Prateek Singhal

647 citations
41 papers · 424 · h-index 13

Impact in

Papers in

Prateek Singhal

35 papers receiving 375 citations

Peers

Prateek Singhal
Comparison fields: 5 of 72
  • Health Informatics 6
  • Electrical and Electronic Engineering 210
  • Computer Vision and Pattern Recognition 79
  • Energy Engineering and Power Technology 11
  • Safety, Risk, Reliability and Quality 23
Replace Abhishek Javali with:
Abhishek Javali India
Siddhartha Bhattacharyya United States
Linyao Yang China
Bassem Ouni United Arab Emirates
Zhenhui Ye China
R.P. Klump United States
Abdullah Khalili Iran
Marjan Abdechiri Iran
Zhen Gao China
Gan Luo China
Prateek Singhal relative to Abhishek Javali India Abhishek Javali's profile →
Citations per field
00.5×2×3×4×4.6×
Abhishek Javali · 1×
Citations per year

Countries citing papers authored by Prateek Singhal

Since Specialization
Citations

This map shows the geographic impact of Prateek 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 Prateek Singhal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Prateek Singhal more than expected).

Fields of papers citing papers by Prateek Singhal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Prateek 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 Prateek Singhal. The network helps show where Prateek Singhal may publish in the future.

Co-authors

The 25 scholars most cited alongside Prateek Singhal, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Prateek Singhal Line = papers co-authored together Prateek Singhal links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201553
2 201146
3 201529
4 201127
5 201526
6 201425
7 202223
8 202121
9 201517
10 202214
11 202213
12 202013
13 201113
14 202212
15 20189
16 20229
17 20189
18 20158
19 20147
20 20246

About Prateek Singhal

Prateek Singhal is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Networks and Communications and Biomedical Engineering, having authored 41 papers that have together received 424 indexed citations. Recurring topics across this work include Optimal Power Flow Distribution (13 papers), Electric Power System Optimization (12 papers), Smart Grid Energy Management (6 papers), Energy Load and Power Forecasting (6 papers), Face recognition and analysis (4 papers), Multimodal Machine Learning Applications (2 papers), IoT and Edge/Fog Computing (2 papers) and Balance, Gait, and Falls Prevention (2 papers). The work is most often cited by research in Health Informatics (6 citations), Electrical and Electronic Engineering (210 citations), Computer Vision and Pattern Recognition (79 citations), Energy Engineering and Power Technology (11 citations) and Safety, Risk, Reliability and Quality (23 citations). Prateek Singhal has collaborated with scholars based in India, United States and Germany. Frequent co-authors include Veena Sharma, Ram Naresh, Prabhat Kumar Srivastava, Visesh Chari, N. Dinesh Reddy, Sarvesh Kumar, K. Madhava Krishna, Arvind Kumar Tiwari, D. K. Singh and Dinesh Goyal. Their work appears in journals such as IET Generation Transmission & Distribution, Semigroup Forum, Computational Intelligence and Neuroscience, Arabian Journal for Science and Engineering and ECS Transactions.

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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