Mehdi Amini
- Hardware and Architecture top 5%
- Artificial Intelligence top 10%
- Computer Networks and Communications top 10%
- Electrical and Electronic Engineering
- Computer Vision and Pattern Recognition
- Co-authors
- Chris LattnerJacques A. PienaarAlbert CohenTatiana ShpeismanOleksandr ZinenkoNicolas VasilacheUday BondhugulaAndy Davis
- Topics
- Parallel Computing and Optimization Techniques (6 papers)Logic, programming, and type systems (3 papers)Computational Physics and Python Applications (2 papers)
- Journals
- Repository for Publications and Research Data (ETH Zurich)Proceedings of the Python in Science Conferences
- Partner nations
- United StatesFranceSwitzerland
In The Last Decade
Mehdi Amini
6 papers receiving 303 citations
Hit Papers
Peers
Comparison fields: 5 of 38
- Hardware and Architecture 198
- Artificial Intelligence 124
- Computer Networks and Communications 105
- Electrical and Electronic Engineering 56
- Computer Vision and Pattern Recognition 50
Countries citing papers authored by Mehdi Amini
This map shows the geographic impact of Mehdi Amini'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 Mehdi Amini with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mehdi Amini more than expected).
Fields of papers citing papers by Mehdi Amini
This network shows the impact of papers produced by Mehdi Amini. 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 Mehdi Amini. The network helps show where Mehdi Amini may publish in the future.
Co-authorship network of co-authors of Mehdi Amini
This figure shows the co-authorship network connecting the top 25 collaborators of Mehdi Amini. A scholar is included among the top collaborators of Mehdi Amini 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 Mehdi Amini. Mehdi Amini is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | MLIR: Scaling Compiler Infrastructure for Domain Specific Computationbreakdown → | 252 |
| 3 | 16 | |
| 4 | 20 | |
| 5 | 19 | |
| 6 | 1 |
About Mehdi Amini
Mehdi Amini is a scholar working on Hardware and Architecture, Artificial Intelligence and Information Systems, having authored 6 papers that have together received 316 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (6 papers), Logic, programming, and type systems (3 papers) and Computational Physics and Python Applications (2 papers). The work is most often cited by research in Hardware and Architecture (198 citations), Computational Mathematics (12 citations) and Software (28 citations). Mehdi Amini has collaborated with scholars based in United States, France and Switzerland. Frequent co-authors include Chris Lattner, Jacques A. Pienaar, Albert Cohen, Tatiana Shpeisman, Oleksandr Zinenko, Nicolas Vasilache, Uday Bondhugula, Andy Davis, Xavier Corbillon and Tobias Grosser. Their work appears in journals such as Repository for Publications and Research Data (ETH Zurich) and Proceedings of the Python in Science Conferences.
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.