Shikhar Sharma
- Molecular Biology top 10%
- Artificial Intelligence top 10%
- Cancer Research
- Genetics
- Oncology
- Co-authors
- Peter A. JonesGangning LiangDaniel D. De CarvalhoAllen S. YangShinwu JeongTheresa K. KellyKimberly D. SiegmundErika M. Wolff
- Topics
- Epigenetics and DNA Methylation (8 papers)Natural Language Processing Techniques (6 papers)Topic Modeling (5 papers)
- Journals
- Molecular and Cellular BiologyCancer CellJournal of Pharmacology and Experimental Therapeutics
- Partner nations
- United StatesIndiaCanada
In The Last Decade
Shikhar Sharma
28 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 115
- Molecular Biology 811
- Artificial Intelligence 197
- Cancer Research 142
- Genetics 123
- Oncology 84
Countries citing papers authored by Shikhar Sharma
This map shows the geographic impact of Shikhar Sharma'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 Shikhar Sharma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shikhar Sharma more than expected).
Fields of papers citing papers by Shikhar Sharma
This network shows the impact of papers produced by Shikhar Sharma. 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 Shikhar Sharma. The network helps show where Shikhar Sharma may publish in the future.
Co-authorship network of co-authors of Shikhar Sharma
This figure shows the co-authorship network connecting the top 25 collaborators of Shikhar Sharma. A scholar is included among the top collaborators of Shikhar Sharma 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 Shikhar Sharma. Shikhar Sharma is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 28 | |
| 2 | 4 | |
| 3 | 16 | |
| 4 | 19 | |
| 5 | 16 | |
| 6 | 66 | |
| 7 | 26 | |
| 8 | 5 | |
| 9 | Dead-ends and Secure Exploration in Reinforcement Learning | 4 |
| 10 | From FiLM to Video: Multi-turn Question Answering with Multi-modal Context | 5 |
| 11 | Keep Drawing It: Iterative language-based image generation and editing. | 4 |
| 12 | Natural Language Generation in Dialogue using Lexicalized and Delexicalized Data | 3 |
| 13 | 113 | |
| 14 | Semantic Extraction of Named Entities From Bank Wire Text. | 1 |
| 15 | 54 | |
| 16 | 214 | |
| 17 | 18 | |
| 18 | 91 | |
| 19 | 220 | |
| 20 | 144 |
About Shikhar Sharma
Shikhar Sharma is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Medicine, having authored 28 papers that have together received 1.2k indexed citations. Recurring topics across this work include Epigenetics and DNA Methylation (8 papers), Natural Language Processing Techniques (6 papers) and Topic Modeling (5 papers). The work is most often cited by research in Molecular Biology (811 citations), Cancer Research (142 citations) and Artificial Intelligence (197 citations). Shikhar Sharma has collaborated with scholars based in United States, India and Canada. Frequent co-authors include Peter A. Jones, Gangning Liang, Daniel D. De Carvalho, Allen S. Yang, Shinwu Jeong, Theresa K. Kelly, Kimberly D. Siegmund, Erika M. Wolff, Xiaojing Yang and Sheng‐Fang Su. Their work appears in journals such as Molecular and Cellular Biology, Cancer Cell and Journal of Pharmacology and Experimental Therapeutics.
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.