Yajnaseni Dash

522 citations
36 papers · 305 indexed · h-index 7
Topics
Hydrological Forecasting Using AI (8 papers)Energy Load and Power Forecasting (5 papers)Machine Learning and ELM (4 papers)
Journals
SHILAP Revista de lepidopterologíaIEEE AccessEpilepsia
Partner nations
IndiaMalaysiaGermany

In The Last Decade

Yajnaseni Dash

27 papers receiving 294 citations

Peers

Yajnaseni Dash
Comparison fields: 5 of 61
  • Electrical and Electronic Engineering 122
  • Environmental Engineering 98
  • Control and Systems Engineering 78
  • Computer Networks and Communications 53
  • Artificial Intelligence 51
Replace M. Pushpalatha with:
M. Pushpalatha India
Juan López Spain
Qingquan Lv China
Deepak Sharma India
Chen Zeng China
Rajeev Ranjan India
Manoj Nambiar India
William B. Yates United Kingdom
S. Santhosh Baboo India
Yajnaseni Dash relative to M. Pushpalatha India M. Pushpalatha's profile →
Citations per field
00.5×7.1×
M. Pushpalatha · 1×
Citations per year

Countries citing papers authored by Yajnaseni Dash

Since Specialization
Citations

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

Fields of papers citing papers by Yajnaseni Dash

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yajnaseni Dash

This figure shows the co-authorship network connecting the top 25 collaborators of Yajnaseni Dash. A scholar is included among the top collaborators of Yajnaseni Dash 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 Yajnaseni Dash. Yajnaseni Dash 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 0
2 0
3 0
4 1
5 3
6 0
7 0
8 1
9 3
10 1
11 0
12 5
13 4
14 3
15 2
16 88
17 31
18 2
19
A Survey on Serial and Parallel Optimization Techniques Applicable for Matrix Multiplication Algorithm
3
20 70

About Yajnaseni Dash

Yajnaseni Dash is a scholar working on Environmental Engineering, Hardware and Architecture and Computer Networks and Communications, having authored 36 papers that have together received 305 indexed citations. Recurring topics across this work include Hydrological Forecasting Using AI (8 papers), Energy Load and Power Forecasting (5 papers) and Machine Learning and ELM (4 papers). The work is most often cited by research in Environmental Engineering (98 citations), Software (14 citations) and Control and Systems Engineering (78 citations). Yajnaseni Dash has collaborated with scholars based in India, Malaysia and Germany. Frequent co-authors include Bijaya Ketan Panigrahi, Saroj K. Mishra, Anamika Yadav, Sandeep Sahany, Ajay Rana, Sanjay Kumar Dubey, Naween Kumar, Ajith Abraham, Ajith Abraham and Sanjay Kumar. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access and Epilepsia.

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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