Ramya Ramakrishnan
Impact in
-
- Cancer and Skin Lesions
Papers in
- Co-authors
- Julie ShahStefanos NikolaidisPrzemyslaw A. LasotaJohn F. KalinichDavid E. McClainN. RamakrishnanEric HorvitzDebadeepta Dey
- Journals
- Journal of Artificial Intelligence Research (2 papers)Blood (1 paper)Pediatric Blood & Cancer (1 paper)Frontiers in Immunology (1 paper)The International Journal of Robotics Research (1 paper)
- Partner nations
- United StatesIndiaUnited Kingdom
In The Last Decade
Ramya Ramakrishnan
29 papers receiving 290 citations
Peers
Comparison fields: 5 of 111
- Human-Computer Interaction 17
- Dermatology 25
- Social Psychology 47
- Pathology and Forensic Medicine 34
- Artificial Intelligence 54
Countries citing papers authored by Ramya Ramakrishnan
This map shows the geographic impact of Ramya Ramakrishnan'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 Ramya Ramakrishnan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ramya Ramakrishnan more than expected).
Fields of papers citing papers by Ramya Ramakrishnan
This network shows the impact of papers produced by Ramya Ramakrishnan. 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 Ramya Ramakrishnan. The network helps show where Ramya Ramakrishnan may publish in the future.
Co-authors
The 25 scholars most cited alongside Ramya Ramakrishnan, 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 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 1 | |
| 5 | 2023 | 0 | |
| 6 | 2020 | 16 | |
| 7 | 2020 | 7 | |
| 8 | 2020 | 1 | |
| 9 | 2019 | 1 | |
| 10 | 2019 | 12 | |
| 11 | 2018 | 46 | |
| 12 | 2018 | 1 | |
| 13 | 2017 | 7 | |
| 14 | Towards Interpretable Explanations for Transfer Learning in Sequential Tasks | 2016 | 5 |
| 15 | 2012 | 8 | |
| 16 | 2012 | 2 | |
| 17 | 2011 | 12 | |
| 18 | Plumbagin-induced apoptosis in lymphocytes is mediated through increased reactive oxigen species production and activation of the caspase cascade | 2007 | 2 |
| 19 | An Expertise Recommender Using Web Mining | 2001 | 6 |
| 20 | 2000 | 28 |
About Ramya Ramakrishnan
Ramya Ramakrishnan is a scholar working on Human-Computer Interaction, Toxicology, Pathology and Forensic Medicine, Obstetrics and Gynecology and Dermatology, having authored 36 papers that have together received 302 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (5 papers), Breast Lesions and Carcinomas (3 papers), Chronic Lymphocytic Leukemia Research (2 papers), Machine Learning and Algorithms (2 papers), Topic Modeling (2 papers), Adipokines, Inflammation, and Metabolic Diseases (2 papers), Acute Myeloid Leukemia Research (2 papers) and Cancer and Skin Lesions (2 papers). The work is most often cited by research in Human-Computer Interaction (17 citations), Dermatology (25 citations), Social Psychology (47 citations), Pathology and Forensic Medicine (34 citations) and Artificial Intelligence (54 citations). Ramya Ramakrishnan has collaborated with scholars based in United States, India and United Kingdom. Frequent co-authors include Julie Shah, Stefanos Nikolaidis, Przemyslaw A. Lasota, John F. Kalinich, David E. McClain, N. Ramakrishnan, Eric Horvitz, Debadeepta Dey, Ece Kamar and Victoria Interrante. Their work appears in journals such as Journal of Artificial Intelligence Research, Blood, Pediatric Blood & Cancer, Frontiers in Immunology and The International Journal of Robotics 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.