Utkarsh Singhal

2.1k total citations · 1 hit paper
9 papers, 560 citations indexed

About

Utkarsh Singhal is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering and Biomedical Engineering. According to data from OpenAlex, Utkarsh Singhal has authored 9 papers receiving a total of 560 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Artificial Intelligence, 2 papers in Electrical and Electronic Engineering and 2 papers in Biomedical Engineering. Recurrent topics in Utkarsh Singhal's work include Electrical and Bioimpedance Tomography (2 papers), Remote-Sensing Image Classification (1 paper) and Wireless Body Area Networks (1 paper). Utkarsh Singhal is often cited by papers focused on Electrical and Bioimpedance Tomography (2 papers), Remote-Sensing Image Classification (1 paper) and Wireless Body Area Networks (1 paper). Utkarsh Singhal collaborates with scholars based in United States and India. Utkarsh Singhal's co-authors include Michel M. Maharbiz, Elad Alon, Dongjin Seo, Konlin Shen, Ryan Neely, Jose M. Carmena, Jan M. Rabaey, Bernhard E. Boser, Hao-Yen Tang and J. M. Tsai and has published in prestigious journals such as Neuron, IEEE Transactions on Biomedical Circuits and Systems and Mineral Economics.

In The Last Decade

Utkarsh Singhal

9 papers receiving 542 citations

Hit Papers

Wireless Recording in the Peripheral Nervous System with ... 2016 2026 2019 2022 2016 100 200 300

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Utkarsh Singhal United States 5 307 243 238 95 52 9 560
Hoc Khiem Trieu Germany 15 291 0.9× 433 1.8× 254 1.1× 66 0.7× 29 0.6× 51 755
Seong‐Kwan Hong South Korea 16 298 1.0× 662 2.7× 77 0.3× 51 0.5× 24 0.5× 69 770
Véronique Rochus Belgium 14 416 1.4× 619 2.5× 260 1.1× 179 1.9× 99 1.9× 113 1.0k
Yueming Gao China 14 381 1.2× 251 1.0× 56 0.2× 74 0.8× 15 0.3× 97 697
Dean A. Scribner United States 14 77 0.3× 399 1.6× 366 1.5× 156 1.6× 21 0.4× 37 780
Jia Hao Cheong Singapore 15 441 1.4× 754 3.1× 139 0.6× 43 0.5× 35 0.7× 38 954
Hyoungho Ko South Korea 16 590 1.9× 595 2.4× 119 0.5× 66 0.7× 9 0.2× 139 894
Enrique Mario Spinelli Argentina 16 606 2.0× 300 1.2× 227 1.0× 183 1.9× 14 0.3× 66 910
Hong‐Zhang Wang China 9 281 0.9× 80 0.3× 162 0.7× 50 0.5× 24 0.5× 40 507
Jiawei Xu China 21 1.0k 3.3× 791 3.3× 540 2.3× 383 4.0× 43 0.8× 112 1.6k

Countries citing papers authored by Utkarsh Singhal

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Utkarsh Singhal

This figure shows the co-authorship network connecting the top 25 collaborators of Utkarsh Singhal. A scholar is included among the top collaborators of Utkarsh Singhal based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Utkarsh Singhal. Utkarsh Singhal is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Singhal, Utkarsh, Carlos Esteves, Ameesh Makadia, & Stella X. Yu. (2023). Learning to Transform for Generalizable Instance-wise Invariance. 6188–6198. 1 indexed citations
2.
Singhal, Utkarsh, et al.. (2022). Do efficient commodity markets co-move: evidence from Indian base metals market. Mineral Economics. 36(3). 413–425. 3 indexed citations
3.
Singhal, Utkarsh & Stella X. Yu. (2022). Complex-valued Butterfly Transform for Efficient Hyperspectral Image Processing. 2022 International Joint Conference on Neural Networks (IJCNN). 501. 1–8. 1 indexed citations
4.
Singhal, Utkarsh, et al.. (2022). Co-domain Symmetry for Complex-Valued Deep Learning. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 671–680. 5 indexed citations
5.
Singhal, Utkarsh, et al.. (2022). Analysis and Development of E-Commerce Web Application. 65–72. 3 indexed citations
6.
Tancik, Matthew, Pratul P. Srinivasan, Ben Mildenhall, et al.. (2020). Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains. Neural Information Processing Systems. 33. 7537–7547. 36 indexed citations
7.
Seo, Dongjin, Ryan Neely, Konlin Shen, et al.. (2016). Wireless Recording in the Peripheral Nervous System with Ultrasonic Neural Dust. Neuron. 91(3). 529–539. 397 indexed citations breakdown →
8.
Tang, Hao-Yen, Dongjin Seo, Utkarsh Singhal, et al.. (2016). Miniaturizing Ultrasonic System for Portable Health Care and Fitness. IEEE Transactions on Biomedical Circuits and Systems. 9(6). 1–1. 37 indexed citations
9.
Tang, Hao-Yen, Yipeng Lu, Xiaoyue Jiang, et al.. (2016). 11.2 3D ultrasonic fingerprint sensor-on-a-chip. 202–203. 77 indexed citations

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.

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