Sunil Pranit Lal

1.2k citations
39 papers · 831 indexed · h-index 16
Topics
Machine Learning in Bioinformatics (10 papers)RNA and protein synthesis mechanisms (7 papers)EEG and Brain-Computer Interfaces (6 papers)
Partner nations
FijiNew ZealandAustralia

In The Last Decade

Sunil Pranit Lal

36 papers receiving 792 citations

Peers

Sunil Pranit Lal
Comparison fields: 5 of 97
  • Molecular Biology 320
  • Cognitive Neuroscience 197
  • Computer Networks and Communications 143
  • Information Systems 139
  • Artificial Intelligence 125
Replace Yixin Chen with:
Yixin Chen China
Supriya Supriya Australia
Hui Yan China
M. Cevdet İnce Türkiye
Luca Didaci Italy
Jiajun Lin China
Hyoung Joong Kim South Korea
Fengzhen Tang China
Vivek Nigam United States
Eirina Bourtsoulatze United Kingdom
Sunil Pranit Lal relative to Yixin Chen China Yixin Chen's profile →
Citations per field
00.5×6.2×
Yixin Chen · 1×
Citations per year

Countries citing papers authored by Sunil Pranit Lal

Since Specialization
Citations

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

Fields of papers citing papers by Sunil Pranit Lal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sunil Pranit Lal. 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 Sunil Pranit Lal. The network helps show where Sunil Pranit Lal may publish in the future.

Co-authorship network of co-authors of Sunil Pranit Lal

This figure shows the co-authorship network connecting the top 25 collaborators of Sunil Pranit Lal. A scholar is included among the top collaborators of Sunil Pranit Lal 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 Sunil Pranit Lal. Sunil Pranit Lal is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 107
2 0
3 34
4 48
5 53
6 52
7 0
8 63
9 6
10 27
11 21
12 22
13 12
14 3
15 21
16 12
17 35
18 2
19
Access schemes based on perfect critical set partitions and transformations
2
20 4

About Sunil Pranit Lal

Sunil Pranit Lal is a scholar working on Signal Processing, Computer Science Applications and Computer Networks and Communications, having authored 39 papers that have together received 831 indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (10 papers), RNA and protein synthesis mechanisms (7 papers) and EEG and Brain-Computer Interfaces (6 papers). The work is most often cited by research in Cognitive Neuroscience (197 citations), Signal Processing (87 citations) and Human-Computer Interaction (41 citations). Sunil Pranit Lal has collaborated with scholars based in Fiji, New Zealand and Australia. Frequent co-authors include Amit K. Awasthi, Alok Sharma, Amardeep Singh, Hans W. Guesgen, Abdollah Dehzangi, Tatsuhiko Tsunoda, Abdul Sattar, Yosvany López, Ghazaleh Taherzadeh and Jacob J. Michaelson. Their work appears in journals such as PLoS ONE, Analytical Biochemistry and IEEE Access.

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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