Faizan Ullah

920 total citations
29 papers, 492 citations indexed

About

Faizan Ullah is a scholar working on Artificial Intelligence, Computer Networks and Communications and Neurology. According to data from OpenAlex, Faizan Ullah has authored 29 papers receiving a total of 492 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 11 papers in Computer Networks and Communications and 9 papers in Neurology. Recurrent topics in Faizan Ullah's work include Brain Tumor Detection and Classification (9 papers), Privacy-Preserving Technologies in Data (6 papers) and Advanced Neural Network Applications (5 papers). Faizan Ullah is often cited by papers focused on Brain Tumor Detection and Classification (9 papers), Privacy-Preserving Technologies in Data (6 papers) and Advanced Neural Network Applications (5 papers). Faizan Ullah collaborates with scholars based in Pakistan, South Korea and Oman. Faizan Ullah's co-authors include Mohammad Abrar, Abdu Salam, Farhan Amin, Muhammad Nadeem, Raja Waseem Anwar, Salabat Khan, Amerah Alabrah, Muna Al‐Razgan, Taha Alfakih and Gyu Sang Choi and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Access.

In The Last Decade

Faizan Ullah

26 papers receiving 476 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Faizan Ullah Pakistan	14	177	172	141	99	92	29	492
Abdu Salam Pakistan	12	129 0.7×	122 0.7×	113 0.8×	119 1.2×	44 0.5×	33	421
Sudipta Roy India	13	130 0.7×	102 0.6×	354 2.5×	104 1.1×	52 0.6×	93	602
Meenakshi Sharma India	11	194 1.1×	216 1.3×	249 1.8×	33 0.3×	78 0.8×	26	546
A. Manikandan India	15	156 0.9×	41 0.2×	103 0.7×	186 1.9×	33 0.4×	43	545
Geng Ji China	11	275 1.6×	42 0.2×	109 0.8×	100 1.0×	26 0.3×	39	448
Abeer Saber Egypt	13	408 2.3×	142 0.8×	156 1.1×	33 0.3×	222 2.4×	24	694
Chetna Kaushal India	11	205 1.2×	42 0.2×	92 0.7×	46 0.5×	105 1.1×	44	439
Arvind Dhaka India	10	89 0.5×	118 0.7×	169 1.2×	42 0.4×	33 0.4×	48	375
M. N. Giri Prasad India	12	156 0.9×	36 0.2×	156 1.1×	73 0.7×	48 0.5×	82	543
K. Saikumar India	12	80 0.5×	42 0.2×	64 0.5×	115 1.2×	43 0.5×	55	409

Countries citing papers authored by Faizan Ullah

Since Specialization

Citations

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

Fields of papers citing papers by Faizan Ullah

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Faizan Ullah

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

All Works

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20 of 20 papers shown

Abrar, Mohammad, et al.. (2025). Enhancing brain tumor segmentation using attention based convolutional UNet on MRI images. Scientific Reports. 15(1). 36603–36603. 1 indexed citations

Sarwar, Nadeem, et al.. (2025). A flexible and lightweight signcryption scheme for underwater wireless sensor networks. Scientific Reports. 15(1). 13511–13511. 1 indexed citations

Anwar, Raja Waseem, Mohammad Abrar, & Faizan Ullah. (2025). Transformative Transfer Learning for MRI Brain Tumor Precision: Innovative Insights. IEEE Access. 13. 31749–31761. 3 indexed citations

Anwar, Raja Waseem, Mohammad Abrar, Abdu Salam, & Faizan Ullah. (2025). Federated learning with LSTM for intrusion detection in IoT-based wireless sensor networks: a multi-dataset analysis. PeerJ Computer Science. 11. e2751–e2751. 6 indexed citations

Ullah, Faizan, et al.. (2025). EcoTaskSched: a hybrid machine learning approach for energy-efficient task scheduling in IoT-based fog-cloud environments. Scientific Reports. 15(1). 12296–12296. 4 indexed citations

Abrar, Mohammad, et al.. (2025). Intelligent two-phase dual authentication framework for Internet of Medical Things. Scientific Reports. 15(1). 1760–1760. 11 indexed citations

Anwar, Raja Waseem, et al.. (2025). Advanced intrusion detection in the industrial Internet of Things using federated learning and LSTM models. Ad Hoc Networks. 178. 103991–103991. 1 indexed citations

Munir, Asim, et al.. (2024). A Dynamic Trust evaluation and update model using advance decision tree for underwater Wireless Sensor Networks. Scientific Reports. 14(1). 22393–22393. 4 indexed citations

Ullah, Faizan, et al.. (2024). Deep Trust: A Novel Framework for Dynamic Trust and Reputation Management in the Internet of Things (IoT)-Based Networks. IEEE Access. 12. 87407–87419. 16 indexed citations

10.

Salam, Abdu, et al.. (2024). Big Data Analytics Model Using Artificial Intelligence (AI) and 6G Technologies for Healthcare. IEEE Access. 12. 97924–97937. 6 indexed citations

11.

Salam, Abdu, et al.. (2024). Securing Smart Manufacturing by Integrating Anomaly Detection With Zero-Knowledge Proofs. IEEE Access. 12. 36346–36360. 26 indexed citations

12.

Salam, Abdu, et al.. (2024). Efficient prediction of anticancer peptides through deep learning. PeerJ Computer Science. 10. e2171–e2171. 8 indexed citations

13.

Ullah, Faizan, Muhammad Nadeem, & Mohammad Abrar. (2024). Revolutionizing Brain Tumor Segmentation in MRI with Dynamic Fusion of Handcrafted Features and Global Pathway-based Deep Learning. KSII Transactions on Internet and Information Systems. 18(1). 24 indexed citations

14.

Ali, Faheem, et al.. (2024). Advanced Zero-Shot Learning (AZSL) Framework for Secure Model Generalization in Federated Learning. IEEE Access. 12. 184393–184407. 22 indexed citations

15.

Ullah, Faizan, Muhammad Nadeem, Mohammad Abrar, et al.. (2023). Enhancing Brain Tumor Segmentation Accuracy through Scalable Federated Learning with Advanced Data Privacy and Security Measures. Mathematics. 11(19). 4189–4189. 54 indexed citations

16.

Salam, Abdu, et al.. (2023). Efficient Data Collaboration Using Multi-Party Privacy Preserving Machine Learning Framework. IEEE Access. 11. 138151–138164. 17 indexed citations

17.

Salam, Abdu, Faizan Ullah, Farhan Amin, & Mohammad Abrar. (2023). Deep Learning Techniques for Web-Based Attack Detection in Industry 5.0: A Novel Approach. SHILAP Revista de lepidopterología. 11(4). 107–107. 32 indexed citations

18.

Ullah, Faizan, Abdu Salam, Mohammad Abrar, & Farhan Amin. (2023). Brain Tumor Segmentation Using a Patch-Based Convolutional Neural Network: A Big Data Analysis Approach. Mathematics. 11(7). 1635–1635. 18 indexed citations

19.

Ullah, Faizan, Muhammad Nadeem, Mohammad Abrar, et al.. (2023). Brain Tumor Segmentation from MRI Images Using Handcrafted Convolutional Neural Network. Diagnostics. 13(16). 2650–2650. 50 indexed citations

20.

Shah, Pir Masoom, Faizan Ullah, Abdullah Gani, et al.. (2021). Deep GRU-CNN Model for COVID-19 Detection From Chest X-Rays Data. IEEE Access. 10. 35094–35105. 49 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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