Başak Güler

1.5k total citations · 1 hit paper
46 papers, 860 citations indexed

About

Başak Güler is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering and Statistical and Nonlinear Physics. According to data from OpenAlex, Başak Güler has authored 46 papers receiving a total of 860 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Artificial Intelligence, 13 papers in Electrical and Electronic Engineering and 10 papers in Statistical and Nonlinear Physics. Recurrent topics in Başak Güler's work include Privacy-Preserving Technologies in Data (18 papers), Cryptography and Data Security (12 papers) and Complex Network Analysis Techniques (9 papers). Başak Güler is often cited by papers focused on Privacy-Preserving Technologies in Data (18 papers), Cryptography and Data Security (12 papers) and Complex Network Analysis Techniques (9 papers). Başak Güler collaborates with scholars based in United States, Canada and United Kingdom. Başak Güler's co-authors include A. Salman Avestimehr, Jinhyun So, Aylin Yener, Ananthram Swami, A. S. Grader, Turgay Ertekin, F. Gümrah, Jiantao Jiao, Prithwish Basu and Antonio Ortega 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

Başak Güler

42 papers receiving 844 citations

Hit Papers

Turbo-Aggregate: Breaking the Quadratic Aggregation Barri... 2021 2026 2022 2024 2021 50 100 150
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Turbo-Aggregate: Breaking the Quadratic Aggregation Barrier in Secure Federated Learning
    2021 184 citations Jinhyun So, Başak Güler et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Başak Güler United States 13 554 237 193 65 52 46 860
Ruilin Liu United States 11 121 0.2× 73 0.3× 86 0.4× 27 0.4× 49 0.9× 28 329
John Bellardo United States 12 179 0.3× 380 1.6× 831 4.3× 20 0.3× 32 0.6× 34 1.2k
Jun Tao China 12 108 0.2× 150 0.6× 221 1.1× 30 0.5× 4 0.1× 102 457
Jia Liu China 15 112 0.2× 260 1.1× 536 2.8× 103 1.6× 11 0.2× 123 735
Thomas Wagner Austria 8 163 0.3× 77 0.3× 109 0.6× 10 0.2× 9 0.2× 26 397
Stefania Monica Italy 12 103 0.2× 210 0.9× 108 0.6× 109 1.7× 12 0.2× 48 375
Hamid Esmaeili Najafabadi Canada 10 101 0.2× 111 0.5× 102 0.5× 26 0.4× 5 0.1× 28 418
Jian Shu China 10 79 0.1× 160 0.7× 242 1.3× 50 0.8× 10 0.2× 95 403
E. Zervas Greece 12 212 0.4× 168 0.7× 179 0.9× 25 0.4× 9 0.2× 48 534

Countries citing papers authored by Başak Güler

Since Specialization
Citations

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

Fields of papers citing papers by Başak Güler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Başak Güler

This figure shows the co-authorship network connecting the top 25 collaborators of Başak Güler. A scholar is included among the top collaborators of Başak Güler 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 Başak Güler. Başak Güler 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.
Sen, Supatra, et al.. (2025). Gradient Inversion Attacks on Parameter-Efficient Fine-Tuning. 10224–10234. 1 indexed citations
2.
Alanazi, Turki M., Başak Güler, Amit Roy Chowdhury, et al.. (2025). FedBand: Adaptive Federated Learning Under Strict Bandwidth Constraints. 1–9.
3.
Lu, Xingyu, et al.. (2024). Scalable Multi-Round Multi-Party Privacy-Preserving Neural Network Training. IEEE Transactions on Information Theory. 70(11). 8204–8236. 2 indexed citations
4.
Güler, Başak, et al.. (2024). Secure Aggregation for Clustered Federated Learning With Passive Adversaries. IEEE Transactions on Communications. 72(7). 4117–4133. 1 indexed citations
5.
So, Jinhyun, et al.. (2023). Securing Secure Aggregation: Mitigating Multi-Round Privacy Leakage in Federated Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 37(8). 9864–9873. 39 indexed citations
6.
Chang, Xiangyu, et al.. (2023). Federated Learning for Massive MIMO Power Allocation. 651–655.
7.
Anantharajah, Ahalieyah, Frédéric Goormaghtigh, Başak Güler, et al.. (2023). Long-term intensive care unit outbreak of carbapenemase-producing organisms associated with contaminated sink drains. Journal of Hospital Infection. 143. 38–47. 15 indexed citations
8.
Lu, Xingyu, et al.. (2023). SCALR: Communication-Efficient Secure Multi-Party Logistic Regression. IEEE Transactions on Communications. 72(1). 162–178. 2 indexed citations
9.
10.
Güler, Başak, et al.. (2022). Communication-Efficient Secure Aggregation for Federated Learning. GLOBECOM 2022 - 2022 IEEE Global Communications Conference. 3881–3886. 7 indexed citations
11.
So, Jinhyun, Başak Güler, & Salman Avestimehr. (2020). A Scalable Approach for Privacy-Preserving Collaborative Machine Learning. Neural Information Processing Systems. 33. 8054–8066. 2 indexed citations
12.
So, Jinhyun, Başak Güler, & A. Salman Avestimehr. (2020). Byzantine-Resilient Secure Federated Learning. IEEE Journal on Selected Areas in Communications. 39(7). 2168–2181. 187 indexed citations
13.
Güler, Başak, et al.. (2019). Robust Graph Signal Sampling. 50. 7520–7524. 3 indexed citations
14.
Güler, Başak, Aylin Yener, & Ananthram Swami. (2018). The Semantic Communication Game. IEEE Transactions on Cognitive Communications and Networking. 4(4). 787–802. 112 indexed citations
15.
Güler, Başak, Aylin Yener, & Ananthram Swami. (2016). Learning causal information flow structures in multi-layer networks. 301. 1340–1344. 2 indexed citations
16.
Güler, Başak, et al.. (2014). Optimal strategies for targeted influence in signed networks. 906–911. 4 indexed citations
17.
Güler, Başak & Aylin Yener. (2014). Compressing Semantic Information with Varying Priorities. 213–222. 3 indexed citations
18.
Güler, Başak & Aylin Yener. (2014). Semantic index assignment. 431–436. 18 indexed citations
19.
Güler, Başak & Aylin Yener. (2014). Selective Interference Alignment for MIMO Cognitive Femtocell Networks. IEEE Journal on Selected Areas in Communications. 32(3). 439–450. 48 indexed citations
20.
Güler, Başak, et al.. (2014). Communicating in a socially-aware network: Impact of relationship types. 788–792. 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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