Aman Ullah

908 citations
28 papers · 583 · h-index 15

Impact in

Papers in

Aman Ullah

27 papers receiving 568 citations

Peers

Aman Ullah
Comparison fields: 5 of 81
  • Statistical and Nonlinear Physics 355
  • Artificial Intelligence 184
  • Experimental and Cognitive Psychology 65
  • Computer Networks and Communications 110
  • Information Systems 100
Replace Zejun Sun with:
Zejun Sun China
Lotfi Ben Romdhane Tunisia
Ahmad Zareie United Kingdom
Dónal Doyle Ireland
Xiao-Long Ren China
Hao Yin United States
Giridhar Maji India
Yasuko Matsubara Japan
Aman Ullah relative to Zejun Sun China Zejun Sun's profile →
Citations per field
00.5×3.0×
Zejun Sun · 1×
Citations per year

Countries citing papers authored by Aman Ullah

Since Specialization
Citations

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

Fields of papers citing papers by Aman Ullah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Aman 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 Aman Ullah Line = papers co-authored together Aman Ullah links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2021106
2 202178
3 201935
4 202330
5 202125
6 202425
7 202225
8 202225
9 202324
10 202222
11 202220
12 202220
13 202019
14 202219
15 202414
16 202213
17 202512
18 201912
19 202310
20 202310

About Aman Ullah

Aman Ullah is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence, Computer Networks and Communications, Information Systems and Experimental and Cognitive Psychology, having authored 28 papers that have together received 583 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (17 papers), Opinion Dynamics and Social Influence (17 papers), Advanced Graph Neural Networks (8 papers), Network Security and Intrusion Detection (4 papers), Recommender Systems and Techniques (3 papers), Software Engineering Research (2 papers), Mental Health Research Topics (2 papers) and Software Reliability and Analysis Research (2 papers). The work is most often cited by research in Statistical and Nonlinear Physics (355 citations), Artificial Intelligence (184 citations), Experimental and Cognitive Psychology (65 citations), Computer Networks and Communications (110 citations) and Information Systems (100 citations). Aman Ullah has collaborated with scholars based in China, Pakistan and Türkiye. Frequent co-authors include Nasrullah Khan, Jinfang Sheng, Bin Wang, Zejun Sun, Jun Long, Zongmin Ma, Kemal Polat, Rajesh Kumar, Salah Ud Din and Qinli Yang. Their work appears in journals such as Expert Systems with Applications, Applied Intelligence, Social Network Analysis and Mining, Information Processing & Management and IEEE Transactions on Industrial Informatics.

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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