Farman Ullah

2.0k citations
108 papers · 1.3k · h-index 22

Impact in

Papers in

Farman Ullah

95 papers receiving 1.2k citations

Peers

Farman Ullah
Comparison fields: 5 of 148
  • Modeling and Simulation 45
  • Computer Vision and Pattern Recognition 181
  • Computer Networks and Communications 191
  • Health Informatics 10
  • Control and Systems Engineering 157
Replace Mohammad-R. Akbarzadeh-T with:
Mohammad-R. Akbarzadeh-T Iran
Chia‐Hung Lin Taiwan
Danilo Pelusi Italy
Manik Sharma India
Mohamed Hammami Tunisia
Mohd Asif Shah India
Abdul Quaiyum Ansari India
Zhenhua Yu China
Jingwen Wang China
Waleed Alasmary Saudi Arabia
Farman Ullah relative to Mohammad-R. Akbarzadeh-T Iran Mohammad-R. Akbarzadeh-T's profile →
Citations per field
00.5×2.6×
Mohammad-R. Akbarzadeh-T · 1×
Citations per year

Countries citing papers authored by Farman Ullah

Since Specialization
Citations

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

Fields of papers citing papers by Farman Ullah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Farman Ullah, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Farman Ullah Line = papers co-authored together Farman Ullah links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 108 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202081
2 201868
3 201053
4 200449
5 201947
6 202247
7 202244
8 200739
9 201939
10 202039
11 200338
12 202134
13 201829
14 200528
15 202127
16 202125
17 201225
18 202123
19 202022
20 201722

About Farman Ullah

Farman Ullah is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications, Computer Vision and Pattern Recognition, Artificial Intelligence and Information Systems, having authored 108 papers that have together received 1.3k indexed citations. Recurring topics across this work include Context-Aware Activity Recognition Systems (9 papers), IoT and Edge/Fog Computing (8 papers), Vehicular Ad Hoc Networks (VANETs) (8 papers), Optimal Power Flow Distribution (8 papers), COVID-19 diagnosis using AI (7 papers), Opportunistic and Delay-Tolerant Networks (7 papers), Radio Frequency Integrated Circuit Design (6 papers) and Power System Optimization and Stability (6 papers). The work is most often cited by research in Modeling and Simulation (45 citations), Computer Vision and Pattern Recognition (181 citations), Computer Networks and Communications (191 citations), Health Informatics (10 citations) and Control and Systems Engineering (157 citations). Farman Ullah has collaborated with scholars based in Pakistan, South Korea and United Arab Emirates. Frequent co-authors include Sungchang Lee, Muhammad Asif Zahoor Raja, Yasir Muhammad, Naveed Ishtiaq Chaudhary, Hafeez Anwar, Javid Hussain, Viqar Uddin Ahmad, Kyung Sup Kwak, Yigang He and M. Iqbal Choudhary. Their work appears in journals such as Sensors, IEEE Access, Electronics, Chaos Solitons & Fractals and Wireless Communications and Mobile Computing.

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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