Deepesh Data

639 total citations
19 papers, 171 citations indexed

About

Deepesh Data is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering and Computational Theory and Mathematics. According to data from OpenAlex, Deepesh Data has authored 19 papers receiving a total of 171 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 6 papers in Electrical and Electronic Engineering and 5 papers in Computational Theory and Mathematics. Recurrent topics in Deepesh Data's work include Privacy-Preserving Technologies in Data (13 papers), Cryptography and Data Security (9 papers) and Stochastic Gradient Optimization Techniques (7 papers). Deepesh Data is often cited by papers focused on Privacy-Preserving Technologies in Data (13 papers), Cryptography and Data Security (9 papers) and Stochastic Gradient Optimization Techniques (7 papers). Deepesh Data collaborates with scholars based in United States, India and Hong Kong. Deepesh Data's co-authors include Suhas Diggavi, Antonious M. Girgis, Jemin George, Peter Kairouz, Ananda Theertha Suresh, Vinod M. Prabhakaran, Linqi Song, Manoj Prabhakaran, Bikash Kumar Dey and Manoj K. Mishra and has published in prestigious journals such as IEEE Transactions on Automatic Control, IEEE Transactions on Information Theory and Journal of Cryptology.

In The Last Decade

Deepesh Data

17 papers receiving 170 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Deepesh Data United States	8	145	48	39	17	11	19	171
Wenhao Yang China	4	144 1.0×	43 0.9×	39 1.0×	4 0.2×	37 3.4×	9	157
Chen-Yu Ho Saudi Arabia	6	130 0.9×	65 1.4×	33 0.8×	5 0.3×	7 0.6×	6	197
Gregory M. Zaverucha Canada	5	51 0.4×	106 2.2×	50 1.3×	13 0.8×	3 0.3×	8	160
Takahiro Matsuda Japan	6	62 0.4×	26 0.5×	17 0.4×	18 1.1×	1 0.1×	29	99
Roopsha Samanta United States	7	24 0.2×	54 1.1×	52 1.3×	23 1.4×	6 0.5×	18	112
David Leroy France	2	152 1.0×	27 0.6×	18 0.5×	2 0.1×	32 2.9×	3	180
Peter C. Dillinger United States	5	47 0.3×	16 0.3×	18 0.5×	23 1.4×	5 0.5×	12	104
Thibault Gisselbrecht France	3	154 1.1×	27 0.6×	18 0.5×	2 0.1×	33 3.0×	4	181
Witold Hołubowicz Poland	7	73 0.5×	111 2.3×	40 1.0×	6 0.4×		36	159
Akshayaram Srinivasan United States	6	169 1.2×	12 0.3×	13 0.3×	21 1.2×	2 0.2×	12	199

Countries citing papers authored by Deepesh Data

Since Specialization

Citations

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

Fields of papers citing papers by Deepesh Data

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Deepesh Data

This figure shows the co-authorship network connecting the top 25 collaborators of Deepesh Data. A scholar is included among the top collaborators of Deepesh Data 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 Deepesh Data. Deepesh Data is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

19 of 19 papers shown

Data, Deepesh, et al.. (2024). Decentralized Optimization Resilient Against Local Data Poisoning Attacks. IEEE Transactions on Automatic Control. 70(1). 81–96.

Boyle, Elette, et al.. (2023). Must the Communication Graph of MPC Protocols be an Expander?. Journal of Cryptology. 36(3).

Data, Deepesh & Suhas Diggavi. (2023). Byzantine-Resilient High-Dimensional Federated Learning. IEEE Transactions on Information Theory. 69(10). 6639–6670. 7 indexed citations

Data, Deepesh, et al.. (2022). Decentralized Learning Robust to Data Poisoning Attacks. 2022 IEEE 61st Conference on Decision and Control (CDC). 6788–6793. 1 indexed citations

Girgis, Antonious M., Deepesh Data, & Suhas Diggavi. (2022). Distributed User-Level Private Mean Estimation. 2022 IEEE International Symposium on Information Theory (ISIT). 2196–2201. 1 indexed citations

Data, Deepesh, et al.. (2022). SPARQ-SGD: Event-Triggered and Compressed Communication in Decentralized Optimization. IEEE Transactions on Automatic Control. 68(2). 721–736. 34 indexed citations

Girgis, Antonious M., Deepesh Data, Suhas Diggavi, Peter Kairouz, & Ananda Theertha Suresh. (2021). Shuffled Model of Differential Privacy in Federated Learning. International Conference on Artificial Intelligence and Statistics. 2521–2529. 20 indexed citations

Girgis, Antonious M., Deepesh Data, & Suhas Diggavi. (2021). Differentially Private Federated Learning with Shuffling and Client Self-Sampling. 338–343. 7 indexed citations

Girgis, Antonious M., Deepesh Data, Suhas Diggavi, Peter Kairouz, & Ananda Theertha Suresh. (2021). Shuffled Model of Federated Learning: Privacy, Accuracy and Communication Trade-Offs. IEEE Journal on Selected Areas in Information Theory. 2(1). 464–478. 33 indexed citations

10.

Data, Deepesh & Suhas Diggavi. (2020). On Byzantine-Resilient High-Dimensional Stochastic Gradient Descent. 2628–2633. 4 indexed citations

11.

Data, Deepesh, et al.. (2020). SPARQ-SGD: Event-Triggered and Compressed Communication in Decentralized Optimization. 3449–3456. 17 indexed citations

12.

Girgis, Antonious M., Deepesh Data, & Suhas Diggavi. (2020). Hiding Identities: Estimation Under Local Differential Privacy. 914–919. 1 indexed citations

13.

Data, Deepesh & Suhas Diggavi. (2019). Byzantine-Tolerant Distributed Coordinate Descent. 2724–2728. 2 indexed citations

14.

Data, Deepesh, Linqi Song, & Suhas Diggavi. (2019). Data Encoding Methods for Byzantine-Resilient Distributed Optimization. 2719–2723. 11 indexed citations

15.

Data, Deepesh, Linqi Song, & Suhas Diggavi. (2018). Data Encoding for Byzantine-Resilient Distributed Gradient Descent. 863–870. 8 indexed citations

16.

Data, Deepesh, Vinod M. Prabhakaran, & Manoj Prabhakaran. (2016). Communication and Randomness Lower Bounds for Secure Computation. IEEE Transactions on Information Theory. 62(7). 3901–3929. 16 indexed citations

17.

Data, Deepesh & Vinod M. Prabhakaran. (2015). On coding for secure computing. 2737–2741. 2 indexed citations

18.

Data, Deepesh, Bikash Kumar Dey, Manoj K. Mishra, & Vinod M. Prabhakaran. (2014). How to securely compute the modulo-two sum of binary sources. arXiv (Cornell University). 496–500. 6 indexed citations

19.

Data, Deepesh & Vinod M. Prabhakaran. (2013). Communication requirements for secure computation. 2012. 211–217. 1 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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