Jay Airao
Impact in
- Mechanical Engineering top 5%
- Advanced machining processes and optimization
- Additive Manufacturing Materials and Processes
- Advanced materials and composites
-
- Engineering Technology and Methodologies
- Manufacturing Process and Optimization
Papers in
-
- Advanced machining processes and optimization 27
- Additive Manufacturing Materials and Processes 6
-
- Advanced Machining and Optimization Techniques 22
- Co-authors
- Chandrakant K. Nirala (20 shared papers)Navneet Khanna (12 shared papers)Grzegorz Królczyk (3 shared papers)Rachele Bertolini (1 shared paper)Hussien Hegab (2 shared papers)Anish Roy (1 shared paper)Ramin Aghababaei (5 shared papers)Tam T. Truong (2 shared papers)
In The Last Decade
Jay Airao
28 papers receiving 642 citations
Peers
Comparison fields: 5 of 39
- Mechanical Engineering 599
- Industrial and Manufacturing Engineering 88
- Electrical and Electronic Engineering 377
- Biomedical Engineering 252
- Automotive Engineering 47
Countries citing papers authored by Jay Airao
This map shows the geographic impact of Jay Airao'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 Jay Airao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jay Airao more than expected).
Fields of papers citing papers by Jay Airao
This network shows the impact of papers produced by Jay Airao. 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 Jay Airao. The network helps show where Jay Airao may publish in the future.
Co-authors
The 24 scholars most cited alongside Jay Airao, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 121 | |
| 2 | 2022 | 59 | |
| 3 | 2022 | 42 | |
| 4 | 2022 | 37 | |
| 5 | 2022 | 35 | |
| 6 | 2019 | 34 | |
| 7 | 2024 | 34 | |
| 8 | 2023 | 32 | |
| 9 | 2020 | 31 | |
| 10 | 2018 | 25 | |
| 11 | 2021 | 24 | |
| 12 | 2023 | 24 | |
| 13 | 2022 | 22 | |
| 14 | 2022 | 22 | |
| 15 | 2024 | 13 | |
| 16 | 2022 | 13 | |
| 17 | 2022 | 12 | |
| 18 | 2021 | 12 | |
| 19 | 2021 | 12 | |
| 20 | 2022 | 11 |
About Jay Airao
Jay Airao is a scholar working on Mechanical Engineering, Electrical and Electronic Engineering, Biomedical Engineering, Computational Mechanics and Industrial and Manufacturing Engineering, having authored 29 papers that have together received 656 indexed citations. Recurring topics across this work include Advanced machining processes and optimization (27 papers), Advanced Machining and Optimization Techniques (22 papers), Advanced Surface Polishing Techniques (10 papers), Additive Manufacturing Materials and Processes (6 papers), Laser Material Processing Techniques (4 papers), Tunneling and Rock Mechanics (3 papers), Industrial Vision Systems and Defect Detection (2 papers) and Engineering Technology and Methodologies (2 papers). The work is most often cited by research in Mechanical Engineering (599 citations), Industrial and Manufacturing Engineering (88 citations), Electrical and Electronic Engineering (377 citations), Biomedical Engineering (252 citations) and Automotive Engineering (47 citations). Jay Airao has collaborated with scholars based in India, Denmark and Poland. Frequent co-authors include Chandrakant K. Nirala, Navneet Khanna, Grzegorz Królczyk, Rachele Bertolini, Hussien Hegab, Anish Roy, Ramin Aghababaei, Tam T. Truong, Bhavesh Chaudhary and Vivek Bajpai. Their work appears in journals such as Tribology International, The International Journal of Advanced Manufacturing Technology, Wear, Sustainable materials and technologies and Measurement.
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.