Anurag Daram
Impact in
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- Domain Adaptation and Few-Shot Learning
- Machine Learning and ELM
- Neural Networks and Applications
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- Neural dynamics and brain function
Papers in
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- Domain Adaptation and Few-Shot Learning 5
- Machine Learning and ELM 3
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- Advanced Memory and Neural Computing 3
- Ferroelectric and Negative Capacitance Devices 1
- Co-authors
- Dhireesha Kudithipudi (6 shared papers)Ángel Yanguas-Gil (4 shared papers)Jeffrey W. Elam (1 shared paper)William Severa (1 shared paper)Nicholas Soures (1 shared paper)Benjamin R. Epstein (1 shared paper)Anil U. Mane (1 shared paper)Matthew Mattina (1 shared paper)
- Journals
- Nature Electronics (1 paper)Frontiers in Neuroscience (1 paper)OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (1 paper)
- Partner nations
- United StatesGermanyItaly
In The Last Decade
Anurag Daram
6 papers receiving 29 citations
Peers
Comparison fields: 5 of 21
- Artificial Intelligence 18
- Cognitive Neuroscience 7
- Neurology 2
- Cellular and Molecular Neuroscience 4
- Electrical and Electronic Engineering 12
Countries citing papers authored by Anurag Daram
This map shows the geographic impact of Anurag Daram'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 Anurag Daram with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anurag Daram more than expected).
Fields of papers citing papers by Anurag Daram
This network shows the impact of papers produced by Anurag Daram. 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 Anurag Daram. The network helps show where Anurag Daram may publish in the future.
Co-authors
The 12 scholars most cited alongside Anurag Daram, 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 | 2023 | 9 | |
| 2 | 2021 | 6 | |
| 3 | 2019 | 5 | |
| 4 | 2019 | 4 | |
| 5 | 2023 | 3 | |
| 6 | 2020 | 2 |
About Anurag Daram
Anurag Daram is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Cellular and Molecular Neuroscience and Cognitive Neuroscience, having authored 6 papers that have together received 29 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (5 papers), Machine Learning and ELM (3 papers), Advanced Memory and Neural Computing (3 papers), Multimodal Machine Learning Applications (2 papers), Ferroelectric and Negative Capacitance Devices (1 paper), Neuroscience and Neural Engineering (1 paper), Brain Tumor Detection and Classification (1 paper) and Neural dynamics and brain function (1 paper). The work is most often cited by research in Artificial Intelligence (18 citations), Cognitive Neuroscience (7 citations), Neurology (2 citations), Cellular and Molecular Neuroscience (4 citations) and Electrical and Electronic Engineering (12 citations). Anurag Daram has collaborated with scholars based in United States, Germany and Italy. Frequent co-authors include Dhireesha Kudithipudi, Ángel Yanguas-Gil, Jeffrey W. Elam, William Severa, Nicholas Soures, Benjamin R. Epstein, Anil U. Mane, Matthew Mattina, James B. Aimone and Emre Neftci. Their work appears in journals such as Nature Electronics, Frontiers in Neuroscience and OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information).
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.