Kea‐Tiong Tang

7.1k total citations
200 papers, 4.1k citations indexed

About

Kea‐Tiong Tang is a scholar working on Electrical and Electronic Engineering, Biomedical Engineering and Cellular and Molecular Neuroscience. According to data from OpenAlex, Kea‐Tiong Tang has authored 200 papers receiving a total of 4.1k indexed citations (citations by other indexed papers that have themselves been cited), including 147 papers in Electrical and Electronic Engineering, 96 papers in Biomedical Engineering and 42 papers in Cellular and Molecular Neuroscience. Recurrent topics in Kea‐Tiong Tang's work include Advanced Memory and Neural Computing (70 papers), Advanced Chemical Sensor Technologies (57 papers) and Gas Sensing Nanomaterials and Sensors (37 papers). Kea‐Tiong Tang is often cited by papers focused on Advanced Memory and Neural Computing (70 papers), Advanced Chemical Sensor Technologies (57 papers) and Gas Sensing Nanomaterials and Sensors (37 papers). Kea‐Tiong Tang collaborates with scholars based in Taiwan, China and Iran. Kea‐Tiong Tang's co-authors include Shih-Wen Chiu, Meng‐Fan Chang, Chih-Cheng Hsieh, Ren-Shuo Liu, Sudhir Kumar Pandey, Ki‐Hyun Kim, Chung‐Chuan Lo, Wei-Chen Wei, Cheng-Xin Xue and Hung-Yi Hsieh and has published in prestigious journals such as Science, Applied Physics Letters and Langmuir.

In The Last Decade

Kea‐Tiong Tang

180 papers receiving 4.1k citations

Peers

Kea‐Tiong Tang

EEE

CMN

BIOEN

Xiaojin Zhao China

Ankur Srivastava United States

H. Troy Nagle United States

Wenbin Ye China

Chi-Ying Tsui Hong Kong

Sukhan Lee South Korea

Giuseppe Ferri Italy

Qiang Li China

Eugenio Martinelli Italy

Ming Wang China

Xiaojin Zhao China

Kea‐Tiong Tang

1.0k ×0.3

EEE

959 ×0.8

197 ×0.4

CMN

75 ×0.2

207 ×0.5

BIOEN

Citations per year, relative to Kea‐Tiong Tang Kea‐Tiong Tang (= 1×) peers Xiaojin Zhao

Countries citing papers authored by Kea‐Tiong Tang

Since Specialization

Citations

This map shows the geographic impact of Kea‐Tiong Tang'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 Kea‐Tiong Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kea‐Tiong Tang more than expected).

Fields of papers citing papers by Kea‐Tiong Tang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kea‐Tiong Tang. 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 Kea‐Tiong Tang. The network helps show where Kea‐Tiong Tang may publish in the future.

Co-authorship network of co-authors of Kea‐Tiong Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Kea‐Tiong Tang. A scholar is included among the top collaborators of Kea‐Tiong Tang 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 Kea‐Tiong Tang. Kea‐Tiong Tang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Gupta, Shivam, Yu-Hsien Lin, Shih-Wen Chiu, et al.. (2025). Low temperature inkjet-printed metal oxide sensors for sensitive and selective NO ₂ detection. Nanoscale. 17(22). 13850–13860. 2 indexed citations

Zhang, Jian, et al.. (2025). ANP-G: A 28-nm 1.04-pJ/SOP Sub-mm² Asynchronous Hybrid Neural Network Olfactory Processor Enabling Few-Shot Class-Incremental On-Chip Learning. IEEE Journal of Solid-State Circuits. 60(7). 2660–2670.

Hu, Yuhang, Fan Yin, Li‐Peng Zhou, et al.. (2025). Coordination-assembly of a redox-active Pd₆L₃ cage for aerobic C(sp³)–H bond photooxidation of aromatic cyclic ethers. Chemical Communications. 61(43). 7819–7822.

