Jonathan Chang

4.1k total citations · 2 hit papers
95 papers, 2.9k citations indexed

About

Jonathan Chang is a scholar working on Electrical and Electronic Engineering, Hardware and Architecture and Genetics. According to data from OpenAlex, Jonathan Chang has authored 95 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 80 papers in Electrical and Electronic Engineering, 13 papers in Hardware and Architecture and 8 papers in Genetics. Recurrent topics in Jonathan Chang's work include Semiconductor materials and devices (40 papers), Advanced Memory and Neural Computing (23 papers) and Ferroelectric and Negative Capacitance Devices (22 papers). Jonathan Chang is often cited by papers focused on Semiconductor materials and devices (40 papers), Advanced Memory and Neural Computing (23 papers) and Ferroelectric and Negative Capacitance Devices (22 papers). Jonathan Chang collaborates with scholars based in Taiwan, United States and Australia. Jonathan Chang's co-authors include Daniel L. Rabosky, Michael E. Alfaro, Stephen A. Smith, Brian L. Sidlauskas, Hung-Jen Liao, Jonathan M. Eastman, Francesco Santini, Jonathan S. Mitchell, Peter F. Cowman and Matt Friedman and has published in prestigious journals such as Nature, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Jonathan Chang

84 papers receiving 2.8k citations

Hit Papers

An inverse latitudinal gradient in speciation rate fo... 2013 2026 2017 2021 2018 2013 200 400 600

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jonathan Chang Taiwan 21 1.2k 626 540 515 477 95 2.9k
Scott A. Taylor United States 34 221 0.2× 326 0.5× 1.5k 2.8× 80 0.2× 940 2.0× 120 3.6k
Joseph F. Ryan United States 32 385 0.3× 37 0.1× 742 1.4× 1.5k 2.9× 523 1.1× 114 3.8k
Mitsumasa Koyanagi Japan 28 340 0.3× 39 0.1× 123 0.2× 127 0.2× 191 0.4× 91 2.5k
Thomas L. Daniel United States 34 163 0.1× 335 0.5× 390 0.7× 162 0.3× 631 1.3× 64 3.4k
Nicholas W. Roberts United Kingdom 27 240 0.2× 165 0.3× 241 0.4× 43 0.1× 418 0.9× 92 2.9k
Lam Si Tung Ho United States 9 28 0.0× 253 0.4× 263 0.5× 261 0.5× 261 0.5× 24 1.1k
David Ferrier United Kingdom 31 91 0.1× 83 0.1× 435 0.8× 481 0.9× 396 0.8× 78 3.5k
Marie Dacke Sweden 35 151 0.1× 161 0.3× 1.2k 2.2× 73 0.1× 359 0.8× 83 3.5k
Marco Corti Italy 25 41 0.0× 447 0.7× 855 1.6× 1.2k 2.3× 902 1.9× 92 3.1k
Georg Mayer Germany 33 40 0.0× 55 0.1× 293 0.5× 671 1.3× 512 1.1× 109 2.7k

Countries citing papers authored by Jonathan Chang

Since Specialization
Citations

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

Fields of papers citing papers by Jonathan Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jonathan Chang. 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 Jonathan Chang. The network helps show where Jonathan Chang may publish in the future.

