Evan Sheehan
Impact in
- Instrumentation top 5%
- Astronomy and Astrophysical Research
- Astronomy and Astrophysics top 10%
- Stellar, planetary, and galactic studies
- Astrophysics and Star Formation Studies
- Galaxies: Formation, Evolution, Phenomena
- Gamma-ray bursts and supernovae
- Astro and Planetary Science
- Astrophysical Phenomena and Observations
Papers in
-
- Multimodal Machine Learning Applications 2
- Advanced Image and Video Retrieval Techniques 1
- Co-authors
- Burak Uzkent (3 shared papers)Stefano Ermon (3 shared papers)Haakon Faste (1 shared paper)Marshall Burke (2 shared papers)Chenlin Meng (2 shared papers)David B. Lobell (2 shared papers)Kumar Ayush (1 shared paper)Matthew Tan (1 shared paper)
- Journals
- Publications of the Astronomical Society of the Pacific (2 papers)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- United StatesFranceGermany
In The Last Decade
Evan Sheehan
6 papers receiving 546 citations
Evan Sheehan's Hit Papers
Peers
Comparison fields: 5 of 71
- Instrumentation 188
- Astronomy and Astrophysics 566
- Spectroscopy 56
- Nuclear and High Energy Physics 39
- Atmospheric Science 31
Countries citing papers authored by Evan Sheehan
This map shows the geographic impact of Evan Sheehan'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 Evan Sheehan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Evan Sheehan more than expected).
Fields of papers citing papers by Evan Sheehan
This network shows the impact of papers produced by Evan Sheehan. 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 Evan Sheehan. The network helps show where Evan Sheehan may publish in the future.
Co-authors
The 9 scholars most cited alongside Evan Sheehan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | The Science Performance of JWST as Characterized in Commissioning Hit paper breakdown → | 2023 | 380 |
| 2 | The Mid-infrared Instrument for JWST and Its In-flight Performance Hit paper breakdown → | 2023 | 268 |
| 3 | 2013 | 23 | |
| 4 | 2019 | 20 | |
| 5 | 2019 | 16 | |
| 6 | 2022 | 13 |
About Evan Sheehan
Evan Sheehan is a scholar working on Computer Vision and Pattern Recognition, Instrumentation, Communication, Artificial Intelligence and Astronomy and Astrophysics, having authored 6 papers that have together received 720 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (2 papers), Multimodal Machine Learning Applications (2 papers), Advanced Image and Video Retrieval Techniques (1 paper), Calibration and Measurement Techniques (1 paper), Knowledge Management and Sharing (1 paper), Data-Driven Disease Surveillance (1 paper), Optical Systems and Laser Technology (1 paper) and COVID-19 diagnosis using AI (1 paper). The work is most often cited by research in Instrumentation (188 citations), Astronomy and Astrophysics (566 citations), Spectroscopy (56 citations), Nuclear and High Energy Physics (39 citations) and Atmospheric Science (31 citations). Evan Sheehan has collaborated with scholars based in United States, France and Germany. Frequent co-authors include Burak Uzkent, Stefano Ermon, Haakon Faste, Marshall Burke, Chenlin Meng, David B. Lobell, Kumar Ayush, Matthew Tan and Neal Jean. Their work appears in journals such as Publications of the Astronomical Society of the Pacific, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) and arXiv (Cornell University).
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.