Mahyar Salek
- Management Science and Operations Research top 10%
- Artificial Intelligence
- Computer Science Applications top 10%
- Statistical and Nonlinear Physics
- Information Systems
- Co-authors
- Greg StoddardPushmeet KohliSreenivas GollapudiAbhimanyu DasRina PanigrahyYoram BachrachPeter KeyCristopher Moore
- Topics
- Optimization and Search Problems (2 papers)Advanced Image and Video Retrieval Techniques (2 papers)Domain Adaptation and Few-Shot Learning (2 papers)
- Cited by
- Computer Science ApplicationsManagement Science and Operations ResearchStatistical and Nonlinear Physics
- Journals
- Cancer ResearchNational Conference on Artificial IntelligenceProceedings of the AAAI Conference on Artificial Intelligence
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
Mahyar Salek
7 papers receiving 114 citations
Peers
Comparison fields: 5 of 31
- Management Science and Operations Research 55
- Artificial Intelligence 49
- Computer Science Applications 39
- Statistical and Nonlinear Physics 30
- Information Systems 23
Countries citing papers authored by Mahyar Salek
This map shows the geographic impact of Mahyar Salek'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 Mahyar Salek with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mahyar Salek more than expected).
Fields of papers citing papers by Mahyar Salek
This network shows the impact of papers produced by Mahyar Salek. 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 Mahyar Salek. The network helps show where Mahyar Salek may publish in the future.
Co-authorship network of co-authors of Mahyar Salek
This figure shows the co-authorship network connecting the top 25 collaborators of Mahyar Salek. A scholar is included among the top collaborators of Mahyar Salek 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 Mahyar Salek. Mahyar Salek 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 | A fast bandit algorithm for recommendations to users with heterogeneous tastes | 21 |
| 3 | Hotspotting – A Probabilistic Graphical Model For Image Object Localization | 3 |
| 4 | 17 | |
| 5 | 38 | |
| 6 | 24 | |
| 7 | 13 |
About Mahyar Salek
Mahyar Salek is a scholar working on Management Science and Operations Research, Biophysics and Marketing, having authored 7 papers that have together received 117 indexed citations. Recurring topics across this work include Optimization and Search Problems (2 papers), Advanced Image and Video Retrieval Techniques (2 papers) and Domain Adaptation and Few-Shot Learning (2 papers). The work is most often cited by research in Computer Science Applications (39 citations), Management Science and Operations Research (55 citations) and Statistical and Nonlinear Physics (30 citations). Mahyar Salek has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Greg Stoddard, Pushmeet Kohli, Sreenivas Gollapudi, Abhimanyu Das, Rina Panigrahy, Yoram Bachrach, Peter Key, Cristopher Moore, David Kempe and Stéphane C. Boutet. Their work appears in journals such as Cancer Research, National Conference on Artificial Intelligence and Proceedings of the AAAI Conference on Artificial Intelligence.
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.