Ritam Guha

941 total citations
24 papers, 594 citations indexed

About

Ritam Guha is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Ritam Guha has authored 24 papers receiving a total of 594 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Artificial Intelligence, 7 papers in Computational Theory and Mathematics and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in Ritam Guha's work include Metaheuristic Optimization Algorithms Research (10 papers), Evolutionary Algorithms and Applications (9 papers) and Advanced Multi-Objective Optimization Algorithms (7 papers). Ritam Guha is often cited by papers focused on Metaheuristic Optimization Algorithms Research (10 papers), Evolutionary Algorithms and Applications (9 papers) and Advanced Multi-Objective Optimization Algorithms (7 papers). Ritam Guha collaborates with scholars based in India, United States and Australia. Ritam Guha's co-authors include Ram Sarkar, Manosij Ghosh, Ajith Abraham, Kushal Kanti Ghosh, Neeraj Kumar, Pawan Kumar Singh, Vikrant Bhateja, Seyedali Mirjalili, Debotosh Bhattacharjee and Andrew Tomkins and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and IEEE Transactions on Evolutionary Computation.

In The Last Decade

Ritam Guha

22 papers receiving 571 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ritam Guha India 12 404 164 87 67 47 24 594
Hakan Ezgi Kızılöz Türkiye 10 329 0.8× 94 0.6× 83 1.0× 40 0.6× 40 0.9× 20 517
Ghada Khoriba Egypt 9 382 0.9× 146 0.9× 113 1.3× 61 0.9× 17 0.4× 42 608
Hossein Nematzadeh Iran 14 371 0.9× 307 1.9× 79 0.9× 62 0.9× 102 2.2× 31 688
Artur Ferreira Portugal 8 281 0.7× 169 1.0× 37 0.4× 70 1.0× 97 2.1× 31 607
Eghbal G. Mansoori Iran 12 356 0.9× 120 0.7× 104 1.2× 74 1.1× 106 2.3× 50 571
Yanpeng Qu China 13 248 0.6× 109 0.7× 68 0.8× 72 1.1× 24 0.5× 49 388
Ayça Deniz Türkiye 8 303 0.8× 87 0.5× 78 0.9× 29 0.4× 35 0.7× 15 436
Xuewen Chen United States 8 357 0.9× 99 0.6× 37 0.4× 65 1.0× 71 1.5× 19 507
Faliang Huang China 13 396 1.0× 152 0.9× 30 0.3× 133 2.0× 25 0.5× 50 702
Nailah Al–Madi Jordan 11 312 0.8× 80 0.5× 47 0.5× 41 0.6× 21 0.4× 26 548

Countries citing papers authored by Ritam Guha

Since Specialization
Citations

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

Fields of papers citing papers by Ritam Guha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ritam Guha

This figure shows the co-authorship network connecting the top 25 collaborators of Ritam Guha. A scholar is included among the top collaborators of Ritam Guha 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 Ritam Guha. Ritam Guha 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
1.
2.
Guha, Ritam, Sreeja Lakshmi, Tiehui Wang, Eakapol Wangkahart, & Preetham Elumalai. (2025). Protective efficacy of Interferon-γ and β-glucan adjuvanted formalin killed vaccines in Nile tilapia against Edwardsiella tarda infection. Developmental & Comparative Immunology. 169. 105404–105404. 1 indexed citations
3.
4.
Lakshmi, Sreeja, Ritam Guha, Alex Wang, et al.. (2025). Analysis of the efficacy of two molecular adjuvants, flagellin and IFN-γ, on the immune response against Streptococcus agalactiae in Nile tilapia (Oreochromis niloticus). Fish Physiology and Biochemistry. 51(1). 47–47. 5 indexed citations
5.
Guha, Ritam, et al.. (2023). Discrete equilibrium optimizer combined with simulated annealing for feature selection. Journal of Computational Science. 67. 101942–101942. 18 indexed citations
6.
Guha, Ritam, et al.. (2023). Virtual metrology in long batch processes using machine learning. Materials and Manufacturing Processes. 38(15). 1997–2008. 4 indexed citations
7.
Guha, Ritam, Wei Ao, Vishnu Naresh Boddeti, et al.. (2023). MOAZ: A Multi-Objective AutoML-Zero Framework. Proceedings of the Genetic and Evolutionary Computation Conference. 485–492. 2 indexed citations
8.
Guha, Ritam & Kalyanmoy Deb. (2023). Compromising Pareto-Optimality With Regularity in Platform-Based Multiobjective Optimization. IEEE Transactions on Evolutionary Computation. 28(6). 1746–1760. 3 indexed citations
9.
Park, Daniel, Xingyou Song, Mitchell McIntire, et al.. (2023). Discovering Adaptable Symbolic Algorithms from Scratch. 3889–3896. 2 indexed citations
10.
Guha, Ritam, et al.. (2022). Groundwater Flow Algorithm: A Novel Hydro-Geology Based Optimization Algorithm. IEEE Access. 10. 132193–132211. 9 indexed citations
11.
Guha, Ritam, Manosij Ghosh, Pawan Kumar Singh, Ram Sarkar, & Mita Nasipuri. (2021). A Hybrid Swarm and Gravitation-based feature selection algorithm for handwritten Indic script classification problem. Complex & Intelligent Systems. 7(2). 823–839. 8 indexed citations
12.
Ghosh, Kushal Kanti, et al.. (2021). S-shaped versus V-shaped transfer functions for binary Manta ray foraging optimization in feature selection problem. Neural Computing and Applications. 33(17). 11027–11041. 83 indexed citations
13.
Guha, Ritam, et al.. (2021). Enhancement of image contrast using Selfish Herd Optimizer. Multimedia Tools and Applications. 81(1). 637–657. 7 indexed citations
14.
Guha, Ritam, et al.. (2020). Introducing clustering based population in Binary Gravitational Search Algorithm for Feature Selection. Applied Soft Computing. 93. 106341–106341. 42 indexed citations
15.
Ghosh, Manosij, et al.. (2020). Fuzzy mutation embedded hybrids of gravitational search and Particle Swarm Optimization methods for engineering design problems. Engineering Applications of Artificial Intelligence. 95. 103847–103847. 17 indexed citations
16.
Ghosh, Manosij, Ritam Guha, Pawan Kumar Singh, Vikrant Bhateja, & Ram Sarkar. (2019). A histogram based fuzzy ensemble technique for feature selection. Evolutionary Intelligence. 12(4). 713–724. 13 indexed citations
17.
Ghosh, Manosij, et al.. (2019). Binary Genetic Swarm Optimization: A Combination of GA and PSO for Feature Selection. SHILAP Revista de lepidopterología. 29(1). 1598–1610. 43 indexed citations
18.
Guha, Ritam, et al.. (2019). Deluge based Genetic Algorithm for feature selection. Evolutionary Intelligence. 14(2). 357–367. 69 indexed citations
19.
Guha, Ritam, Manosij Ghosh, Pawan Kumar Singh, Ram Sarkar, & Mita Nasipuri. (2019). M-HMOGA: A New Multi-Objective Feature Selection Algorithm for Handwritten Numeral Classification. SHILAP Revista de lepidopterología. 29(1). 1453–1467. 13 indexed citations
20.
Ghosh, Manosij, Ritam Guha, Ram Sarkar, & Ajith Abraham. (2019). A wrapper-filter feature selection technique based on ant colony optimization. Neural Computing and Applications. 32(12). 7839–7857. 136 indexed citations

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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