Onur Cezmi Mutlu
- Computer Networks and Communications top 10%
- Artificial Intelligence top 10%
- Electrical and Electronic Engineering
- Information Systems top 10%
- Computer Vision and Pattern Recognition
- Co-authors
- Kevin HsiehPhillip B. GibbonsAaron HarlapNandita VijaykumarGregory R. GangerMinesh PatelJeremie S. KimDennis P. Wall
- Topics
- Advanced Data Storage Technologies (7 papers)Child Development and Digital Technology (5 papers)Autism Spectrum Disorder Research (5 papers)
- Journals
- SHILAP Revista de lepidopterologíaBioinformaticsIEEE Transactions on Computers
- Partner nations
- United StatesSwitzerlandUnited Kingdom
In The Last Decade
Onur Cezmi Mutlu
18 papers receiving 313 citations
Peers
Comparison fields: 5 of 51
- Computer Networks and Communications 136
- Artificial Intelligence 124
- Electrical and Electronic Engineering 69
- Information Systems 68
- Computer Vision and Pattern Recognition 52
Countries citing papers authored by Onur Cezmi Mutlu
This map shows the geographic impact of Onur Cezmi Mutlu'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 Onur Cezmi Mutlu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Onur Cezmi Mutlu more than expected).
Fields of papers citing papers by Onur Cezmi Mutlu
This network shows the impact of papers produced by Onur Cezmi Mutlu. 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 Onur Cezmi Mutlu. The network helps show where Onur Cezmi Mutlu may publish in the future.
Co-authorship network of co-authors of Onur Cezmi Mutlu
This figure shows the co-authorship network connecting the top 25 collaborators of Onur Cezmi Mutlu. A scholar is included among the top collaborators of Onur Cezmi Mutlu 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 Onur Cezmi Mutlu. Onur Cezmi Mutlu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 4 | |
| 3 | 0 | |
| 4 | 4 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 5 | |
| 8 | 1 | |
| 9 | 4 | |
| 10 | 23 | |
| 11 | 17 | |
| 12 | 10 | |
| 13 | 12 | |
| 14 | 2 | |
| 15 | 4 | |
| 16 | 3 | |
| 17 | Using Crowdsourcing to Train Facial Emotion Machine Learning Models with Ambiguous Labels. | 2 |
| 18 | 29 | |
| 19 | Gaia: geo-distributed machine learning approaching LAN speeds | 184 |
| 20 | 18 |
About Onur Cezmi Mutlu
Onur Cezmi Mutlu is a scholar working on Hardware and Architecture, Pharmacy and Computer Networks and Communications, having authored 20 papers that have together received 325 indexed citations. Recurring topics across this work include Advanced Data Storage Technologies (7 papers), Child Development and Digital Technology (5 papers) and Autism Spectrum Disorder Research (5 papers). The work is most often cited by research in Hardware and Architecture (49 citations), Computational Mathematics (4 citations) and Computer Networks and Communications (136 citations). Onur Cezmi Mutlu has collaborated with scholars based in United States, Switzerland and United Kingdom. Frequent co-authors include Kevin Hsieh, Phillip B. Gibbons, Aaron Harlap, Nandita Vijaykumar, Gregory R. Ganger, Minesh Patel, Jeremie S. Kim, Dennis P. Wall, Peter Washington and Aaron Kline. Their work appears in journals such as SHILAP Revista de lepidopterología, Bioinformatics and IEEE Transactions on Computers.
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.