Pejman Honarmandi
- Materials Chemistry
- Mechanical Engineering top 10%
- Automotive Engineering
- Statistics, Probability and Uncertainty top 5%
- Mechanics of Materials
- Co-authors
- Raymundo ArróyaveVahid AttariM. Aghaie-KhafriAlaa ElwanyThien Duongİbrahim KaramanLei XueDouglas Allaire
- Topics
- Additive Manufacturing Materials and Processes (8 papers)Machine Learning in Materials Science (7 papers)Additive Manufacturing and 3D Printing Technologies (7 papers)
- Partner nations
- United StatesSwedenIran
In The Last Decade
Pejman Honarmandi
22 papers receiving 288 citations
Peers
Comparison fields: 5 of 46
- Materials Chemistry 184
- Mechanical Engineering 163
- Automotive Engineering 51
- Statistics, Probability and Uncertainty 37
- Mechanics of Materials 36
Countries citing papers authored by Pejman Honarmandi
This map shows the geographic impact of Pejman Honarmandi'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 Pejman Honarmandi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pejman Honarmandi more than expected).
Fields of papers citing papers by Pejman Honarmandi
This network shows the impact of papers produced by Pejman Honarmandi. 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 Pejman Honarmandi. The network helps show where Pejman Honarmandi may publish in the future.
Co-authorship network of co-authors of Pejman Honarmandi
This figure shows the co-authorship network connecting the top 25 collaborators of Pejman Honarmandi. A scholar is included among the top collaborators of Pejman Honarmandi 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 Pejman Honarmandi. Pejman Honarmandi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 6 | |
| 4 | 5 | |
| 5 | 19 | |
| 6 | 22 | |
| 7 | 8 | |
| 8 | 1 | |
| 9 | 21 | |
| 10 | 41 | |
| 11 | 16 | |
| 12 | Materials Design Under Bayesian Uncertainty Quantification | 1 |
| 13 | 23 | |
| 14 | 18 | |
| 15 | 1 | |
| 16 | 6 | |
| 17 | 11 | |
| 18 | 41 | |
| 19 | 5 | |
| 20 | 20 |
About Pejman Honarmandi
Pejman Honarmandi is a scholar working on Statistics, Probability and Uncertainty, Automotive Engineering and Metals and Alloys, having authored 22 papers that have together received 294 indexed citations. Recurring topics across this work include Additive Manufacturing Materials and Processes (8 papers), Machine Learning in Materials Science (7 papers) and Additive Manufacturing and 3D Printing Technologies (7 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (37 citations), Mechanical Engineering (163 citations) and Automotive Engineering (51 citations). Pejman Honarmandi has collaborated with scholars based in United States, Sweden and Iran. Frequent co-authors include Raymundo Arróyave, Vahid Attari, M. Aghaie-Khafri, Alaa Elwany, Thien Duong, İbrahim Karaman, Lei Xue, Douglas Allaire, Marius Stan and Noah H. Paulson. Their work appears in journals such as Acta Materialia, Materials & Design and Additive manufacturing.
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.