Felipe Oviedo
- Materials Chemistry top 5%
- Electrical and Electronic Engineering top 10%
- Computational Theory and Mathematics top 5%
- Molecular Biology
- Artificial Intelligence top 10%
- Co-authors
- Tonio BuonassisiJuan Lavista FerresShijing SunKeith T. ButlerZekun RenNoor Titan Putri HartonoSiyu TianA. Gilad Kusne
- Topics
- Machine Learning in Materials Science (11 papers)Perovskite Materials and Applications (8 papers)Chalcogenide Semiconductor Thin Films (5 papers)
- Cited by
- Materials ChemistryComputational Theory and MathematicsElectrical and Electronic Engineering
- Journals
- Nature CommunicationsSHILAP Revista de lepidopterologíaChemical Communications
- Partner nations
- United StatesSingaporeUnited Kingdom
In The Last Decade
Felipe Oviedo
33 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 114
- Materials Chemistry 894
- Electrical and Electronic Engineering 526
- Computational Theory and Mathematics 184
- Molecular Biology 151
- Artificial Intelligence 130
Countries citing papers authored by Felipe Oviedo
This map shows the geographic impact of Felipe Oviedo'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 Felipe Oviedo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Felipe Oviedo more than expected).
Fields of papers citing papers by Felipe Oviedo
This network shows the impact of papers produced by Felipe Oviedo. 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 Felipe Oviedo. The network helps show where Felipe Oviedo may publish in the future.
Co-authorship network of co-authors of Felipe Oviedo
This figure shows the co-authorship network connecting the top 25 collaborators of Felipe Oviedo. A scholar is included among the top collaborators of Felipe Oviedo 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 Felipe Oviedo. Felipe Oviedo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 3 | |
| 4 | 7 | |
| 5 | 0 | |
| 6 | 3 | |
| 7 | 6 | |
| 8 | 6 | |
| 9 | 86 | |
| 10 | 13 | |
| 11 | 28 | |
| 12 | Interpretable and Explainable Machine Learning for Materials Science and Chemistrybreakdown → | 193 |
| 13 | 111 | |
| 14 | 1 | |
| 15 | 28 | |
| 16 | 1 | |
| 17 | 131 | |
| 18 | 3 | |
| 19 | Fast classification of small X-ray diffraction datasets using data augmentation and deep neural networks. | 6 |
| 20 | 30 |
About Felipe Oviedo
Felipe Oviedo is a scholar working on Materials Chemistry, Ecological Modeling and Electrical and Electronic Engineering, having authored 35 papers that have together received 1.4k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (11 papers), Perovskite Materials and Applications (8 papers) and Chalcogenide Semiconductor Thin Films (5 papers). The work is most often cited by research in Materials Chemistry (894 citations), Computational Theory and Mathematics (184 citations) and Electrical and Electronic Engineering (526 citations). Felipe Oviedo has collaborated with scholars based in United States, Singapore and United Kingdom. Frequent co-authors include Tonio Buonassisi, Juan Lavista Ferres, Shijing Sun, Keith T. Butler, Zekun Ren, Noor Titan Putri Hartono, Siyu Tian, A. Gilad Kusne, Savitha Ramasamy and Brian DeCost. Their work appears in journals such as Nature Communications, SHILAP Revista de lepidopterología and Chemical Communications.
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.