Ashish M. Gujarathi

1.2k total citations
54 papers, 924 citations indexed

About

Ashish M. Gujarathi is a scholar working on Control and Systems Engineering, Mechanical Engineering and Computational Theory and Mathematics. According to data from OpenAlex, Ashish M. Gujarathi has authored 54 papers receiving a total of 924 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Control and Systems Engineering, 20 papers in Mechanical Engineering and 16 papers in Computational Theory and Mathematics. Recurrent topics in Ashish M. Gujarathi's work include Process Optimization and Integration (22 papers), Advanced Multi-Objective Optimization Algorithms (16 papers) and Advanced Control Systems Optimization (11 papers). Ashish M. Gujarathi is often cited by papers focused on Process Optimization and Integration (22 papers), Advanced Multi-Objective Optimization Algorithms (16 papers) and Advanced Control Systems Optimization (11 papers). Ashish M. Gujarathi collaborates with scholars based in Oman, India and Indonesia. Ashish M. Gujarathi's co-authors include B. V. Babu, Hasan Mousa, G. Reza Vakili-Nezhaad, Jamil Naser, Chandan Guria, Nallusamy Sivakumar, Mahnaz Mohammadi, Nabeel Al‐Rawahi, Mohammed Al-Aghbari and Reginald Victor and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Cleaner Production and Scientific Reports.

In The Last Decade

Ashish M. Gujarathi

51 papers receiving 898 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ashish M. Gujarathi Oman 17 342 202 195 148 141 54 924
Tilman Barz Austria 19 323 0.9× 255 1.3× 151 0.8× 106 0.7× 114 0.8× 54 886
Shivom Sharma Switzerland 17 284 0.8× 313 1.5× 168 0.9× 109 0.7× 291 2.1× 38 935
Lingyun Wei China 10 154 0.5× 43 0.2× 177 0.9× 166 1.1× 33 0.2× 42 919
Shaobo Deng China 13 96 0.3× 29 0.1× 154 0.8× 57 0.4× 333 2.4× 45 1.1k
Sunwon Park South Korea 21 180 0.5× 733 3.6× 56 0.3× 28 0.2× 286 2.0× 71 1.3k
Boeun Kim South Korea 15 65 0.2× 158 0.8× 304 1.6× 31 0.2× 129 0.9× 50 804
Mirko Skiborowski Germany 30 712 2.1× 727 3.6× 73 0.4× 61 0.4× 605 4.3× 89 1.7k
Ross E. Swaney United States 17 149 0.4× 842 4.2× 33 0.2× 167 1.1× 247 1.8× 35 1.3k
Kristian M. Lien Norway 22 327 1.0× 739 3.7× 81 0.4× 70 0.5× 442 3.1× 62 1.5k
Manojkumar Ramteke India 16 154 0.5× 262 1.3× 83 0.4× 82 0.6× 78 0.6× 64 772

Countries citing papers authored by Ashish M. Gujarathi

Since Specialization
Citations

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

Fields of papers citing papers by Ashish M. Gujarathi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ashish M. Gujarathi. 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 Ashish M. Gujarathi. The network helps show where Ashish M. Gujarathi may publish in the future.

Co-authorship network of co-authors of Ashish M. Gujarathi

This figure shows the co-authorship network connecting the top 25 collaborators of Ashish M. Gujarathi. A scholar is included among the top collaborators of Ashish M. Gujarathi 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 Ashish M. Gujarathi. Ashish M. Gujarathi 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.
Salmi, Mika, et al.. (2025). Environment-, process-, and energy-specific multi-objective optimization of the industrial large-scale natural gas dehydration process. Chemical Engineering Journal Advances. 25. 100980–100980.
2.
Gujarathi, Ashish M., et al.. (2025). Techno-enviro-economic analysis of industrial carbon capture process via multi-criteria optimization and retrofitting approach. Energy. 338. 138912–138912. 1 indexed citations
3.
Gujarathi, Ashish M., et al.. (2025). Towards enhancing sustainable hydrogen production process via process-, energy-, and environmental-based multi-criteria optimization. International Journal of Hydrogen Energy. 133. 472–490. 1 indexed citations
4.
Gujarathi, Ashish M., et al.. (2024). Investigation of sustainable operation oriented- economic, process and environment based multi-criteria optimization of large scale methanol production plant. Journal of Cleaner Production. 474. 143614–143614. 2 indexed citations
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Gujarathi, Ashish M., et al.. (2023). Insight into evolutionary optimization approach of batch and fed-batch fermenters for lactic acid production. SHILAP Revista de lepidopterología. 8. 100105–100105. 4 indexed citations
8.
Al-Aghbari, Mohammed & Ashish M. Gujarathi. (2023). Hybrid approach of using bi-objective genetic programming in well control optimization of waterflood management. Geoenergy Science and Engineering. 228. 211967–211967. 1 indexed citations
9.
Gujarathi, Ashish M., et al.. (2023). Multi-objective optimization of methanol production for energy efficiency and environmental sustainability. Computers & Chemical Engineering. 179. 108426–108426. 11 indexed citations
10.
Gujarathi, Ashish M., et al.. (2021). Safety, economics, environment and energy based criteria towards multi-objective optimization of natural gas sweetening process: An industrial case study. Journal of Natural Gas Science and Engineering. 95. 104207–104207. 28 indexed citations
11.
Al-Aghbari, Mohammed, et al.. (2021). Hybrid Multi-Objective Optimization Approach in Water Flooding. Journal of Energy Resources Technology. 144(6). 8 indexed citations
12.
Gujarathi, Ashish M., et al.. (2020). Towards process, energy and safety based criteria for multi-objective optimization of industrial acid gas removal process. Process Safety and Environmental Protection. 140. 86–99. 17 indexed citations
13.
Gujarathi, Ashish M., et al.. (2020). Multi-objective optimization of industrial gas-sweetening operations using economic and environmental criteria. Process Safety and Environmental Protection. 140. 283–298. 27 indexed citations
14.
Vakili-Nezhaad, G. Reza, et al.. (2019). Molecular dynamics simulation of water–graphene nanofluid. SN Applied Sciences. 1(3). 12 indexed citations
15.
Vakili-Nezhaad, G. Reza, Ashish M. Gujarathi, Nabeel Al‐Rawahi, & Mahnaz Mohammadi. (2019). Performance of WS2 monolayers as a new family of anode materials for metal-ion (mg, Al and ca) batteries. Materials Chemistry and Physics. 230. 114–121. 74 indexed citations
16.
Al-Battashi, Huda, Neelamegam Annamalai, Ashish M. Gujarathi, et al.. (2018). Waste office paper: A potential feedstock for cellulase production by a novel strain Bacillus velezensis ASN1. Waste Management. 79. 491–500. 40 indexed citations
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Gujarathi, Ashish M., et al.. (2015). Optimization of reactor network design problem using Jumping Gene Adaptation of Differential Evolution. Journal of Physics Conference Series. 622. 12044–12044. 4 indexed citations
19.
Gujarathi, Ashish M., et al.. (2011). Differential Evolution using Jumping Genes Adaptation.. 353–370. 1 indexed citations
20.
Gujarathi, Ashish M. & B. V. Babu. (2009). Optimization of Adiabatic Styrene Reactor: A Hybrid Multiobjective Differential Evolution (H-MODE) Approach. Industrial & Engineering Chemistry Research. 48(24). 11115–11132. 28 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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