Shih‐Chii Liu
- Electrical and Electronic Engineering top 0.5%
- Cognitive Neuroscience top 0.5%
- Cellular and Molecular Neuroscience top 0.5%
- Artificial Intelligence top 0.5%
- Computer Vision and Pattern Recognition top 1%
- Co-authors
- Tobi DelbrückGiacomo IndiveriDaniel NeilMichael PfeifferYuhuang HuBodo RueckauerMinhao YangChristian Brändli
- Topics
- Advanced Memory and Neural Computing (77 papers)Neural dynamics and brain function (49 papers)Speech and Audio Processing (35 papers)
- Cited by
- Cognitive NeuroscienceCellular and Molecular NeuroscienceElectrical and Electronic Engineering
- Journals
- Proceedings of the National Academy of SciencesNature CommunicationsJournal of Neuroscience
- Partner nations
- SwitzerlandUnited StatesSpain
In The Last Decade
Shih‐Chii Liu
154 papers receiving 8.2k citations
Hit Papers
Peers
Comparison fields: 5 of 153
- Electrical and Electronic Engineering 6.4k
- Cognitive Neuroscience 3.6k
- Cellular and Molecular Neuroscience 2.2k
- Artificial Intelligence 2.2k
- Computer Vision and Pattern Recognition 871
Countries citing papers authored by Shih‐Chii Liu
This map shows the geographic impact of Shih‐Chii Liu'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 Shih‐Chii Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shih‐Chii Liu more than expected).
Fields of papers citing papers by Shih‐Chii Liu
This network shows the impact of papers produced by Shih‐Chii Liu. 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 Shih‐Chii Liu. The network helps show where Shih‐Chii Liu may publish in the future.
Co-authorship network of co-authors of Shih‐Chii Liu
This figure shows the co-authorship network connecting the top 25 collaborators of Shih‐Chii Liu. A scholar is included among the top collaborators of Shih‐Chii Liu 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 Shih‐Chii Liu. Shih‐Chii Liu 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 | 0 | |
| 3 | 0 | |
| 4 | 4 | |
| 5 | 5 | |
| 6 | 2 | |
| 7 | 12 | |
| 8 | 14 | |
| 9 | 6 | |
| 10 | 18 | |
| 11 | 40 | |
| 12 | 1 | |
| 13 | 22 | |
| 14 | 35 | |
| 15 | 15 | |
| 16 | 9 | |
| 17 | 51 | |
| 18 | 2 | |
| 19 | 13 | |
| 20 | Adaptive Retina with Center-Surround Receptive Field | 8 |
About Shih‐Chii Liu
Shih‐Chii Liu is a scholar working on Signal Processing, Cognitive Neuroscience and Cellular and Molecular Neuroscience, having authored 161 papers that have together received 8.4k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (77 papers), Neural dynamics and brain function (49 papers) and Speech and Audio Processing (35 papers). The work is most often cited by research in Cognitive Neuroscience (3.6k citations), Cellular and Molecular Neuroscience (2.2k citations) and Electrical and Electronic Engineering (6.4k citations). Shih‐Chii Liu has collaborated with scholars based in Switzerland, United States and Spain. Frequent co-authors include Tobi Delbrück, Giacomo Indiveri, Daniel Neil, Michael Pfeiffer, Yuhuang Hu, Bodo Rueckauer, Minhao Yang, Christian Brändli, André van Schaik and Raphael Berner. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Communications and Journal of Neuroscience.
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.