Sumana Devata
- Hematology top 5%
-
- Lymphoma Diagnosis and Treatment 25
- Oncology top 10%
- CAR-T cell therapy research 15
- Immunology top 10%
- Immune Cell Function and Interaction 5
- Biosimilars and Bioanalytical Methods 4
- Dermatology top 5%
- Cutaneous lymphoproliferative disorders research 7
-
- Chronic Lymphocytic Leukemia Research 10
-
- Monoclonal and Polyclonal Antibodies Research 7
-
- CNS Lymphoma Diagnosis and Treatment 5
- Co-authors
- Ryan A. WilcoxTycel PhillipsMark KaminskiSuman L. SoodPhilip S. BoonstraRashmi ChughErica CampagnaroAsra Ahmed
- Partner nations
- United StatesSouth KoreaUnited Kingdom
In The Last Decade
Sumana Devata
49 papers receiving 769 citations
Peers
Comparison fields: 5 of 70
- Hematology 175
- Pathology and Forensic Medicine 279
- Oncology 347
- Immunology 267
- Dermatology 87
Countries citing papers authored by Sumana Devata
This map shows the geographic impact of Sumana Devata'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 Sumana Devata with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sumana Devata more than expected).
Fields of papers citing papers by Sumana Devata
This network shows the impact of papers produced by Sumana Devata. 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 Sumana Devata. The network helps show where Sumana Devata may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Sumana Devata, 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 | 2024 | 4 | |
| 2 | 2024 | 0 | |
| 3 | 2024 | 9 | |
| 4 | 2023 | 1 | |
| 5 | 2023 | 1 | |
| 6 | 2020 | 55 | |
| 7 | 2020 | 107 | |
| 8 | 2020 | 16 | |
| 9 | 2019 | 191 | |
| 10 | 2018 | 8 | |
| 11 | 2017 | 2 | |
| 12 | 2017 | 2 | |
| 13 | 2016 | 17 | |
| 14 | 2016 | 8 | |
| 15 | 2015 | 15 | |
| 16 | 2013 | 30 | |
| 17 | 2012 | 14 | |
| 18 | 2010 | 19 | |
| 19 | 2010 | 1 | |
| 20 | 2007 | 29 |
About Sumana Devata
Sumana Devata is a scholar working on Pathology and Forensic Medicine, Genetics, Oncology, Dermatology and Hematology, having authored 52 papers that have together received 778 indexed citations. Recurring topics across this work include Lymphoma Diagnosis and Treatment (25 papers), CAR-T cell therapy research (15 papers), Chronic Lymphocytic Leukemia Research (10 papers), Cutaneous lymphoproliferative disorders research (7 papers), Monoclonal and Polyclonal Antibodies Research (7 papers), CNS Lymphoma Diagnosis and Treatment (5 papers), Immune Cell Function and Interaction (5 papers) and Biosimilars and Bioanalytical Methods (4 papers). The work is most often cited by research in Hematology (175 citations), Pathology and Forensic Medicine (279 citations), Oncology (347 citations), Immunology (267 citations) and Dermatology (87 citations). Sumana Devata has collaborated with scholars based in United States, South Korea and United Kingdom. Frequent co-authors include Ryan A. Wilcox, Tycel Phillips, Mark Kaminski, Suman L. Sood, Philip S. Boonstra, Rashmi Chugh, Erica Campagnaro, Asra Ahmed, Moshe Talpaz and Scott D. Gitlin. Their work appears in journals such as Blood, Journal of Clinical Oncology, Hematological Oncology, Journal of Visualized Experiments and HemaSphere.
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.