Jay Satia
- Artificial Intelligence top 10%
- Management Science and Operations Research top 10%
- Pediatrics, Perinatology and Child Health
- General Health Professions
- Public Health, Environmental and Occupational Health
- Co-authors
- Roy E. LavePeter FajansMargarita DíazPeter E. HallRuth SimmonsJuan Dı́azChristopher EliasKavita Chauhan
- Topics
- Global Maternal and Child Health (10 papers)Reproductive Health and Contraception (2 papers)Demographic Trends and Gender Preferences (2 papers)
- Cited by
- Management Science and Operations ResearchGeneral Decision SciencesPediatrics, Perinatology and Child Health
- Partner nations
- United StatesIndiaMexico
In The Last Decade
Jay Satia
14 papers receiving 249 citations
Peers
Comparison fields: 5 of 74
- Artificial Intelligence 101
- Management Science and Operations Research 67
- Pediatrics, Perinatology and Child Health 66
- General Health Professions 44
- Public Health, Environmental and Occupational Health 38
Countries citing papers authored by Jay Satia
This map shows the geographic impact of Jay Satia'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 Jay Satia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jay Satia more than expected).
Fields of papers citing papers by Jay Satia
This network shows the impact of papers produced by Jay Satia. 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 Jay Satia. The network helps show where Jay Satia may publish in the future.
Co-authorship network of co-authors of Jay Satia
This figure shows the co-authorship network connecting the top 25 collaborators of Jay Satia. A scholar is included among the top collaborators of Jay Satia based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jay Satia. Jay Satia is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | Innovations in maternal health : case studies from India | 6 |
| 4 | Rural Health Innovation through Leadership Development and Organisational Effectiveness | 1 |
| 5 | 11 | |
| 6 | 4 | |
| 7 | 1 | |
| 8 | 10 | |
| 9 | 1 | |
| 10 | 57 | |
| 11 | Effective managerial practices in population programmes. Benchmarking for continuous improvements. | 1 |
| 12 | 1 | |
| 13 | 0 | |
| 14 | 1 | |
| 15 | 17 | |
| 16 | 0 | |
| 17 | 143 | |
| 18 | 31 |
About Jay Satia
Jay Satia is a scholar working on Pediatrics, Perinatology and Child Health, Gender Studies and Management Science and Operations Research, having authored 18 papers that have together received 288 indexed citations. Recurring topics across this work include Global Maternal and Child Health (10 papers), Reproductive Health and Contraception (2 papers) and Demographic Trends and Gender Preferences (2 papers). The work is most often cited by research in Management Science and Operations Research (67 citations), General Decision Sciences (8 citations) and Pediatrics, Perinatology and Child Health (66 citations). Jay Satia has collaborated with scholars based in United States, India and Mexico. Frequent co-authors include Roy E. Lave, Peter Fajans, Margarita Díaz, Peter E. Hall, Ruth Simmons, Juan Dı́az, Christopher Elias, Kavita Chauhan, Anant Kumar and Shireen Jejeebhoy. Their work appears in journals such as The Journal of Finance, Management Science and Operations Research.
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.