Arif Ullah

416 citations
19 papers · 209 · h-index 8

Impact in

Papers in

Arif Ullah

15 papers receiving 205 citations

Peers

Arif Ullah
Comparison fields: 5 of 49
  • Atomic and Molecular Physics, and Optics 120
  • Computational Theory and Mathematics 31
  • Physical and Theoretical Chemistry 16
  • Materials Chemistry 82
  • Statistical and Nonlinear Physics 20
Replace Xinzijian Liu with:
Xinzijian Liu China
Junjie Yang United States
Olivier Adjoua France
George Boxer United States
Tong Jiang China
Jeffrey B. Schriber United States
Jakub Rydzewski Poland
Manas Sajjan United States
Kade Head-Marsden United States
Katharine W. Moore United States
Arif Ullah relative to Xinzijian Liu China Xinzijian Liu's profile →
Citations per field
00.5×1.5×
Xinzijian Liu · 1×
Citations per year

Countries citing papers authored by Arif Ullah

Since Specialization
Citations

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

Fields of papers citing papers by Arif Ullah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

19 of 19 papers shown
#Work
1 202435
2 202235
3 202129
4 202219
5 202018
6 202417
7 202416
8 202410
9 20236
10 20236
11 20186
12 20235
13 20245
14 20241
15 20241
16 20250
17 20250
18 20240
19 20170

About Arif Ullah

Arif Ullah is a scholar working on Atomic and Molecular Physics, and Optics, Artificial Intelligence, Materials Chemistry, Molecular Biology and Statistical and Nonlinear Physics, having authored 19 papers that have together received 209 indexed citations. Recurring topics across this work include Spectroscopy and Quantum Chemical Studies (8 papers), Quantum, superfluid, helium dynamics (7 papers), Machine Learning in Materials Science (3 papers), Quantum many-body systems (3 papers), Advanced Chemical Physics Studies (2 papers), Computational Drug Discovery Methods (2 papers), Climate variability and models (2 papers) and Quantum Information and Cryptography (2 papers). The work is most often cited by research in Atomic and Molecular Physics, and Optics (120 citations), Computational Theory and Mathematics (31 citations), Physical and Theoretical Chemistry (16 citations), Materials Chemistry (82 citations) and Statistical and Nonlinear Physics (20 citations). Arif Ullah has collaborated with scholars based in China, United States and Pakistan. Frequent co-authors include Pavlo O. Dral, Alexei A. Kananenka, Xiao Zheng, YiJing Yan, Fuchun Ge, Maxim F. Gelin, Vladimir Chernyak, Lina Zhang, Yun‐An Yan and Yuming Su. Their work appears in journals such as Machine Learning Science and Technology, The Journal of Chemical Physics, The Journal of Physical Chemistry Letters, Computer Physics Communications and Nature Communications.

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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