Komal Pandya

24 papers receiving 318 citations

Komal Pandya's Hit Papers

A review on Quantum Approximate Optimization Algorithm and its variants 2024 · 147 citations
1470+1Years since publication4080120

Peers

Komal Pandya
Comparison fields: 5 of 91
  • Critical Care and Intensive Care Medicine 28
  • Internal Medicine 12
  • Anesthesiology and Pain Medicine 17
  • Artificial Intelligence 113
  • Developmental Neuroscience 10
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Xi Zhou China
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J. A. Blom Netherlands
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Ramesh C. Joshi India
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Countries citing papers authored by Komal Pandya

Since Specialization
Citations

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

Fields of papers citing papers by Komal Pandya

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A review on Quantum Approximate Optimization Algorithm and its variants
Hit paper breakdown →
2024147
2 202123
3 202016
4 201816
5 201615
6 201613
7 201013
8 201912
9 202110
10 20119
11 20059
12 20108
13 20237
14 20177
15 20195
16 20194
17 20213
18 20233
19
Mass lesion in an intravenous drug user. Round pneumonia.
19893
20 20231

About Komal Pandya

Komal Pandya is a scholar working on Critical Care and Intensive Care Medicine, Cardiology and Cardiovascular Medicine, Artificial Intelligence, Surgery and Biomedical Engineering, having authored 26 papers that have together received 328 indexed citations. Recurring topics across this work include Intensive Care Unit Cognitive Disorders (5 papers), Mechanical Circulatory Support Devices (4 papers), Quantum Computing Algorithms and Architecture (3 papers), Cardiac Arrest and Resuscitation (3 papers), Anesthesia and Sedative Agents (3 papers), Quantum Information and Cryptography (3 papers), Organizational and Employee Performance (2 papers) and Workplace Spirituality and Leadership (2 papers). The work is most often cited by research in Critical Care and Intensive Care Medicine (28 citations), Internal Medicine (12 citations), Anesthesiology and Pain Medicine (17 citations), Artificial Intelligence (113 citations) and Developmental Neuroscience (10 citations). Komal Pandya has collaborated with scholars based in United States, India and Italy. Frequent co-authors include Andrea Ceschini, Rui-Hao Li, Kostas Blekos, Alexander H. Flannery, Aric Schadler, Aaron M. Cook, Kyle A. Weant, Michael Sekela, Machelle Wilson and Jeremiah J. Duby. Their work appears in journals such as Annals of Pharmacotherapy, Seminars in Cardiothoracic and Vascular Anesthesia, Orthopedics, Physics Reports and Information Sciences.

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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