Chi-Shuen Lee

859 total citations
12 papers, 578 citations indexed

About

Chi-Shuen Lee is a scholar working on Electrical and Electronic Engineering, Materials Chemistry and Biomedical Engineering. According to data from OpenAlex, Chi-Shuen Lee has authored 12 papers receiving a total of 578 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Electrical and Electronic Engineering, 9 papers in Materials Chemistry and 5 papers in Biomedical Engineering. Recurrent topics in Chi-Shuen Lee's work include Carbon Nanotubes in Composites (7 papers), Advanced Memory and Neural Computing (4 papers) and Advancements in Semiconductor Devices and Circuit Design (4 papers). Chi-Shuen Lee is often cited by papers focused on Carbon Nanotubes in Composites (7 papers), Advanced Memory and Neural Computing (4 papers) and Advancements in Semiconductor Devices and Circuit Design (4 papers). Chi-Shuen Lee collaborates with scholars based in United States. Chi-Shuen Lee's co-authors include H.‐S. Philip Wong, Eric Pop, Aaron D. Franklin, Wilfried Haensch, Gage Hills, Subhasish Mitra, Max M. Shulaker, Lan Wei, Ximeng Guan and Kenneth E. Goodson and has published in prestigious journals such as IEEE Transactions on Electron Devices, Computer and IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

In The Last Decade

Chi-Shuen Lee

12 papers receiving 558 citations

Peers

Chi-Shuen Lee
Farhana Parveen United States
Jixuan Wu China
Sven Beyer Germany
Srivatsa Srinivasa United States
Mostafizur Rahman United States
Chilhee Chung South Korea
Farhana Parveen United States
Chi-Shuen Lee
Citations per year, relative to Chi-Shuen Lee Chi-Shuen Lee (= 1×) peers Farhana Parveen

Countries citing papers authored by Chi-Shuen Lee

Since Specialization
Citations

This map shows the geographic impact of Chi-Shuen Lee'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 Chi-Shuen Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chi-Shuen Lee more than expected).

Fields of papers citing papers by Chi-Shuen Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chi-Shuen Lee. 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 Chi-Shuen Lee. The network helps show where Chi-Shuen Lee may publish in the future.

Co-authorship network of co-authors of Chi-Shuen Lee

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

All Works

12 of 12 papers shown
1.
Lee, Chi-Shuen, Brian Cline, Saurabh Sinha, Greg Yeric, & H.‐S. Philip Wong. (2016). 32-bit Processor core at 5-nm technology: Analysis of transistor and interconnect impact on VLSI system performance. 28.3.1–28.3.4. 36 indexed citations
2.
Lee, Chi-Shuen, Eric Pop, Aaron D. Franklin, Wilfried Haensch, & H.‐S. Philip Wong. (2015). A Compact Virtual-Source Model for Carbon Nanotube FETs in the Sub-10-nm Regime—Part I: Intrinsic Elements. IEEE Transactions on Electron Devices. 62(9). 3061–3069. 195 indexed citations
3.
Lee, Chi-Shuen, Eric Pop, & H.‐S. Philip Wong. (2015). Compact modeling and design optimization of carbon nanotube field-effect transistors for the sub-10-nm technology nodes. 275–276. 5 indexed citations
4.
Hills, Gage, Jie Zhang, Max M. Shulaker, et al.. (2015). Rapid Co-Optimization of Processing and Circuit Design to Overcome Carbon Nanotube Variations. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 34(7). 1082–1095. 37 indexed citations
5.
Lee, Chi-Shuen & H.‐S. Philip Wong. (2015). Stanford Virtual-Source Carbon Nanotube Field-Effect Transistors Model. 20 indexed citations
6.
Aly, Mohamed M. Sabry, Mingyu Gao, Gage Hills, et al.. (2015). Energy-Efficient Abundant-Data Computing: The N3XT 1,000x. Computer. 48(12). 24–33. 166 indexed citations
7.
Ahn, Chiyui, Zizhen Jiang, Chi-Shuen Lee, et al.. (2015). 1D Selection Device Using Carbon Nanotube FETs for High-Density Cross-Point Memory Arrays. IEEE Transactions on Electron Devices. 62(7). 2197–2204. 34 indexed citations
8.
Ahn, Chiyui, Zizhen Jiang, Chi-Shuen Lee, et al.. (2014). A 1TnR array architecture using a one-dimensional selection device. 32. 1–2. 4 indexed citations
9.
Wei, Hai, Max M. Shulaker, Gage Hills, et al.. (2013). Carbon nanotube circuits: opportunities and challenges. Design, Automation, and Test in Europe. 619–624. 7 indexed citations
10.
Wei, Lan, Chi-Shuen Lee, Aaron D. Franklin, et al.. (2013). Compact Model for Carbon Nanotube Field-Effect Transistors Including Nonidealities and Calibrated With Experimental Data Down to 9-nm Gate Length. IEEE Transactions on Electron Devices. 60(6). 1834–1843. 67 indexed citations
11.
Lee, Chi-Shuen, et al.. (2013). Compact models of emerging devices. 12. 1–2. 1 indexed citations
12.
Wei, Hai, Max M. Shulaker, Gage Hills, et al.. (2013). Carbon Nanotube Circuits: Opportunities and Challenges. Design, Automation & Test in Europe Conference & Exhibition (DATE), 2013. 619–624. 6 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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