Amin Ullah

514 total citations · 1 hit paper
10 papers, 299 citations indexed

About

Amin Ullah is a scholar working on Computer Vision and Pattern Recognition, Molecular Biology and Computational Mechanics. According to data from OpenAlex, Amin Ullah has authored 10 papers receiving a total of 299 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Computer Vision and Pattern Recognition, 2 papers in Molecular Biology and 2 papers in Computational Mechanics. Recurrent topics in Amin Ullah's work include Combustion and flame dynamics (2 papers), Computational Fluid Dynamics and Aerodynamics (2 papers) and Advanced Neural Network Applications (2 papers). Amin Ullah is often cited by papers focused on Combustion and flame dynamics (2 papers), Computational Fluid Dynamics and Aerodynamics (2 papers) and Advanced Neural Network Applications (2 papers). Amin Ullah collaborates with scholars based in Pakistan, United States and China. Amin Ullah's co-authors include Fawad Fawad, Jianqiang Li, Tariq Mahmood, Shanshan Tu, Muhammad Ehatisham-ul-Haq, Sadaqat Ur Rehman, Raja Majid Mehmood, Lubna Nadeem, Amjad Rehman and Tanzila Saba and has published in prestigious journals such as IEEE Access, Sensors and Applied Sciences.

In The Last Decade

Amin Ullah

9 papers receiving 288 citations

Hit Papers

Smart cities: the role of Internet of Things and machine ... 2023 2026 2024 2025 2023 25 50 75 100

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Amin Ullah Pakistan 5 87 65 49 48 46 10 299
Hailan Kuang China 10 43 0.5× 22 0.3× 42 0.9× 76 1.6× 123 2.7× 70 361
Ehab Essa Egypt 13 110 1.3× 75 1.2× 115 2.3× 82 1.7× 164 3.6× 26 436
Eoin Brophy Ireland 8 67 0.8× 52 0.8× 113 2.3× 62 1.3× 74 1.6× 12 318
Shir Li Wang Malaysia 10 32 0.4× 30 0.5× 74 1.5× 23 0.5× 85 1.8× 32 263
Bachir Boucheham Algeria 8 101 1.2× 53 0.8× 69 1.4× 79 1.6× 66 1.4× 33 300
Deepta Rajan United States 8 42 0.5× 27 0.4× 213 4.3× 27 0.6× 33 0.7× 19 400
Juan-Carlos Pérez-Cortés Spain 12 33 0.4× 21 0.3× 161 3.3× 30 0.6× 169 3.7× 51 355
Kazım Hanbay Türkiye 12 32 0.4× 28 0.4× 49 1.0× 21 0.4× 271 5.9× 33 508
S. Lokesh India 7 34 0.4× 16 0.2× 90 1.8× 48 1.0× 63 1.4× 41 391

Countries citing papers authored by Amin Ullah

Since Specialization
Citations

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

Fields of papers citing papers by Amin Ullah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Amin Ullah

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

All Works

10 of 10 papers shown
1.
Ullah, Amin, et al.. (2023). Robust Deep Neural Network-Based Framework for Predicting and Classifying Capsid Protein Based on Biomedical Data. IEEE Access. 11. 107412–107428. 1 indexed citations
2.
Ullah, Amin, Jianqiang Li, Lubna Nadeem, et al.. (2023). Smart cities: the role of Internet of Things and machine learning in realizing a data-centric smart environment. Complex & Intelligent Systems. 10(1). 1607–1637. 106 indexed citations breakdown →
3.
Mehmood, Zahid, et al.. (2023). High-Definition Image Formation Using Multi-stage Cycle Generative Adversarial Network with Applications in Image Forensic. Arabian Journal for Science and Engineering. 49(3). 3887–3896.
4.
Mehmood, Zahid, et al.. (2022). Stress Estimation Model for the Sustainable Health of Cancer Patients. Computational and Mathematical Methods in Medicine. 2022. 1–11. 1 indexed citations
5.
Iqbal, Saeed, Adnan N. Qureshi, Amin Ullah, Jianqiang Li, & Tariq Mahmood. (2022). Improving the Robustness and Quality of Biomedical CNN Models through Adaptive Hyperparameter Tuning. Applied Sciences. 12(22). 11870–11870. 23 indexed citations
6.
Ali, Shaukat, et al.. (2022). Publishing and Interlinking COVID-19 Data Using Linked Open Data Principles: Toward Effective Healthcare Planning and Decision-Making. Mathematical Problems in Engineering. 2022. 1–16. 4 indexed citations
7.
Ullah, Amin, Sadaqat Ur Rehman, Shanshan Tu, et al.. (2021). A Hybrid Deep CNN Model for Abnormal Arrhythmia Detection Based on Cardiac ECG Signal. Sensors. 21(3). 951–951. 108 indexed citations
8.
Masud, Jehanzeb, et al.. (2020). Numerical Modeling and Analysis of Afterburner Combustion of a Low Bypass Ratio Turbofan Engine. AIAA Scitech 2020 Forum. 7 indexed citations
9.
Jamil, Sonain, et al.. (2020). Malicious UAV Detection Using Integrated Audio and Visual Features for Public Safety Applications. Sensors. 20(14). 3923–3923. 47 indexed citations
10.
Masud, Jehanzeb, et al.. (2020). Numerical Analysis of Afterburner Characteristics of a Low Bypass Ratio Turbofan Engine at Various Flight Conditions. AIAA Scitech 2020 Forum. 2 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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