Palash Ghosh
Impact in
- Modeling and Simulation top 10%
- COVID-19 epidemiological studies
-
- Pharmacovigilance and Adverse Drug Reactions
Papers in
-
- Statistical Methods in Clinical Trials 6
- Advanced Causal Inference Techniques 2
-
- SARS-CoV-2 and COVID-19 Research 2
- Co-authors
- Bibhas Chakraborty (7 shared papers)Anup Dewanji (3 shared papers)Hitendra Kumar Patel (1 shared paper)Ramesh V. Sonti (1 shared paper)Sujoy Ghosh (2 shared papers)Sibaji Gaj (1 shared paper)Juan C. Vivar (1 shared paper)Arijit Sur (1 shared paper)
- Journals
- Statistics in Medicine (2 papers)Biometrical Journal (1 paper)Pharmaceutical Statistics (1 paper)Annals of the Institute of Statistical Mathematics (1 paper)JMIR Public Health and Surveillance (1 paper)
- Partner nations
- IndiaSingaporeUnited States
In The Last Decade
Palash Ghosh
17 papers receiving 190 citations
Peers
Comparison fields: 5 of 84
- Modeling and Simulation 32
- Toxicology 17
- Statistics and Probability 21
- Rheumatology 19
- Complementary and alternative medicine 10
Countries citing papers authored by Palash Ghosh
This map shows the geographic impact of Palash Ghosh'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 Palash Ghosh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Palash Ghosh more than expected).
Fields of papers citing papers by Palash Ghosh
This network shows the impact of papers produced by Palash Ghosh. 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 Palash Ghosh. The network helps show where Palash Ghosh may publish in the future.
Co-authors
The 25 scholars most cited alongside Palash Ghosh, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 48 | |
| 2 | 2020 | 26 | |
| 3 | 2023 | 21 | |
| 4 | 2014 | 20 | |
| 5 | 2018 | 19 | |
| 6 | 2019 | 16 | |
| 7 | 2020 | 11 | |
| 8 | 2016 | 10 | |
| 9 | 2019 | 9 | |
| 10 | 2013 | 6 | |
| 11 | 2011 | 4 | |
| 12 | 2023 | 3 | |
| 13 | 2022 | 2 | |
| 14 | 2022 | 2 | |
| 15 | 2021 | 1 | |
| 16 | 2023 | 1 | |
| 17 | 2019 | 1 | |
| 18 | 2015 | 0 | |
| 19 | 2025 | 0 | |
| 20 | 2023 | 0 |
About Palash Ghosh
Palash Ghosh is a scholar working on Statistics and Probability, Infectious Diseases, Toxicology, Economics and Econometrics and Modeling and Simulation, having authored 20 papers that have together received 200 indexed citations. Recurring topics across this work include Statistical Methods in Clinical Trials (6 papers), Pharmacovigilance and Adverse Drug Reactions (3 papers), COVID-19 epidemiological studies (3 papers), Plant-Microbe Interactions and Immunity (2 papers), COVID-19 Pandemic Impacts (2 papers), Advanced Causal Inference Techniques (2 papers), SARS-CoV-2 and COVID-19 Research (2 papers) and Plant Pathogenic Bacteria Studies (2 papers). The work is most often cited by research in Modeling and Simulation (32 citations), Toxicology (17 citations), Statistics and Probability (21 citations), Rheumatology (19 citations) and Complementary and alternative medicine (10 citations). Palash Ghosh has collaborated with scholars based in India, Singapore and United States. Frequent co-authors include Bibhas Chakraborty, Anup Dewanji, Hitendra Kumar Patel, Ramesh V. Sonti, Sujoy Ghosh, Sibaji Gaj, Juan C. Vivar, Arijit Sur, Jeffrey Wilkins and Erica E. M. Moodie. Their work appears in journals such as Statistics in Medicine, Biometrical Journal, Pharmaceutical Statistics, Annals of the Institute of Statistical Mathematics and JMIR Public Health and Surveillance.
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.