Ramin Hasani
- Artificial Intelligence top 5%
- Control and Systems Engineering top 10%
- Electrical and Electronic Engineering
- Cognitive Neuroscience top 10%
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Radu GrosuDaniela RusMathias LechnerAlexander AminiThomas A. HenzingerAaron RayGuodong WangGerald Teschl
- Topics
- Neural Networks and Applications (8 papers)Model Reduction and Neural Networks (7 papers)Reinforcement Learning in Robotics (5 papers)
- Journals
- PLoS ONEPhilosophical Transactions of the Royal Society B Biological SciencesApplied Soft Computing
- Partner nations
- AustriaUnited StatesUnited Kingdom
In The Last Decade
Ramin Hasani
30 papers receiving 680 citations
Peers
Comparison fields: 5 of 101
- Artificial Intelligence 235
- Control and Systems Engineering 139
- Electrical and Electronic Engineering 134
- Cognitive Neuroscience 125
- Computer Vision and Pattern Recognition 72
Countries citing papers authored by Ramin Hasani
This map shows the geographic impact of Ramin Hasani'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 Ramin Hasani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ramin Hasani more than expected).
Fields of papers citing papers by Ramin Hasani
This network shows the impact of papers produced by Ramin Hasani. 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 Ramin Hasani. The network helps show where Ramin Hasani may publish in the future.
Co-authorship network of co-authors of Ramin Hasani
This figure shows the co-authorship network connecting the top 25 collaborators of Ramin Hasani. A scholar is included among the top collaborators of Ramin Hasani 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 Ramin Hasani. Ramin Hasani 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 | 33 | |
| 3 | 1 | |
| 4 | 62 | |
| 5 | 2 | |
| 6 | 69 | |
| 7 | 7 | |
| 8 | 21 | |
| 9 | 3 | |
| 10 | 119 | |
| 11 | Learning Long-Term Dependencies in Irregularly-Sampled Time Series | 4 |
| 12 | 8 | |
| 13 | 1 | |
| 14 | 6 | |
| 15 | 10 | |
| 16 | 45 | |
| 17 | 15 | |
| 18 | 46 | |
| 19 | 14 | |
| 20 | On the ε-Best Coapproximation | 1 |
About Ramin Hasani
Ramin Hasani is a scholar working on Aging, Statistical and Nonlinear Physics and Artificial Intelligence, having authored 30 papers that have together received 700 indexed citations. Recurring topics across this work include Neural Networks and Applications (8 papers), Model Reduction and Neural Networks (7 papers) and Reinforcement Learning in Robotics (5 papers). The work is most often cited by research in Aging (43 citations), Artificial Intelligence (235 citations) and Health Informatics (9 citations). Ramin Hasani has collaborated with scholars based in Austria, United States and United Kingdom. Frequent co-authors include Radu Grosu, Daniela Rus, Mathias Lechner, Alexander Amini, Thomas A. Henzinger, Aaron Ray, Guodong Wang, Gerald Teschl, Stephen Larson and Max Tschaikowski. Their work appears in journals such as PLoS ONE, Philosophical Transactions of the Royal Society B Biological Sciences and Applied Soft Computing.
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.