems Optimization (48 papers). Daniela Tuninetti is often cited by papers focused on Cooperative Communication and Network Coding (86 papers), Wireless Communication Security Techniques (75 papers) and Advanced MIMO Systems Optimization (48 papers). Daniela Tuninetti collaborates with scholars based in United States, France and Switzerland. Daniela Tuninetti's co-authors include Giuseppe Caire, Natasha Devroye, Stefano Rini, Daniel Graupe, Christina Fragouli, Sergio Verdú, Ishita Basu, Konstantin V. Slavin, Qifa Yan and Shuang Yang and has published in prestigious journals such as IEEE Transactions on Information Theory, IEEE Journal on Selected Areas in Communications and IEEE Transactions on Communications.

In The Last Decade

Daniela Tuninetti

149 papers receiving 2.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniela Tuninetti United States 22 1.6k 1.4k 199 192 156 153 2.0k
Guofa Cai China 20 867 0.6× 460 0.3× 192 1.0× 51 0.3× 11 0.1× 77 1.3k
Stephen J. Shellhammer United States 11 926 0.6× 1.1k 0.8× 89 0.4× 6 0.0× 74 0.5× 16 1.4k
Chia‐Hsiang Yang Taiwan 19 713 0.5× 251 0.2× 54 0.3× 31 0.2× 243 1.6× 113 1.2k
Ji Wang China 14 268 0.2× 133 0.1× 192 1.0× 34 0.2× 39 0.3× 93 675
Bobak Nazer United States 21 2.3k 1.5× 2.2k 1.6× 85 0.4× 6 0.0× 16 0.1× 80 2.7k
G. Ray India 19 435 0.3× 284 0.2× 52 0.3× 7 0.0× 127 0.8× 62 1.2k
K. Tsakalis United States 21 140 0.1× 118 0.1× 63 0.3× 81 0.4× 266 1.7× 70 1.7k
Amirhossein Alimohammad Canada 15 468 0.3× 191 0.1× 64 0.3× 3 0.0× 104 0.7× 67 613
Yeseong Kim United States 19 991 0.6× 243 0.2× 7 0.0× 23 0.1× 31 0.2× 64 1.2k
Qishao Wang China 15 50 0.0× 357 0.3× 65 0.3× 40 0.2× 68 0.4× 42 600

Countries citing papers authored by Daniela Tuninetti

Since Specialization
Citations

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

Fields of papers citing papers by Daniela Tuninetti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniela Tuninetti

This figure shows the co-authorship network connecting the top 25 collaborators of Daniela Tuninetti. A scholar is included among the top collaborators of Daniela Tuninetti 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 Daniela Tuninetti. Daniela Tuninetti 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.
Yan, Qifa & Daniela Tuninetti. (2021). Robust and Secure Cache-aided Private Linear Function Retrieval from Coded Servers. 78–83. 2 indexed citations
2.
Wan, Kai, Hua Sun, Mingyue Ji, Daniela Tuninetti, & Giuseppe Caire. (2020). Cache-Aided Scalar Linear Function Retrieval. 1717–1722. 2 indexed citations
3.
Wan, Kai, Hua Sun, Mingyue Ji, Daniela Tuninetti, & Giuseppe Caire. (2020). Novel Converse for Device-to-Device Demand-Private Caching with a Trusted Server. 1705–1710. 5 indexed citations
4.
Tuninetti, Daniela, et al.. (2019). Decentralized Pliable Index Coding. 532–536. 3 indexed citations
5.
Graupe, Daniel, et al.. (2018). Who May Benefit From On-Demand Control of Deep Brain Stimulation? Noninvasive Evaluation of Parkinson Patients. Neuromodulation Technology at the Neural Interface. 21(6). 611–616. 6 indexed citations
6.
Wan, Kai, Daniela Tuninetti, Pablo Piantanida, & Mingyue Ji. (2018). On Combination Networks with Cache-aided Relays and Users. International ITG Workshop on Smart Antennas. 1–7. 2 indexed citations
7.
Wan, Kai, Daniela Tuninetti, Mingyue Ji, & Pablo Piantanida. (2018). A Novel Asymmetric Coded Placement in Combination Networks with end-user\n Caches. arXiv (Cornell University). 5 indexed citations
8.
Tuninetti, Daniela, et al.. (2018). On Identifying a Massive Number of Distributions. Figshare. 3 indexed citations
9.
Wan, Kai, Daniela Tuninetti, Mingyue Ji, & Pablo Piantanida. (2017). Combination Networks with End-user-caches: Novel Achievable and Converse\n Bounds under Uncoded Cache Placement. arXiv (Cornell University). 7 indexed citations
10.
Wan, Kai, Mingyue Ji, Pablo Piantanida, & Daniela Tuninetti. (2017). Novel Outer Bounds and Inner Bounds with Uncoded Cache Placement for Combination Networks with End-User-Caches. arXiv (Cornell University). 6 indexed citations
11.
Wan, Kai, et al.. (2017). Combination Networks with Caches: Novel Inner and Outer Bounds with Uncoded Cache Placement.. arXiv (Cornell University). 3 indexed citations
12.
Cardone, Martina, Daniela Tuninetti, Raymond Knopp, & Umer Salim. (2014). On the Capacity of the Two-User Gaussian Causal Cognitive Interference Channel. IEEE Transactions on Information Theory. 60(5). 2512–2541. 5 indexed citations
13.
Basu, Ishita, Daniel Graupe, Daniela Tuninetti, et al.. (2013). Pathological tremor prediction using surface electromyogram and acceleration: potential use in ‘ON–OFF’ demand driven deep brain stimulator design. Journal of Neural Engineering. 10(3). 36019–36019. 77 indexed citations
14.
Rini, Stefano, Daniela Tuninetti, & Natasha Devroye. (2011). A new capacity result for the Z-Gaussian cognitive interference channel. 2403–2407. 7 indexed citations
15.
Basu, Ishita, Daniela Tuninetti, Daniel Graupe, & Konstantin V. Slavin. (2011). Adaptive control of deep brain stimulator for Essential Tremor: Entropy-based tremor prediction using surface-EMG. PubMed. 2011. 7711–7714. 10 indexed citations
16.
Basu, Ishita, Daniel Graupe, Daniela Tuninetti, & Konstantin V. Slavin. (2010). Stochastic modeling of the neuronal activity in the subthalamic nucleus and model parameter identification from Parkinson patient data. Biological Cybernetics. 103(4). 273–283. 3 indexed citations
17.
Graupe, Daniel, Ishita Basu, Daniela Tuninetti, Prasad Vannemreddy, & Konstantin V. Slavin. (2010). Adaptively controlling deep brain stimulation in essential tremor patient via surface electromyography. Neurological Research. 32(9). 899–904. 46 indexed citations
18.
Rini, Stefano, Daniela Tuninetti, & Natasha Devroye. (2009). State of the cognitive interference channel: a new unified inner bound, and capacity to within 1.87 bits. arXiv (Cornell University). 8 indexed citations
19.
Niesen, Urs, Christina Fragouli, & Daniela Tuninetti. (2005). On Cascaded Channels with Finite Complexity Processing at Intermediate Nodes. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 3 indexed citations
20.
Niesen, Urs, Christina Fragouli, & Daniela Tuninetti. (2005). On the capacity of an infinite cascade of channels. 376–385. 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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