Utkarsh Singhal
Impact in
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- Neuroscience and Neural Engineering
- Photoreceptor and optogenetics research
- Biomedical Engineering top 10%
- Advanced Sensor and Energy Harvesting Materials
- Wireless Body Area Networks
Papers in ⓘ
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- Neural Networks and Applications 1
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- Electrical and Bioimpedance Tomography 2
- Co-authors
- Michel M. Maharbiz (2 shared papers)Dongjin Seo (2 shared papers)Elad Alon (2 shared papers)Konlin Shen (1 shared paper)Jose M. Carmena (1 shared paper)Ryan Neely (1 shared paper)Jan M. Rabaey (1 shared paper)Bernhard E. Boser (2 shared papers)
- Journals
- Neuron (1 paper)IEEE Transactions on Biomedical Circuits and Systems (1 paper)Mineral Economics (1 paper)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)2022 International Joint Conference on Neural Networks (IJCNN) (1 paper)
- Partner nations
- United StatesIndia
In The Last Decade
Utkarsh Singhal
9 papers receiving 542 citations
Hit Papers
Peers
Comparison fields: 5 of 72
- Cellular and Molecular Neuroscience 238
- Biomedical Engineering 307
- Computer Graphics and Computer-Aided Design 18
- Cognitive Neuroscience 95
- Electrical and Electronic Engineering 243
Countries citing papers authored by Utkarsh Singhal
This map shows the geographic impact of Utkarsh Singhal'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 Utkarsh Singhal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Utkarsh Singhal more than expected).
Fields of papers citing papers by Utkarsh Singhal
This network shows the impact of papers produced by Utkarsh Singhal. 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 Utkarsh Singhal. The network helps show where Utkarsh Singhal may publish in the future.
Co-authors
The 25 scholars most cited alongside Utkarsh Singhal, 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 | Wireless Recording in the Peripheral Nervous System with Ultrasonic Neural Dust Hit paper breakdown → | 2016 | 397 |
| 2 | 2016 | 77 | |
| 3 | 2016 | 37 | |
| 4 | Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains | 2020 | 36 |
| 5 | 2022 | 5 | |
| 6 | 2022 | 3 | |
| 7 | 2022 | 3 | |
| 8 | 2023 | 1 | |
| 9 | 2022 | 1 |
About Utkarsh Singhal
Utkarsh Singhal is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Biomedical Engineering, Cellular and Molecular Neuroscience and Sociology and Political Science, having authored 9 papers that have together received 560 indexed citations. Recurring topics across this work include Electrical and Bioimpedance Tomography (2 papers), Innovative Energy Harvesting Technologies (1 paper), Neuroscience and Neural Engineering (1 paper), Remote-Sensing Image Classification (1 paper), Cell Image Analysis Techniques (1 paper), Monetary Policy and Economic Impact (1 paper), Ultrasound Imaging and Elastography (1 paper) and Neural Networks and Applications (1 paper). The work is most often cited by research in Cellular and Molecular Neuroscience (238 citations), Biomedical Engineering (307 citations), Computer Graphics and Computer-Aided Design (18 citations), Cognitive Neuroscience (95 citations) and Electrical and Electronic Engineering (243 citations). Utkarsh Singhal has collaborated with scholars based in United States and India. Frequent co-authors include Michel M. Maharbiz, Dongjin Seo, Elad Alon, Konlin Shen, Jose M. Carmena, Ryan Neely, Jan M. Rabaey, Bernhard E. Boser, Hao-Yen Tang and Martin Lim. Their work appears in journals such as Neuron, IEEE Transactions on Biomedical Circuits and Systems, Mineral Economics, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and 2022 International Joint Conference on Neural Networks (IJCNN).
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.