Co-authorship network of co-authors of Jonathan Chang

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

All Works

20 of 20 papers shown
1.
Wang, Liyu, Perng-Fei Yuh, Yuxiao Wang, et al.. (2024). A New Ultra-Low Voltage Metal Fuse for High Density OTP Applications. 1–2.
2.
Lin, Burn J., et al.. (2024). On-Wafer FinFET-Based 3-D E-Beam Detector Cube for In Situ Monitoring of Advanced Lithography Processes Beyond 5 nm. IEEE Transactions on Electron Devices. 71(6). 3739–3745.
3.
Hsieh, Yu‐Cheng, et al.. (2024). High-density via RRAM cell with multi-level setting by current compliance circuits. SHILAP Revista de lepidopterología. 19(1). 54–54. 2 indexed citations
4.
Shih, Jiaw‐Ren, et al.. (2023). Multilevel Fully Logic-Compatible Latch Array for Computing-in-Memory. IEEE Transactions on Electron Devices. 70(4). 2001–2008.
5.
Chang, Jonathan, et al.. (2023). Assessing the Thermal Safety of a Li Metal Solid-State Battery Material Set Using Differential Scanning Calorimetry. ACS Applied Materials & Interfaces. 15(49). 57134–57143. 6 indexed citations
6.
Lin, Burn J., et al.. (2023). 4K Detectors Array for On-Wafer EUV Imaging in Lithography Control Beyond 5-nm Node. IEEE Transactions on Electron Devices. 70(11). 5713–5719.
7.
Huang, Yihan, Burn J. Lin, Jiaw‐Ren Shih, et al.. (2023). On-Wafer 3D E-beam Detector Cube by FinFET CMOS Technologies. 1 indexed citations
8.
Wang, Yi‐Chung, Shu‐Chi Wu, Tzu‐Yi Yang, et al.. (2021). Multifunctional Ion‐Sensitive Floating Gate Fin Field‐Effect Transistor with Three‐Dimensional Nanoseaweed Structure by Glancing Angle Deposition Technology. Small. 18(5). e2104168–e2104168. 5 indexed citations
10.
Sinangil, Mahmut E., Burak Erbagci, Rawan Naous, et al.. (2020). A 7-nm Compute-in-Memory SRAM Macro Supporting Multi-Bit Input, Weight and Output and Achieving 351 TOPS/W and 372.4 GOPS. IEEE Journal of Solid-State Circuits. 56(1). 188–198. 119 indexed citations
11.
Dong, Qing, Zhehong Wang, Jongyup Lim, et al.. (2018). A 1-Mb 28-nm 1T1MTJ STT-MRAM With Single-Cap Offset-Cancelled Sense Amplifier and <italic>In Situ</italic> Self-Write-Termination. IEEE Journal of Solid-State Circuits. 54(1). 231–239. 41 indexed citations
12.
Rabosky, Daniel L., Jonathan Chang, Pascal O. Title, et al.. (2018). An inverse latitudinal gradient in speciation rate for marine fishes. Nature. 559(7714). 392–395. 608 indexed citations breakdown →
13.
Liu, Shang‐Yin Vanson, Bruno Frédérich, Sébastien Lavoué, et al.. (2018). Buccal venom gland associates with increased of diversification rate in the fang blenny fish Meiacanthus (Blenniidae; Teleostei). Molecular Phylogenetics and Evolution. 125. 138–146. 14 indexed citations
15.
Chang, Jonathan, et al.. (2017). Twin mode NV logic gates for high speed computing system on 16nm FINFET CMOS logic process. 12.1.1–12.1.4. 1 indexed citations
16.
Fujiwara, Hidehiro, Liwen Wang, Yen-Huei Chen, et al.. (2016). A 64kb 16nm Asynchronous Disturb Current Free 2-Port SRAM with PMOS Pass-Gates for FinFET Technologies. IEICE technical report. Speech. 116(3). 17–20. 2 indexed citations
17.
Chang, Jonathan, et al.. (2016). Budget-based reliability management to handle impact of thermal issues in 16nm technology. 4C–2. 4 indexed citations
18.
Chang, Jonathan & Michael E. Alfaro. (2015). Crowdsourced geometric morphometrics enable rapid large‐scale collection and analysis of phenotypic data. Methods in Ecology and Evolution. 7(4). 472–482. 23 indexed citations
19.
Chang, Jonathan, Calvin Pan, Eric M. Sobel, et al.. (2015). Genome-wide ultraconserved elements exhibit higher phylogenetic informativeness than traditional gene markers in percomorph fishes. Molecular Phylogenetics and Evolution. 92. 140–146. 58 indexed citations
20.
Rabosky, Daniel L., Francesco Santini, Jonathan M. Eastman, et al.. (2013). Rates of speciation and morphological evolution are correlated across the largest vertebrate radiation. Nature Communications. 4(1). 1958–1958. 506 indexed citations breakdown →

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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