Kevin J. Shih
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Aerospace Engineering
- Signal Processing
- Media Technology top 10%
- Co-authors
- Bryan CatanzaroAndrew TaoFitsum A. RedaKaran SapraShawn NewsamYi ZhuDerek HoiemIan Endres
- Topics
- Speech Recognition and Synthesis (5 papers)Topic Modeling (4 papers)Multimodal Machine Learning Applications (4 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligencearXiv (Cornell University)PubMed Central
- Partner nations
- United StatesUnited KingdomTürkiye
In The Last Decade
Kevin J. Shih
15 papers receiving 398 citations
Peers
Comparison fields: 5 of 62
- Computer Vision and Pattern Recognition 318
- Artificial Intelligence 164
- Aerospace Engineering 46
- Signal Processing 35
- Media Technology 32
Countries citing papers authored by Kevin J. Shih
This map shows the geographic impact of Kevin J. Shih'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 Kevin J. Shih with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kevin J. Shih more than expected).
Fields of papers citing papers by Kevin J. Shih
This network shows the impact of papers produced by Kevin J. Shih. 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 Kevin J. Shih. The network helps show where Kevin J. Shih may publish in the future.
Co-authorship network of co-authors of Kevin J. Shih
This figure shows the co-authorship network connecting the top 25 collaborators of Kevin J. Shih. A scholar is included among the top collaborators of Kevin J. Shih 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 Kevin J. Shih. Kevin J. Shih 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 | 5 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 2 | |
| 6 | 4 | |
| 7 | 35 | |
| 8 | 31 | |
| 9 | Flowtron: an Autoregressive Flow-based Generative Network for Text-to-Speech Synthesis | 2 |
| 10 | RAD-TTS: Parallel Flow-Based TTS with Robust Alignment Learning and Diverse Synthesis | 14 |
| 11 | 11 | |
| 12 | Graphical Contrastive Losses for Scene Graph Generation. | 14 |
| 13 | 247 | |
| 14 | 5 | |
| 15 | 6 | |
| 16 | 41 | |
| 17 | 1 |
About Kevin J. Shih
Kevin J. Shih is a scholar working on Family Practice, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 17 papers that have together received 419 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (5 papers), Topic Modeling (4 papers) and Multimodal Machine Learning Applications (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (318 citations), Artificial Intelligence (164 citations) and Media Technology (32 citations). Kevin J. Shih has collaborated with scholars based in United States, United Kingdom and Türkiye. Frequent co-authors include Bryan Catanzaro, Andrew Tao, Fitsum A. Reda, Karan Sapra, Shawn Newsam, Yi Zhu, Derek Hoiem, Ian Endres, Rafael Valle and Adrian Łańcucki. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, arXiv (Cornell University) and PubMed Central.
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.