Utkarsh Singhal
Impact in
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- Neuroscience and Neural Engineering
- Biomedical Engineering top 10%
- Wireless Body Area Networks
- Advanced Sensor and Energy Harvesting Materials
- Analog and Mixed-Signal Circuit Design
Papers in
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- Neural Networks and Applications 2
- Stochastic Gradient Optimization Techniques 1
- Domain Adaptation and Few-Shot Learning 1
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- Advanced Neural Network Applications 2
- Co-authors
- E. Alon (2 shared papers)Michel M. Maharbiz (2 shared papers)Dongjin Seo (2 shared papers)Jan M. Rabaey (1 shared paper)Jose M. Carmena (1 shared paper)Ryan Neely (1 shared paper)Konlin Shen (1 shared paper)Bernhard E. Boser (2 shared papers)
- Journals
- IEEE Transactions on Biomedical Circuits and Systems (1 paper)Neuron (1 paper)neural information processing systems (1 paper)2022 International Joint Conference on Neural Networks (IJCNN) (1 paper)Digest of technical papers/Digest of technical papers - IEEE International Solid-State Circuits Conference (1 paper)
- Partner nations
- United States
In The Last Decade
Utkarsh Singhal
7 papers receiving 626 citations
Utkarsh Singhal's Hit Papers
Peers
Comparison fields: 5 of 59
- Cellular and Molecular Neuroscience 212
- Biomedical Engineering 234
- Signal Processing 36
- Computer Graphics and Computer-Aided Design 18
- Mechanics of Materials 76
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 | 448 |
| 2 | 2016 | 82 | |
| 3 | Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains | 2020 | 60 |
| 4 | 2016 | 39 | |
| 5 | 2022 | 7 | |
| 6 | 2022 | 1 | |
| 7 | 2023 | 1 |
About Utkarsh Singhal
Utkarsh Singhal is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Media Technology and Cellular and Molecular Neuroscience, having authored 7 papers that have together received 638 indexed citations. Recurring topics across this work include Neural Networks and Applications (2 papers), Advanced Neural Network Applications (2 papers), Stochastic Gradient Optimization Techniques (1 paper), Biometric Identification and Security (1 paper), Ultrasound Imaging and Elastography (1 paper), Domain Adaptation and Few-Shot Learning (1 paper), Analog and Mixed-Signal Circuit Design (1 paper) and Ultrasonics and Acoustic Wave Propagation (1 paper). The work is most often cited by research in Cellular and Molecular Neuroscience (212 citations), Biomedical Engineering (234 citations), Signal Processing (36 citations), Computer Graphics and Computer-Aided Design (18 citations) and Mechanics of Materials (76 citations). Utkarsh Singhal has collaborated with scholars based in United States. Frequent co-authors include E. Alon, Michel M. Maharbiz, Dongjin Seo, Jan M. Rabaey, Jose M. Carmena, Ryan Neely, Konlin Shen, Bernhard E. Boser, Hao-Yen Tang and Matthew Tancik. Their work appears in journals such as IEEE Transactions on Biomedical Circuits and Systems, Neuron, neural information processing systems, 2022 International Joint Conference on Neural Networks (IJCNN) and Digest of technical papers/Digest of technical papers - IEEE International Solid-State Circuits Conference.
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.