Akhil Dodda
Impact in
- Hardware and Architecture top 5%
- Physical Unclonable Functions (PUFs) and Hardware Security
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- Advanced Memory and Neural Computing
- Ferroelectric and Negative Capacitance Devices
- Perovskite Materials and Applications
Papers in
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- Advanced Memory and Neural Computing 7
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- Neuroscience and Neural Engineering 4
- Co-authors
- Saptarshi Das (14 shared papers)Joan M. Redwing (4 shared papers)Shiva Subbulakshmi Radhakrishnan (4 shared papers)Nicholas Trainor (3 shared papers)Aaryan Oberoi (2 shared papers)Andrew Pannone (4 shared papers)Sarbashis Das (1 shared paper)Mauricio Terrones (4 shared papers)
- Journals
- ACS Nano (5 papers)Nature Communications (3 papers)Advanced Theory and Simulations (1 paper)Nature Materials (1 paper)Communications Physics (1 paper)
- Partner nations
- United StatesIndiaHong Kong
In The Last Decade
Akhil Dodda
14 papers receiving 910 citations
Peers
Comparison fields: 5 of 51
- Hardware and Architecture 181
- Electrical and Electronic Engineering 637
- Cellular and Molecular Neuroscience 186
- Materials Chemistry 356
- Acoustics and Ultrasonics 6
Countries citing papers authored by Akhil Dodda
This map shows the geographic impact of Akhil Dodda'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 Akhil Dodda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Akhil Dodda more than expected).
Fields of papers citing papers by Akhil Dodda
This network shows the impact of papers produced by Akhil Dodda. 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 Akhil Dodda. The network helps show where Akhil Dodda may publish in the future.
Co-authors
The 25 scholars most cited alongside Akhil Dodda, 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 | 2022 | 168 | |
| 2 | 2021 | 128 | |
| 3 | 2020 | 100 | |
| 4 | 2022 | 89 | |
| 5 | 2019 | 82 | |
| 6 | 2020 | 72 | |
| 7 | 2019 | 64 | |
| 8 | 2021 | 61 | |
| 9 | 2022 | 43 | |
| 10 | 2018 | 42 | |
| 11 | 2022 | 26 | |
| 12 | 2021 | 15 | |
| 13 | 2017 | 13 | |
| 14 | 2018 | 12 |
About Akhil Dodda
Akhil Dodda is a scholar working on Electrical and Electronic Engineering, Cellular and Molecular Neuroscience, Hardware and Architecture, Materials Chemistry and Statistical and Nonlinear Physics, having authored 14 papers that have together received 915 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (7 papers), Neuroscience and Neural Engineering (4 papers), 2D Materials and Applications (4 papers), Physical Unclonable Functions (PUFs) and Hardware Security (4 papers), Advanced Thermodynamics and Statistical Mechanics (2 papers), Neural dynamics and brain function (2 papers), Molecular Communication and Nanonetworks (2 papers) and MXene and MAX Phase Materials (2 papers). The work is most often cited by research in Hardware and Architecture (181 citations), Electrical and Electronic Engineering (637 citations), Cellular and Molecular Neuroscience (186 citations), Materials Chemistry (356 citations) and Acoustics and Ultrasonics (6 citations). Akhil Dodda has collaborated with scholars based in United States, India and Hong Kong. Frequent co-authors include Saptarshi Das, Joan M. Redwing, Shiva Subbulakshmi Radhakrishnan, Nicholas Trainor, Aaryan Oberoi, Andrew Pannone, Sarbashis Das, Mauricio Terrones, Amritanand Sebastian and Thomas F. Schranghamer. Their work appears in journals such as ACS Nano, Nature Communications, Advanced Theory and Simulations, Nature Materials and Communications Physics.
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.