Andy Shih
Impact in
- Ophthalmology top 10%
- Ocular Infections and Treatments
- Retinal and Optic Conditions
- Ocular Diseases and Behçet’s Syndrome
- Glaucoma and retinal disorders
Papers in
-
- Bayesian Modeling and Causal Inference 3
- Machine Learning and Data Classification 2
- Reinforcement Learning in Robotics 2
- Explainable Artificial Intelligence (XAI) 2
- Data Stream Mining Techniques 1
- Natural Language Processing Techniques 1
- Artificial Intelligence in Games 1
- Co-authors
- Adnan Darwiche (3 shared papers)Arthur Choi (3 shared papers)Stefano Ermon (5 shared papers)Wei‐Chi Wu (1 shared paper)Eugene Yu‐Chuan Kang (1 shared paper)Ching‐Hsi Hsiao (1 shared paper)Chi‐Hung Lin (1 shared paper)Chang‐Fu Kuo (1 shared paper)
- Journals
- Diagnostics (1 paper)2022 17th ACM/IEEE International Conference on Human-Robot Interaction (HRI) (1 paper)arXiv (Cornell University) (2 papers)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)Neural Information Processing Systems (1 paper)
- Partner nations
- United StatesFranceTaiwan
In The Last Decade
Andy Shih
9 papers receiving 125 citations
Peers
Comparison fields: 5 of 43
- Ophthalmology 48
- Health Informatics 3
- Artificial Intelligence 59
- Computational Mathematics 1
- Radiology, Nuclear Medicine and Imaging 24
Countries citing papers authored by Andy Shih
This map shows the geographic impact of Andy 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 Andy Shih with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andy Shih more than expected).
Fields of papers citing papers by Andy Shih
This network shows the impact of papers produced by Andy 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 Andy Shih. The network helps show where Andy Shih may publish in the future.
Co-authors
The 14 scholars most cited alongside Andy Shih, 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 | 2021 | 53 | |
| 2 | 2019 | 20 | |
| 3 | 2020 | 19 | |
| 4 | 2021 | 14 | |
| 5 | Formal Verification of Bayesian Network Classifiers | 2018 | 11 |
| 6 | Probabilistic Circuits for Variational Inference in Discrete Graphical Models | 2020 | 2 |
| 7 | 2022 | 2 | |
| 8 | 2024 | 2 | |
| 9 | 2021 | 2 |
About Andy Shih
Andy Shih is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Theory and Mathematics, Control and Systems Engineering and Computational Mathematics, having authored 9 papers that have together received 125 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (3 papers), Rough Sets and Fuzzy Logic (2 papers), Machine Learning and Data Classification (2 papers), Reinforcement Learning in Robotics (2 papers), Explainable Artificial Intelligence (XAI) (2 papers), Data Stream Mining Techniques (1 paper), Natural Language Processing Techniques (1 paper) and Artificial Intelligence in Games (1 paper). The work is most often cited by research in Ophthalmology (48 citations), Health Informatics (3 citations), Artificial Intelligence (59 citations), Computational Mathematics (1 citation) and Radiology, Nuclear Medicine and Imaging (24 citations). Andy Shih has collaborated with scholars based in United States, France and Taiwan. Frequent co-authors include Adnan Darwiche, Arthur Choi, Stefano Ermon, Wei‐Chi Wu, Eugene Yu‐Chuan Kang, Ching‐Hsi Hsiao, Chi‐Hung Lin, Chang‐Fu Kuo, Ming‐Tse Kuo and Yih-Shiou Hwang. Their work appears in journals such as Diagnostics, 2022 17th ACM/IEEE International Conference on Human-Robot Interaction (HRI), arXiv (Cornell University), Proceedings of the AAAI Conference on Artificial Intelligence and Neural Information Processing Systems.
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.