Mohana Kunasekaran

704 citations
52 papers · 421 indexed · 1 hit paper · h-index 12

Mohana Kunasekaran

44 papers receiving 394 citations

Hit Papers

Artificial intelligence in public health: the potential o...642023202620242025204060

Peers

Mohana Kunasekaran
Comparison fields: 5 of 103
  • Modeling and Simulation 91
  • Virology 79
  • Health Informatics 18
  • Infectious Diseases 118
  • Health 48
Replace Wei Xin Khong with:
Wei Xin Khong Singapore
Charisma Y. Atkins United States
Saira Khowaja Pakistan
Emery Manirambona Rwanda
Denise Arakaki-Sánchez Brazil
Cari van Schalkwyk South Africa
Stéphanie Haïm‐Boukobza France
SagarC Galwankar United States
Aziz Mert Ipekci Switzerland
Mohana Kunasekaran relative to Wei Xin Khong Singapore Wei Xin Khong's profile →
Citations per field
00.5×6.5×
Wei Xin Khong · 1×
Citations per year

Countries citing papers authored by Mohana Kunasekaran

Since Specialization
Citations

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

Fields of papers citing papers by Mohana Kunasekaran

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20250
3 20241
4 202425
5 202429
6 20230
7 20232
8 20233
9
Artificial intelligence in public health: the potential of epidemic early warning systemsbreakdown →
202364
10 202310
11 20233
12 20220
13 202221
14 20223
15 20222
16 20202
17 201920
18 201916
19 20181
20 201813

About Mohana Kunasekaran

Mohana Kunasekaran is a scholar working on Modeling and Simulation, Virology and Infectious Diseases, having authored 52 papers that have together received 421 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (14 papers), Influenza Virus Research Studies (10 papers), Bacillus and Francisella bacterial research (10 papers), Poxvirus research and outbreaks (10 papers), Infection Control and Ventilation (9 papers), Viral Infections and Outbreaks Research (8 papers), Vaccine Coverage and Hesitancy (6 papers) and SARS-CoV-2 and COVID-19 Research (5 papers). The work is most often cited by research in Modeling and Simulation (91 citations), Virology (79 citations) and Health Informatics (18 citations). Mohana Kunasekaran has collaborated with scholars based in Australia, United States and United Kingdom. Frequent co-authors include C. Raina MacIntyre, Abrar Ahmad Chughtai, Valentina Costantino, Xin Chen, Ashley Quigley, David Heslop, Aye Moa, William D. Rawlinson, Holly Seale and Christopher J. Poulos. Their work appears in journals such as Vaccine, Human Vaccines & Immunotherapeutics, Public Health, Western Pacific surveillance response journal and Ageing Research Reviews.

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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