Lokesh Jain

529 citations
18 papers · 338 indexed · h-index 10
Topics
Complex Network Analysis Techniques (10 papers)Opinion Dynamics and Social Influence (8 papers)Spam and Phishing Detection (3 papers)
Partner nations
IndiaAustraliaBulgaria

In The Last Decade

Lokesh Jain

16 papers receiving 319 citations

Peers

Lokesh Jain
Comparison fields: 5 of 76
  • Artificial Intelligence 144
  • Statistical and Nonlinear Physics 137
  • Sociology and Political Science 69
  • Information Systems 53
  • Computer Networks and Communications 32
Replace Enrico Corradini with:
Enrico Corradini Italy
Dónal Doyle Ireland
Zekai J. Gao United States
Edward Benson United States
Giovanni Comarela Brazil
Amitabha Bagchi India
Marcelo G. Armentano Argentina
Joydeep Chandra India
P. Rodríguez France
Jalel Akaichi Tunisia
Lokesh Jain relative to Enrico Corradini Italy Enrico Corradini's profile →
Citations per field
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Citations per year

Countries citing papers authored by Lokesh Jain

Since Specialization
Citations

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

Fields of papers citing papers by Lokesh Jain

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lokesh Jain

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

All Works

18 of 18 papers shown
#WorkIndexed citations
1 21
2 18
3 21
4 70
5 10
6 1
7 69
8 6
9 15
10
MIMO fuzzy logic supervisor-based adaptive control using the example of coupled-tanks levels control
9
11
Design of Process Fuzzy Control for Programmable Logic Controllers
3
12
A New Approach to Supervise Security in Social Network through Quantum Cryptography and Non- Linear Dimension Reduction Techniques
0
13
Advanced techniques in data mining and knowledge discovery
2
14 0
15 6
16 2
17 18
18
Fuzzy clustering models and applications
67

About Lokesh Jain

Lokesh Jain is a scholar working on Statistical and Nonlinear Physics, Architecture and Artificial Intelligence, having authored 18 papers that have together received 338 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (10 papers), Opinion Dynamics and Social Influence (8 papers) and Spam and Phishing Detection (3 papers). The work is most often cited by research in Statistical and Nonlinear Physics (137 citations), Artificial Intelligence (144 citations) and Communication (24 citations). Lokesh Jain has collaborated with scholars based in India, Australia and Bulgaria. Frequent co-authors include Rahul Katarya, Shelly Sachdeva, Janusz Kacprzyk, Yoshiharu Sato, Mika Sato, Motohide Umano, Takao Maeda, Isao Hayashi, Berend Jan van der Zwaag and Dan Corbett. Their work appears in journals such as Expert Systems with Applications, Knowledge-Based Systems and Technology in Society.

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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