Volkan Cevher

8.0k total citations · 1 hit paper
197 papers, 3.8k citations indexed

About

Volkan Cevher is a scholar working on Computational Mechanics, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Volkan Cevher has authored 197 papers receiving a total of 3.8k indexed citations (citations by other indexed papers that have themselves been cited), including 112 papers in Computational Mechanics, 89 papers in Artificial Intelligence and 56 papers in Signal Processing. Recurrent topics in Volkan Cevher's work include Sparse and Compressive Sensing Techniques (103 papers), Blind Source Separation Techniques (34 papers) and Stochastic Gradient Optimization Techniques (28 papers). Volkan Cevher is often cited by papers focused on Sparse and Compressive Sensing Techniques (103 papers), Blind Source Separation Techniques (34 papers) and Stochastic Gradient Optimization Techniques (28 papers). Volkan Cevher collaborates with scholars based in Switzerland, United States and France. Volkan Cevher's co-authors include James H. McClellan, Richard G. Baraniuk, Philip Schniter, Andreas Tittl, Filiz Yesilköy, Yuri S. Kivshar, Yasaman Jahani, Hatice Altug, Eduardo R. Arvelo and Mingkai Liu and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Proceedings of the IEEE and Nature Photonics.

In The Last Decade

Volkan Cevher

187 papers receiving 3.6k citations

Hit Papers

Ultrasensitive hyperspectral imaging and biodetection ena... 2019 2026 2021 2023 2019 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Volkan Cevher Switzerland 31 1.5k 1.1k 982 894 780 197 3.8k
Dharmpal Takhar United States 9 2.1k 1.4× 882 0.8× 1.5k 1.5× 461 0.5× 235 0.3× 11 3.8k
Vivek K Goyal United States 48 1.3k 0.9× 1.4k 1.4× 1.1k 1.2× 1.7k 1.9× 784 1.0× 211 8.0k
Jason N. Laska United States 21 4.1k 2.7× 1.6k 1.5× 2.6k 2.6× 1.3k 1.4× 303 0.4× 24 5.9k
Thierry Blu Hong Kong 25 1.5k 1.0× 600 0.6× 717 0.7× 880 1.0× 201 0.3× 133 4.0k
Mark A. Davenport United States 27 4.9k 3.3× 1.6k 1.5× 2.8k 2.8× 1.7k 1.9× 713 0.9× 82 7.9k
Arjuna Madanayake United States 24 312 0.2× 2.6k 2.4× 459 0.5× 716 0.8× 342 0.4× 263 3.9k
Yue Gao United Kingdom 41 678 0.5× 3.7k 3.5× 481 0.5× 334 0.4× 614 0.8× 304 6.1k
R. Unbehauen Germany 28 484 0.3× 675 0.6× 422 0.4× 844 0.9× 1.3k 1.7× 259 3.8k
Laurent Daudet France 24 610 0.4× 326 0.3× 499 0.5× 1.5k 1.7× 648 0.8× 100 3.6k
Gianluca Setti Italy 39 758 0.5× 1.5k 1.4× 715 0.7× 331 0.4× 642 0.8× 336 5.7k

Countries citing papers authored by Volkan Cevher

Since Specialization
Citations

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

Fields of papers citing papers by Volkan Cevher

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Volkan Cevher

This figure shows the co-authorship network connecting the top 25 collaborators of Volkan Cevher. A scholar is included among the top collaborators of Volkan Cevher 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 Volkan Cevher. Volkan Cevher 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.
Kübler, Jonas M., Jiaji Huang, Matthäus Kleindeßner, et al.. (2024). Inference Optimization of Foundation Models on AI Accelerators. 6605–6615. 4 indexed citations
2.
Trouillet, Alix, Florian Fallegger, Azita Emami, et al.. (2022). A 16-Channel Neural Recording System-on-Chip With CHT Feature Extraction Processor in 65-nm CMOS. IEEE Journal of Solid-State Circuits. 57(9). 2752–2763. 8 indexed citations
3.
Cevher, Volkan, et al.. (2021). An Optimal-Storage Approach to Semidefinite Programming Using Approximate Complementarity. SIAM Journal on Optimization. 31(4). 2695–2725. 7 indexed citations
4.
Levy, Kfir Y., et al.. (2021). STORM+: Fully Adaptive SGD with Recursive Momentum for Nonconvex Optimization. Neural Information Processing Systems. 34. 2 indexed citations
5.
Lin, Junhong & Volkan Cevher. (2020). Convergences of Regularized Algorithms and Stochastic Gradient Methods with Random Projections. Journal of Machine Learning Research. 21(20). 1–44. 5 indexed citations
6.
Fercoq, Olivier, et al.. (2019). Almost surely constrained convex optimization. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 1 indexed citations
7.
Kamalaruban, Parameswaran, et al.. (2019). Interactive Teaching Algorithms for Inverse Reinforcement Learning. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 13 indexed citations
8.
Eftekhari, Armin, et al.. (2019). Fast and Provable ADMM for Learning with Generative Priors. Neural Information Processing Systems. 32. 12027–12039. 7 indexed citations
9.
Sra, Suvrit, et al.. (2019). Conditional Gradient Methods via Stochastic Path-Integrated Differential Estimator. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 7282–7291. 5 indexed citations
10.
Baldassarre, Luca, Mahsa Shoaran, Franco Maloberti, et al.. (2018). Adaptive Learning-Based Compressive Sampling for Low-power Wireless Implants. IEEE Transactions on Circuits and Systems I Regular Papers. 65(11). 3929–3941. 12 indexed citations
11.
Bogunovic, Ilija, et al.. (2018). Robust Maximization of Non-Submodular Objectives.. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 890–899. 1 indexed citations
12.
Cevher, Volkan, et al.. (2018). Stochastic Three-Composite Convex Minimization with a Linear Operator. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 765–774. 5 indexed citations
13.
Scarlett, Jonathan & Volkan Cevher. (2017). Efficient and Near-Optimal Noisy Group Testing: An Information-Theoretic Framework. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 1 indexed citations
14.
Mitrović, Slobodan, et al.. (2017). Streaming Robust Submodular Maximization: A Partitioned Thresholding Approach. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 30. 4557–4566. 6 indexed citations
15.
Carlson, David, Volkan Cevher, & Lawrence Carin. (2015). Stochastic Spectral Descent for Restricted Boltzmann Machines. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 111–119. 17 indexed citations
16.
Signoretto, Marco, Volkan Cevher, & Johan A. K. Suykens. (2013). An SVD-free Approach to a Class of Structured Low Rank Matrix Optimization Problems with Application to System Identification. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 23 indexed citations
17.
Cevher, Volkan, et al.. (2012). Active Learning of Multi-Index Function Models. Neural Information Processing Systems. 25. 1466–1474. 15 indexed citations
18.
Cevher, Volkan, et al.. (2011). Compressible Priors for High-dimensional Statistics. arXiv (Cornell University). 4 indexed citations
19.
Krause, Andreas & Volkan Cevher. (2010). Submodular Dictionary Selection for Sparse Representation. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 567–574. 53 indexed citations
20.
Cevher, Volkan, Marco F. Duarte, & Richard G. Baraniuk. (2008). Distributed target localization via spatial sparsity. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 1–5. 110 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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