Deepti Mehrotra

1.8k citations
130 papers · 1.1k indexed · h-index 16
Topics
IoT and Edge/Fog Computing (15 papers)Software Engineering Research (11 papers)Online Learning and Analytics (10 papers)
Journals
SHILAP Revista de lepidopterologíaApplied Soft ComputingNeural Computing and Applications

In The Last Decade

Deepti Mehrotra

118 papers receiving 990 citations

Peers

Deepti Mehrotra
Comparison fields: 5 of 138
  • Artificial Intelligence 311
  • Information Systems 240
  • Computer Networks and Communications 152
  • Electrical and Electronic Engineering 145
  • Computer Vision and Pattern Recognition 112
Replace Jafreezal Jaafar with:
Jafreezal Jaafar Malaysia
Mazlina Abdul Majid Malaysia
Mutasem K. Alsmadi Saudi Arabia
Abdul Razak Hamdan Malaysia
Horst Samulowitz United States
Zalinda Othman Malaysia
Izzatdin Abdul Aziz Malaysia
Antoni Ligęza Poland
Lianyong Qi China
Deepti Mehrotra relative to Jafreezal Jaafar Malaysia Jafreezal Jaafar's profile →
Citations per field
00.5×1.5×
Jafreezal Jaafar · 1×
Citations per year

Countries citing papers authored by Deepti Mehrotra

Since Specialization
Citations

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

Fields of papers citing papers by Deepti Mehrotra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Deepti Mehrotra

This figure shows the co-authorship network connecting the top 25 collaborators of Deepti Mehrotra. A scholar is included among the top collaborators of Deepti Mehrotra 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 Deepti Mehrotra. Deepti Mehrotra 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 2
2 0
3 4
4 2
5 2
6 2
7 0
8 2
9 0
10 18
11 5
12 21
13 2
14 17
15
Knowledge Enriched Learning by Converging Knowledge Object & Learning Object
7
16 31
17 3
18 4
19
Improving Network Reliability and QOS in EOIPThrough Application Layer Signaling Protocol(RTP)
1
20 2

About Deepti Mehrotra

Deepti Mehrotra is a scholar working on Computer Science Applications, Software and Information Systems, having authored 130 papers that have together received 1.1k indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (15 papers), Software Engineering Research (11 papers) and Online Learning and Analytics (10 papers). The work is most often cited by research in Computer Science Applications (109 citations), Information Systems (240 citations) and Artificial Intelligence (311 citations). Deepti Mehrotra has collaborated with scholars based in India, United Arab Emirates and United Kingdom. Frequent co-authors include Hari Mohan Pandey, Ankit Chaudhary, A. Sai Sabitha, Renuka Nagpal, Abhay Bansal, Gautam Srivastava, Richa Gupta, Rajesh Kumar Tyagi, Pradeep Kumar Bhatia and Arun Sharma. Their work appears in journals such as SHILAP Revista de lepidopterología, Applied Soft Computing and Neural Computing and Applications.

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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