Faruk Polat

865 total citations
77 papers, 625 citations indexed

About

Faruk Polat is a scholar working on Artificial Intelligence, Molecular Biology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Faruk Polat has authored 77 papers receiving a total of 625 indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Artificial Intelligence, 25 papers in Molecular Biology and 17 papers in Computer Vision and Pattern Recognition. Recurrent topics in Faruk Polat's work include Reinforcement Learning in Robotics (21 papers), Gene Regulatory Network Analysis (21 papers) and Evolutionary Algorithms and Applications (18 papers). Faruk Polat is often cited by papers focused on Reinforcement Learning in Robotics (21 papers), Gene Regulatory Network Analysis (21 papers) and Evolutionary Algorithms and Applications (18 papers). Faruk Polat collaborates with scholars based in Türkiye, Canada and Lebanon. Faruk Polat's co-authors include Reda Alhajj, Osman Abul, Makbule Gülçin Özsoy, Tansel Özyer, Mehmet Tan, Sertan Girgin, Fazlı Can, Mohammed Alshalalfa, Güray Erus and R. Alhajj and has published in prestigious journals such as Bioinformatics, BMC Bioinformatics and Information Sciences.

In The Last Decade

Faruk Polat

72 papers receiving 600 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Faruk Polat Türkiye 12 242 195 127 119 95 77 625
Feng Pan China 15 482 2.0× 121 0.6× 33 0.3× 38 0.3× 203 2.1× 62 765
Zhiwei Lin United Kingdom 12 285 1.2× 129 0.7× 20 0.2× 124 1.0× 187 2.0× 41 627
Rob Powers United States 10 403 1.7× 148 0.8× 132 1.0× 14 0.1× 159 1.7× 11 789
Xianshun Chen Singapore 7 545 2.3× 93 0.5× 40 0.3× 49 0.4× 86 0.9× 14 874
Jiawei Zhang China 17 372 1.5× 104 0.5× 76 0.6× 28 0.2× 183 1.9× 53 663
Chris Price United Kingdom 11 396 1.6× 184 0.9× 10 0.1× 53 0.4× 30 0.3× 36 598
Rajdeep Niyogi India 13 156 0.6× 94 0.5× 17 0.1× 63 0.5× 244 2.6× 70 581
Patricia Riddle New Zealand 12 430 1.8× 91 0.5× 14 0.1× 23 0.2× 99 1.0× 57 692
Yinglong Ma China 12 373 1.5× 148 0.8× 26 0.2× 39 0.3× 256 2.7× 52 848
Qingzheng Xu China 13 337 1.4× 53 0.3× 18 0.1× 23 0.2× 81 0.9× 64 669

Countries citing papers authored by Faruk Polat

Since Specialization
Citations

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

Fields of papers citing papers by Faruk Polat

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Faruk Polat

This figure shows the co-authorship network connecting the top 25 collaborators of Faruk Polat. A scholar is included among the top collaborators of Faruk Polat 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 Faruk Polat. Faruk Polat 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.
İyigün, Cem, et al.. (2024). Population-based exploration in reinforcement learning through repulsive reward shaping using eligibility traces. Annals of Operations Research. 347(2). 1059–1091. 2 indexed citations
2.
İyigün, Cem, et al.. (2024). Potential-based reward shaping using state–space segmentation for efficiency in reinforcement learning. Future Generation Computer Systems. 157. 469–484.
3.
Polat, Faruk, et al.. (2024). Relative distances approach for multi-traveling salesmen problem. Knowledge-Based Systems. 300. 112160–112160. 2 indexed citations
4.
Polat, Faruk, et al.. (2023). Solving an industry-inspired generalization of lifelong MAPF problem including multiple delivery locations. Advanced Engineering Informatics. 57. 102026–102026. 5 indexed citations
5.
Polat, Faruk, et al.. (2019). Landmark Based Reward Shaping in Reinforcement Learning with Hidden States. OpenMETU (Middle East Technical University). 1922–1924. 7 indexed citations
6.
Polat, Faruk, et al.. (2017). Employing decomposable partially observable Markov decision processes to control gene regulatory networks. Artificial Intelligence in Medicine. 83. 14–34. 2 indexed citations
7.
Polat, Faruk, et al.. (2016). Effective gene expression data generation framework based on multi-model approach. Artificial Intelligence in Medicine. 70. 41–61. 3 indexed citations
8.
Polat, Faruk, et al.. (2016). Examining place categories for link prediction in location based social networks. 976–979. 3 indexed citations
9.
Polat, Faruk, et al.. (2013). Employing batch reinforcement learning to control gene regulation without explicitly constructing gene regulatory networks. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 2042–2048. 8 indexed citations
10.
Tan, Mehmet, et al.. (2013). Integrating machine learning techniques into robust data enrichment approach and its application to gene expression data. International Journal of Data Mining and Bioinformatics. 8(3). 247–247. 1 indexed citations
11.
Özsoy, Makbule Gülçin & Faruk Polat. (2013). Trust based recommendation systems. 1267–1274. 17 indexed citations
12.
Polat, Faruk, et al.. (2012). Employment of an evolutionary heuristic to solve the target allocation problem efficiently. Information Sciences. 222. 675–695. 18 indexed citations
13.
Tan, Mehmet, Mohammed Alshalalfa, Reda Alhajj, & Faruk Polat. (2009). Influence of Prior Knowledge in Constraint-Based Learning of Gene Regulatory Networks. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 8(1). 130–142. 18 indexed citations
14.
Tan, Mehmet, Reda Alhajj, & Faruk Polat. (2009). Automated Large-Scale Control of Gene Regulatory Networks. IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics). 40(2). 286–297. 7 indexed citations
15.
Tan, Mehmet, Reda Alhajj, & Faruk Polat. (2009). Scalable approach for effective control of gene regulatory networks. Artificial Intelligence in Medicine. 48(1). 51–59. 4 indexed citations
16.
Girgin, Sertan, Faruk Polat, & Reda Alhajj. (2007). Positive Impact of State Similarity on Reinforcement Learning Performance. IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics). 37(5). 1256–1270. 9 indexed citations
17.
Girgin, Sertan, Faruk Polat, & Reda Alhajj. (2007). State similarity based approach for improving performance in RL. OpenMETU (Middle East Technical University). 817–822. 6 indexed citations
18.
Girgin, Sertan, Faruk Polat, & Reda Alhajj. (2006). Learning by Automatic Option Discovery from Conditionally Terminating Sequences. European Conference on Artificial Intelligence. 494–498. 9 indexed citations
19.
Abul, Osman, Reda Alhajj, & Faruk Polat. (2006). A Powerful Approach for Effective Finding of Significantly Differentially Expressed Genes. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 3(3). 220–231. 2 indexed citations
20.
Abul, Osman, Reda Alhajj, Faruk Polat, & Ken Barker. (2004). Finding differentially expressed genes for pattern generation. Bioinformatics. 21(4). 445–450. 3 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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