Khwa, Win-San, Jui-Jen Wu, Chuan-Jia Jhang, et al.. (2024). A 22nm Nonvolatile AI-Edge Processor with 21.4TFLOPS/W using 47.25Mb Lossless-Compressed-Computing STT-MRAM Near-Memory-Compute Macro. 1–2. 3 indexed citations

Wen, Tai-Hao, Je-Min Hung, Wei-Hsing Huang, et al.. (2024). Fusion of memristor and digital compute-in-memory processing for energy-efficient edge computing. Science. 384(6693). 325–332. 47 indexed citations

Chiu, Shih-Wen, et al.. (2024). Gas Identification Algorithm Based on Dynamic Response Analysis of Metal Oxide Sensors Under Temperature Modulation. IEEE Access. 12. 87900–87908. 3 indexed citations

Gupta, Shivam, et al.. (2023). Chemiresistive room temperature NO2 sensor based on nitrogen doped zinc oxide nanowires. Sensors and Actuators B Chemical. 394. 134438–134438. 8 indexed citations

Zhang, Jilin, Jian Zhang, Chunqi Qian, et al.. (2023). 22.6 ANP-I: A 28nm 1.5pJ/SOP Asynchronous Spiking Neural Network Processor Enabling Sub-O.1 μJ/Sample On-Chip Learning for Edge-AI Applications. 21–23. 26 indexed citations

Zhang, Jilin, Xinyu Dai, Jian Zhang, et al.. (2023). ANP-G: A 28nm 1.04pJ/SOP Sub-mm2 Spiking and Back-propagation Hybrid Neural Network Asynchronous Olfactory Processor Enabling Few-shot Class-incremental On-chip Learning. 1–2. 8 indexed citations

10.

Wang, Yi, et al.. (2023). Security and Functional Safety for AI in Embedded Automotive System—A Tutorial. IEEE Transactions on Circuits & Systems II Express Briefs. 71(3). 1701–1707. 9 indexed citations

11.

Hsu, Tzu-Hsiang, Guan-Cheng Chen, Yiren Chen, et al.. (2023). A 0.8 V Intelligent Vision Sensor With Tiny Convolutional Neural Network and Programmable Weights Using Mixed-Mode Processing-in-Sensor Technique for Image Classification. IEEE Journal of Solid-State Circuits. 58(11). 3266–3274. 19 indexed citations

12.

Zamani, Milad, et al.. (2023). A 4.5 $\mu$W Miniaturized 3-Channel Wireless Intra-Cardiac Acquisition System. IEEE Transactions on Biomedical Circuits and Systems. 17(5). 1097–1110. 4 indexed citations

13.

Wu, Ping-Chun, Jian-Wei Su, Yen-Lin Chung, et al.. (2022). A 28nm 1Mb Time-Domain Computing-in-Memory 6T-SRAM Macro with a 6.6ns Latency, 1241GOPS and 37.01TOPS/W for 8b-MAC Operations for Edge-AI Devices. 2022 IEEE International Solid- State Circuits Conference (ISSCC). 1–3. 91 indexed citations

14.

Fang, Zhongyuan, Fei Gao, Haoran Jin, et al.. (2022). A Review of Emerging Electromagnetic-Acoustic Sensing Techniques for Healthcare Monitoring. IEEE Transactions on Biomedical Circuits and Systems. 16(6). 1075–1094. 19 indexed citations

15.

Xue, Cheng-Xin, Je-Min Hung, Hui-Yao Kao, et al.. (2021). 16.1 A 22nm 4Mb 8b-Precision ReRAM Computing-in-Memory Macro with 11.91 to 195.7TOPS/W for Tiny AI Edge Devices. 245–247. 143 indexed citations

16.

Xue, Cheng-Xin, Ting-Wei Chang, Hui-Yao Kao, et al.. (2020). 15.4 A 22nm 2Mb ReRAM Compute-in-Memory Macro with 121-28TOPS/W for Multibit MAC Computing for Tiny AI Edge Devices. 244–246. 180 indexed citations

17.

Tang, Kea‐Tiong, et al.. (2020). A Fully Integrated High-Power-Supply-Rejection Linear Regulator With an Output-Supplied Voltage Reference. IEEE Transactions on Circuits and Systems I Regular Papers. 67(11). 3828–3838. 7 indexed citations

18.

Wei, Wei-Chen, Chuan-Jia Jhang, Yiren Chen, et al.. (2020). A Relaxed Quantization Training Method for Hardware Limitations of Resistive Random Access Memory (ReRAM)-Based Computing-in-Memory. IEEE Journal on Exploratory Solid-State Computational Devices and Circuits. 6(1). 45–52. 10 indexed citations

19.

Hsu, Tzu-Hsiang, Yiren Chen, Ren-Shuo Liu, et al.. (2020). A 0.5-V Real-Time Computational CMOS Image Sensor With Programmable Kernel for Feature Extraction. IEEE Journal of Solid-State Circuits. 56(5). 1588–1596. 65 indexed citations

20.

Yang, Chia‐Min, et al.. (2016). Detection of third-hand smoke on clothing fibers with a surface acoustic wave gas sensor. Biomicrofluidics. 10(1). 11907–11907. 15 indexed citations

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.

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