Ankit Agrawal
Impact in
- Metals and Alloys top 1%
- Hydrogen embrittlement and corrosion behaviors in metals
- Materials Chemistry top 0.5%
- Machine Learning in Materials Science
- X-ray Diffraction in Crystallography
- Electronic and Structural Properties of Oxides
Papers in
-
- Algorithms and Data Compression 12
- Co-authors
- Alok ChoudharyLogan WardWei‐keng LiaoChristopher WolvertonChris WolvertonKasthurirangan GopalakrishnanSiddhartha Kumar KhaitanDipendra Jha
- Journals
- Scientific Reports (10 papers)Integrating materials and manufacturing innovation (6 papers)Journal of the American College of Cardiology (6 papers)Microscopy and Microanalysis (5 papers)npj Computational Materials (4 papers)
- Partner nations
- United StatesIndiaPhilippines
In The Last Decade
Ankit Agrawal
233 papers receiving 9.3k citations
Hit Papers
Peers
Comparison fields: 5 of 205
- Metals and Alloys 345
- Materials Chemistry 4.7k
- Computational Theory and Mathematics 1.1k
- Structural Biology 69
- Mechanical Engineering 1.8k
Countries citing papers authored by Ankit Agrawal
This map shows the geographic impact of Ankit Agrawal'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 Ankit Agrawal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ankit Agrawal more than expected).
Fields of papers citing papers by Ankit Agrawal
This network shows the impact of papers produced by Ankit Agrawal. 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 Ankit Agrawal. The network helps show where Ankit Agrawal may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ankit Agrawal, 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 | 2024 | 5 | |
| 4 | 2024 | 5 | |
| 5 | 2024 | 0 | |
| 6 | 2024 | 44 | |
| 7 | 2024 | 5 | |
| 8 | 2023 | 0 | |
| 9 | 2023 | 6 | |
| 10 | 2023 | 12 | |
| 11 | Recent advances and applications of deep learning methods in materials science Hit paper breakdown → | 2022 | 652 |
| 12 | 2021 | 109 | |
| 13 | 2021 | 6 | |
| 14 | 2020 | 7 | |
| 15 | 2018 | 89 | |
| 16 | Accurate Models of Formation Enthalpy Created using Machine Learning and Voronoi Tessellations | 2016 | 1 |
| 17 | Object Recognition In HADOOP Using HIPI | 2015 | 1 |
| 18 | 2014 | 3 | |
| 19 | 2012 | 8 | |
| 20 | 2011 | 199 |
About Ankit Agrawal
Ankit Agrawal is a scholar working on Metals and Alloys, Artificial Intelligence, Structural Biology, Hardware and Architecture and Statistical and Nonlinear Physics, having authored 257 papers that have together received 9.6k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (53 papers), X-ray Diffraction in Crystallography (24 papers), Genomics and Phylogenetic Studies (18 papers), Complex Network Analysis Techniques (17 papers), Machine Learning in Bioinformatics (14 papers), Data Mining Algorithms and Applications (12 papers), Algorithms and Data Compression (12 papers) and Advanced Data Storage Technologies (12 papers). The work is most often cited by research in Metals and Alloys (345 citations), Materials Chemistry (4.7k citations), Computational Theory and Mathematics (1.1k citations), Structural Biology (69 citations) and Mechanical Engineering (1.8k citations). Ankit Agrawal has collaborated with scholars based in United States, India and Philippines. Frequent co-authors include Alok Choudhary, Logan Ward, Wei‐keng Liao, Christopher Wolverton, Chris Wolverton, Kasthurirangan Gopalakrishnan, Siddhartha Kumar Khaitan, Dipendra Jha, Surya R. Kalidindi and Zijiang Yang. Their work appears in journals such as Scientific Reports, Integrating materials and manufacturing innovation, Journal of the American College of Cardiology, Microscopy and Microanalysis 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.