Rishikesh Magar
Impact in
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- Computational Drug Discovery Methods
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- Machine Learning in Materials Science
- X-ray Diffraction in Crystallography
Papers in
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- Machine Learning in Materials Science 10
- X-ray Diffraction in Crystallography 3
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- Computational Drug Discovery Methods 8
- Co-authors
- Amir Barati Farimani (16 shared papers)Yuyang Wang (5 shared papers)Zhonglin Cao (1 shared paper)Lu Xu (1 shared paper)Ian D. Gates (2 shared papers)Mohammadreza Karamad (2 shared papers)Samira Siahrostami (2 shared papers)Yuting Shi (1 shared paper)
- Journals
- Journal of Chemical Information and Modeling (4 papers)Computers in Biology and Medicine (2 papers)SoftwareX (1 paper)Journal of the American Chemical Society (1 paper)npj Computational Materials (1 paper)
- Partner nations
- United StatesCanada
In The Last Decade
Rishikesh Magar
16 papers receiving 512 citations
Peers
Comparison fields: 5 of 98
- Computational Theory and Mathematics 141
- Materials Chemistry 310
- Metals and Alloys 16
- Modeling and Simulation 23
- Inorganic Chemistry 60
Countries citing papers authored by Rishikesh Magar
This map shows the geographic impact of Rishikesh Magar'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 Rishikesh Magar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rishikesh Magar more than expected).
Fields of papers citing papers by Rishikesh Magar
This network shows the impact of papers produced by Rishikesh Magar. 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 Rishikesh Magar. The network helps show where Rishikesh Magar may publish in the future.
Co-authors
The 15 scholars most cited alongside Rishikesh Magar, 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 | 112 | |
| 2 | 2023 | 98 | |
| 3 | 2022 | 65 | |
| 4 | 2022 | 50 | |
| 5 | 2022 | 48 | |
| 6 | 2021 | 34 | |
| 7 | 2022 | 25 | |
| 8 | 2024 | 25 | |
| 9 | 2021 | 20 | |
| 10 | 2023 | 14 | |
| 11 | 2020 | 11 | |
| 12 | 2024 | 9 | |
| 13 | 2024 | 5 | |
| 14 | 2025 | 3 | |
| 15 | 2021 | 3 | |
| 16 | AugLiChem: Data Augmentation Library ofChemical Structures for Machine Learning. | 2021 | 1 |
| 17 | 2023 | 0 |
About Rishikesh Magar
Rishikesh Magar is a scholar working on Materials Chemistry, Computational Theory and Mathematics, Artificial Intelligence, Molecular Biology and Radiology, Nuclear Medicine and Imaging, having authored 17 papers that have together received 523 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (10 papers), Computational Drug Discovery Methods (8 papers), X-ray Diffraction in Crystallography (3 papers), Metal-Organic Frameworks: Synthesis and Applications (2 papers), Anomaly Detection Techniques and Applications (2 papers), Protein Structure and Dynamics (2 papers), Advanced biosensing and bioanalysis techniques (1 paper) and Advanced Chemical Sensor Technologies (1 paper). The work is most often cited by research in Computational Theory and Mathematics (141 citations), Materials Chemistry (310 citations), Metals and Alloys (16 citations), Modeling and Simulation (23 citations) and Inorganic Chemistry (60 citations). Rishikesh Magar has collaborated with scholars based in United States and Canada. Frequent co-authors include Amir Barati Farimani, Yuyang Wang, Zhonglin Cao, Lu Xu, Ian D. Gates, Mohammadreza Karamad, Samira Siahrostami, Yuting Shi, Liang Chen and Peiyuan Li. Their work appears in journals such as Journal of Chemical Information and Modeling, Computers in Biology and Medicine, SoftwareX, Journal of the American Chemical Society and npj Computational Materials.
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.