Erçan E. Kuruoğlu

2.8k total citations
149 papers, 1.9k citations indexed

About

Erçan E. Kuruoğlu is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Erçan E. Kuruoğlu has authored 149 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Artificial Intelligence, 38 papers in Signal Processing and 32 papers in Computer Vision and Pattern Recognition. Recurrent topics in Erçan E. Kuruoğlu's work include Blind Source Separation Techniques (30 papers), Image and Signal Denoising Methods (18 papers) and Spectroscopy and Chemometric Analyses (18 papers). Erçan E. Kuruoğlu is often cited by papers focused on Blind Source Separation Techniques (30 papers), Image and Signal Denoising Methods (18 papers) and Spectroscopy and Chemometric Analyses (18 papers). Erçan E. Kuruoğlu collaborates with scholars based in Italy, China and Türkiye. Erçan E. Kuruoğlu's co-authors include Josiane Zerubia, Alin Achim, William J. Fitzgerald, Oktay Karakuş, P. J. Rayner, Diego P. Ruíz, D. Salas-González, D. Herranz, Emanuele Salerno and Anna Tonazzini and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Journal of Materials Chemistry A.

In The Last Decade

Erçan E. Kuruoğlu

130 papers receiving 1.8k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Erçan E. Kuruoğlu 552 485 387 376 298 149 1.9k
Nikolaos Galatsanos 1.0k 1.9× 496 1.0× 302 0.8× 204 0.5× 382 1.3× 53 2.0k
Paul Honeiné 540 1.0× 844 1.7× 433 1.1× 277 0.7× 322 1.1× 75 2.1k
D. Hush 417 0.8× 664 1.4× 312 0.8× 377 1.0× 281 0.9× 42 1.8k
Tianshuang Qiu 534 1.0× 354 0.7× 965 2.5× 413 1.1× 310 1.0× 194 2.7k
P. Tseng 576 1.0× 592 1.2× 238 0.6× 311 0.8× 137 0.5× 15 2.3k
Mark E. Oxley 321 0.6× 611 1.3× 209 0.5× 214 0.6× 169 0.6× 115 1.7k
Konstantinos Koutroumbas 500 0.9× 613 1.3× 274 0.7× 116 0.3× 257 0.9× 71 1.7k
Jian Lü 1.2k 2.2× 559 1.2× 270 0.7× 216 0.6× 450 1.5× 132 2.3k
Jinshan Zeng 574 1.0× 372 0.8× 113 0.3× 200 0.5× 281 0.9× 72 1.7k
Peng‐Lang Shui 814 1.5× 508 1.0× 363 0.9× 234 0.6× 387 1.3× 222 2.8k

Countries citing papers authored by Erçan E. Kuruoğlu

Since Specialization
Citations

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

Fields of papers citing papers by Erçan E. Kuruoğlu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Erçan E. Kuruoğlu. 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 Erçan E. Kuruoğlu. The network helps show where Erçan E. Kuruoğlu may publish in the future.

Co-authorship network of co-authors of Erçan E. Kuruoğlu

This figure shows the co-authorship network connecting the top 25 collaborators of Erçan E. Kuruoğlu. A scholar is included among the top collaborators of Erçan E. Kuruoğlu 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 Erçan E. Kuruoğlu. Erçan E. Kuruoğlu 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.
Li, Yang, et al.. (2025). Cauchy Graph Convolutional Networks. International Journal of Approximate Reasoning. 186. 109517–109517.
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Kuruoğlu, Erçan E., et al.. (2025). Adaptive Joint Estimation of Temporal Vertex and Edge Signals. IEEE Transactions on Signal and Information Processing over Networks. 11. 215–229. 1 indexed citations
4.
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Kuruoğlu, Erçan E., et al.. (2024). Optimized Parameter-Efficient Deep Learning Systems via Reversible Jump Simulated Annealing. IEEE Journal of Selected Topics in Signal Processing. 18(6). 1010–1023. 2 indexed citations
6.
Li, Yang, et al.. (2024). Stable Probabilistic Graphical Models for Systemic Risk Estimation. 1340–1345. 1 indexed citations
7.
Zhang, Hengxi, et al.. (2024). Optimizing Trading Strategies in Quantitative Markets Using Multi-Agent Reinforcement Learning. 136–140. 1 indexed citations
8.
Kuruoğlu, Erçan E., et al.. (2023). Attention based hybrid parametric and neural network models for non‐stationary time series prediction. Expert Systems. 41(2). 7 indexed citations
9.
Li, Yiming, et al.. (2023). Portfolio Selection via Graph-Aware Gaussian Processes With Generalized Gaussian Likelihood. IEEE Transactions on Artificial Intelligence. 5(2). 505–515. 3 indexed citations
10.
Li, Yang, et al.. (2023). SDG-L: A Semiparametric Deep Gaussian Process based Framework for Battery Capacity Prediction. ArXiv.org. 1–5. 1 indexed citations
11.
Kuruoğlu, Erçan E., et al.. (2023). Cross-Sign Language Transfer Learning Using Domain Adaptation with Multi-scale Temporal Alignment. Multimedia Tools and Applications. 83(12). 37025–37051.
12.
Kuruoğlu, Erçan E. & Li Yang. (2021). Modelling Time-Varying Epidemiological Parameters for COVID-19. ERCIM news/ERCIM news online edition. 2021(124). 25–26. 2 indexed citations
13.
Kuruoğlu, Erçan E., et al.. (2021). A Hybrid Model Integrating LSTM and Garch for Bitcoin Price Prediction. 1–6. 12 indexed citations
14.
Fu, Wanyi, et al.. (2020). Interpretable machine learning modeling of capacitive deionization for contribution analysis of electrode and process features. Journal of Materials Chemistry A. 9(4). 2259–2268. 26 indexed citations
15.
Wang, Zifeng, Xi Chen, Rui Wen, et al.. (2020). Information Theoretic Counterfactual Learning from Missing-Not-At-Random Feedback. Neural Information Processing Systems. 33. 1854–1864. 1 indexed citations
16.
Argüeso, F., Emanuele Salerno, D. Herranz, et al.. (2011). A Bayesian technique for the detection of point sources in cosmic microwave background maps. LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas). 8 indexed citations
17.
Salas-González, D., Erçan E. Kuruoğlu, & Diego P. Ruíz. (2009). Modelling and Assessing Differential Gene Expression Using the Alpha Stable Distribution. The International Journal of Biostatistics. 5(1). 4 indexed citations
18.
Herranz, D., Erçan E. Kuruoğlu, & L. Toffolatti. (2004). An α-stable approach to the study of the P(D) distribution of unresolved point sources in CMB sky maps. Astronomy and Astrophysics. 424(3). 1081–1096. 20 indexed citations
19.
Herranz, D., Erçan E. Kuruoğlu, & L. Toffolatti. (2003). Using alpha-stable distributions to model the P(D) distribution of point sources in CMB sky maps. arXiv (Cornell University). 1 indexed citations
20.
Kuruoğlu, Erçan E., et al.. (1998). Approximation of α-stable probability densities using finite Gaussian mixtures. European Signal Processing Conference. 1–4. 15 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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