Pradeep Jangir

227 total papers · 6.5k total citations
176 papers, 4.4k citations indexed

About

Pradeep Jangir is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Pradeep Jangir has authored 176 papers receiving a total of 4.4k indexed citations (citations by other indexed papers that have themselves been cited), including 84 papers in Electrical and Electronic Engineering, 65 papers in Artificial Intelligence and 56 papers in Computational Theory and Mathematics. Recurrent topics in Pradeep Jangir's work include Advanced Multi-Objective Optimization Algorithms (56 papers), Metaheuristic Optimization Algorithms Research (53 papers) and Optimal Power Flow Distribution (35 papers). Pradeep Jangir is often cited by papers focused on Advanced Multi-Objective Optimization Algorithms (56 papers), Metaheuristic Optimization Algorithms Research (53 papers) and Optimal Power Flow Distribution (35 papers). Pradeep Jangir collaborates with scholars based in India, Jordan and Saudi Arabia. Pradeep Jangir's co-authors include M. Premkumar, R. Sowmya, Seyedali Mirjalili, Indrajit N. Trivedi, Shahrzad Saremi, Narottam Jangir, Hassan Haes Alhelou, Sundaram B. Pandya, B. Santhosh Kumar and Laith Abualigah and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Expert Systems with Applications.

In The Last Decade

Pradeep Jangir

152 papers receiving 4.2k citations

Hit Papers

Multi-objective ant lion ... 2016 2026 2019 2022 2016 2017 2023 2024 2025 100 200 300 400 500
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation benchmark for papers published in the same subfield and year, or reaches the top citation threshold in at least one of its specific research topics.

  1. Multi-objective ant lion optimizer: a multi-objective optimization algorithm for solving engineering problems
    2016 553 citations Seyedali Mirjalili, Pradeep Jangir et al. Applied Intelligence profile →
  2. Optimization of problems with multiple objectives using the multi-verse optimization algorithm
    2017 280 citations Seyedali Mirjalili, Pradeep Jangir et al. Knowledge-Based Systems profile →
  3. Newton-Raphson-based optimizer: A new population-based metaheuristic algorithm for continuous optimization problems
    2023 194 citations R. Sowmya, M. Premkumar et al. Engineering Applications of Artificial Intelligence profile →
  4. Multi-objective exponential distribution optimizer (MOEDO): a novel math-inspired multi-objective algorithm for global optimization and real-world engineering design problems
    2024 44 citations Kanak Kalita, Janjhyam Venkata Naga Ramesh et al. Scientific Reports profile →
  5. MORIME: A multi-objective RIME optimization framework for efficient truss design
    2025 27 citations Mohammad Aljaidi, Nikunj Mashru et al. Results in Engineering profile →
  6. Advancing truss structure optimization—A multi-objective weighted average algorithm with enhanced convergence and diversity
    2025 19 citations Kanak Kalita, Lenka Čepová et al. Results in Engineering profile →
  7. Machine learning-based prediction of elliptical double steel columns under compression loading
    2025 16 citations Rende Mu, Abdelrahman Kamal Hamed et al. Journal Of Big Data profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Pradeep Jangir 1.8k 1.6k 1.2k 808 549 176 4.4k
Tao Zhang 1.3k 0.7× 1.8k 1.1× 1.2k 1.0× 1.0k 1.3× 190 0.3× 236 4.2k
M. Premkumar 1.8k 1.0× 1.6k 1.0× 663 0.5× 821 1.0× 1.2k 2.3× 138 4.2k
Viviana Cocco Mariani 2.3k 1.3× 3.2k 2.0× 852 0.7× 1.0k 1.3× 395 0.7× 214 7.8k
Liying Wang 1.9k 1.1× 1.1k 0.6× 880 0.7× 805 1.0× 231 0.4× 58 3.9k
Zhile Yang 1.1k 0.6× 2.6k 1.6× 400 0.3× 863 1.1× 372 0.7× 184 4.9k
S. Baskar 2.7k 1.5× 1.9k 1.1× 1.5k 1.2× 1.3k 1.6× 148 0.3× 104 5.7k
Fatma A. Hashim 2.8k 1.5× 1.1k 0.7× 1.2k 1.0× 844 1.0× 188 0.3× 80 5.0k
Ali Sadollah 2.3k 1.3× 896 0.5× 1.5k 1.2× 875 1.1× 159 0.3× 87 5.1k
Pavel Trojovský 1.9k 1.0× 954 0.6× 665 0.5× 634 0.8× 154 0.3× 119 4.3k
Ali Wagdy Mohamed 2.7k 1.5× 681 0.4× 1.4k 1.1× 444 0.5× 269 0.5× 191 4.3k

Countries citing papers authored by Pradeep Jangir

Since Specialization
Citations

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

Fields of papers citing papers by Pradeep Jangir

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pradeep Jangir

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

All Works

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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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