Serpil Üstebay

427 total citations
11 papers, 154 citations indexed

About

Serpil Üstebay is a scholar working on Signal Processing, Electrical and Electronic Engineering and Computer Networks and Communications. According to data from OpenAlex, Serpil Üstebay has authored 11 papers receiving a total of 154 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Signal Processing, 4 papers in Electrical and Electronic Engineering and 3 papers in Computer Networks and Communications. Recurrent topics in Serpil Üstebay's work include Indoor and Outdoor Localization Technologies (3 papers), Network Security and Intrusion Detection (3 papers) and Advanced Malware Detection Techniques (3 papers). Serpil Üstebay is often cited by papers focused on Indoor and Outdoor Localization Technologies (3 papers), Network Security and Intrusion Detection (3 papers) and Advanced Malware Detection Techniques (3 papers). Serpil Üstebay collaborates with scholars based in Türkiye, United Kingdom and Poland. Serpil Üstebay's co-authors include Muhammed Ali Aydın, Zeynep Turgut, Mark Sujan, Gülsüm Kübra Kaya, Ahmet Sertbaş, Colin Pilbeam, Jim Nixon, Nurullah Çalık, Tülin Atmaca and Piotr Gaj and has published in prestigious journals such as SHILAP Revista de lepidopterología, Pattern Recognition Letters and Safety Science.

In The Last Decade

Serpil Üstebay

8 papers receiving 147 citations

Peers

Serpil Üstebay

CNC

AI

SP

RNMI

IS

Debabrata Dansana India

Suneeta Satpathy India

Lirim Ashiku United States

Mohit Kumar India

Shahadate Rezvy United Kingdom

Kaiping Zheng Singapore

Noreen Kausar Malaysia

Himanshu Buckchash India

Vahid Pourahmadi Iran

Tomáš Kupka Norway

Debabrata Dansana India

Serpil Üstebay

44 ×0.5

CNC

39 ×0.4

AI

16 ×0.3

SP

13 ×0.8

RNMI

24 ×1.6

IS

Citations per year, relative to Serpil Üstebay Serpil Üstebay (= 1×) peers Debabrata Dansana

Countries citing papers authored by Serpil Üstebay

Since Specialization

Citations

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

Fields of papers citing papers by Serpil Üstebay

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Serpil Üstebay

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

All Works

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11 of 11 papers shown

1.

Üstebay, Serpil. (2025). Enhancing Zero-Day Attack Detection in IoT Networks via Isolation Forest and Ensemble Tree Models. Istanbul University - Journal of Electrical & Electronics Engineering. 25(1). 1–8.

2.

Çalık, Nurullah, et al.. (2024). Gauss-like Logarithmic Kernel Function to improve the performance of kernel machines on the small datasets. Pattern Recognition Letters. 179. 178–184. 6 indexed citations

3.

Üstebay, Serpil, et al.. (2024). Securing SCADA Systems: A Protocol-Based Intrusion Detection Approach with Shapley Analysis. 1–7. 1 indexed citations

4.

Üstebay, Serpil, et al.. (2023). A Machine Learning Approach Based on Indoor Target Positioning by Using Sensor Data Fusion and Improved Cosine Similarity. Istanbul University - Journal of Electrical & Electronics Engineering. 24(1). 218–227. 1 indexed citations

5.

Kaya, Gülsüm Kübra, Serpil Üstebay, Jim Nixon, Colin Pilbeam, & Mark Sujan. (2023). Exploring the impact of safety culture on incident reporting: Lessons learned from machine learning analysis of NHS England staff survey and incident data. Safety Science. 166. 106260–106260. 9 indexed citations

6.

Üstebay, Serpil, et al.. (2022). A comparison of machine learning algorithms in predicting COVID-19 prognostics. Internal and Emergency Medicine. 18(1). 229–239. 27 indexed citations

7.

Üstebay, Serpil, et al.. (2020). Customer Segmentation Based on Self-Organizing Maps: A Case Study on Airline Passengers. SHILAP Revista de lepidopterología. 1 indexed citations

8.

Turgut, Zeynep, et al.. (2019). Performance analysis of machine learning and deep learning classification methods for indoor localization in Internet of things environment. Transactions on Emerging Telecommunications Technologies. 30(9). 11 indexed citations

9.

Üstebay, Serpil, et al.. (2019). Analysis of Device-Free and Device Dependent Signal Filtering Approaches for Indoor Localization Based on Earth's Magnetic Field System.. 1–13.

10.

Üstebay, Serpil, Zeynep Turgut, & Muhammed Ali Aydın. (2018). Intrusion Detection System with Recursive Feature Elimination by Using Random Forest and Deep Learning Classifier. 71–76. 98 indexed citations

11.

Üstebay, Serpil, et al.. (2017). İç mekân konum tespitinde sinyal haritasının küçültülmesi ve performans analizi. Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi. 32(4). 1131–1142.

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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