Je-Min Hung

1.3k total citations
15 papers, 815 citations indexed

About

Je-Min Hung is a scholar working on Electrical and Electronic Engineering, Cellular and Molecular Neuroscience and Hardware and Architecture. According to data from OpenAlex, Je-Min Hung has authored 15 papers receiving a total of 815 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Electrical and Electronic Engineering, 3 papers in Cellular and Molecular Neuroscience and 3 papers in Hardware and Architecture. Recurrent topics in Je-Min Hung's work include Advanced Memory and Neural Computing (15 papers), Ferroelectric and Negative Capacitance Devices (14 papers) and Semiconductor materials and devices (9 papers). Je-Min Hung is often cited by papers focused on Advanced Memory and Neural Computing (15 papers), Ferroelectric and Negative Capacitance Devices (14 papers) and Semiconductor materials and devices (9 papers). Je-Min Hung collaborates with scholars based in Taiwan, China and United States. Je-Min Hung's co-authors include Meng‐Fan Chang, Chuan-Jia Jhang, Fu-Chun Chang, Cheng-Xin Xue, Chih-Cheng Hsieh, Kea‐Tiong Tang, Ren-Shuo Liu, Tsung-Yung Jonathan Chang, Yu-Der Chih and Win-San Khwa and has published in prestigious journals such as Science, SHILAP Revista de lepidopterología and IEEE Journal of Solid-State Circuits.

In The Last Decade

Je-Min Hung

15 papers receiving 800 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Je-Min Hung Taiwan	12	744	138	123	92	71	15	815
Fu-Chun Chang Taiwan	11	687 0.9×	130 0.9×	109 0.9×	84 0.9×	84 1.2×	13	766
Amogh Agrawal United States	15	673 0.9×	136 1.0×	132 1.1×	56 0.6×	53 0.7×	32	774
Chuan-Jia Jhang Taiwan	9	593 0.8×	118 0.9×	85 0.7×	91 1.0×	54 0.8×	14	649
Yen-Cheng Chiu Taiwan	14	1.0k 1.4×	167 1.2×	172 1.4×	191 2.1×	97 1.4×	20	1.1k
Indranil Chakraborty United States	15	680 0.9×	202 1.5×	63 0.5×	105 1.1×	75 1.1×	36	815
Chorng-Jung Lin Taiwan	8	766 1.0×	99 0.7×	78 0.6×	145 1.6×	51 0.7×	9	804
Sheng-Po Huang Taiwan	7	579 0.8×	100 0.7×	64 0.5×	87 0.9×	69 1.0×	10	631
Anni Lu United States	14	667 0.9×	152 1.1×	62 0.5×	107 1.2×	58 0.8×	36	792
Shubham Jain United States	15	528 0.7×	134 1.0×	82 0.7×	40 0.4×	95 1.3×	33	721
Hongwu Jiang United States	14	734 1.0×	179 1.3×	96 0.8×	134 1.5×	75 1.1×	26	819

Countries citing papers authored by Je-Min Hung

Since Specialization

Citations

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

Fields of papers citing papers by Je-Min Hung

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Je-Min Hung. 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 Je-Min Hung. The network helps show where Je-Min Hung may publish in the future.

Co-authorship network of co-authors of Je-Min Hung

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

All Works

Sort: Min cites: Since: Top N: Style:

15 of 15 papers shown

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

Huang, Wei‐Hsing, Tai-Hao Wen, Je-Min Hung, et al.. (2023). A Nonvolatile Al-Edge Processor with 4MB SLC-MLC Hybrid-Mode ReRAM Compute-in-Memory Macro and 51.4-251TOPS/W. 15–17. 43 indexed citations

Wen, Tai-Hao, Je-Min Hung, Hung-Hsi Hsu, et al.. (2023). A 28nm Nonvolatile AI Edge Processor using 4Mb Analog-Based Near-Memory-Compute ReRAM with 27.2 TOPS/W for Tiny AI Edge Devices. 1–2. 10 indexed citations

Hung, Je-Min, Tai-Hao Wen, Yen-Hsiang Huang, et al.. (2022). 8-b Precision 8-Mb ReRAM Compute-in-Memory Macro Using Direct-Current-Free Time-Domain Readout Scheme for AI Edge Devices. IEEE Journal of Solid-State Circuits. 58(1). 303–315. 32 indexed citations

Hung, Je-Min, Yen-Hsiang Huang, Sheng-Po Huang, et al.. (2022). An 8-Mb DC-Current-Free Binary-to-8b Precision ReRAM Nonvolatile Computing-in-Memory Macro using Time-Space-Readout with 1286.4-21.6TOPS/W for Edge-AI Devices. 2022 IEEE International Solid- State Circuits Conference (ISSCC). 1–3. 86 indexed citations

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

Chiu, Yen-Cheng, Tung-Cheng Chang, Chun‐Ying Lee, et al.. (2021). A 22-nm 1-Mb 1024-b Read Data-Protected STT-MRAM Macro With Near-Memory Shift-and-Rotate Functionality and 42.6-GB/s Read Bandwidth for Security-Aware Mobile Device. IEEE Journal of Solid-State Circuits. 57(6). 1936–1949. 9 indexed citations

Hung, Je-Min, Chun‐Ying Lee, Cheng-Xin Xue, et al.. (2021). CiM3D: Comparator-in-Memory Designs Using Monolithic 3-D Technology for Accelerating Data-Intensive Applications. IEEE Journal on Exploratory Solid-State Computational Devices and Circuits. 7(1). 79–87. 5 indexed citations

Hung, Je-Min, Chuan-Jia Jhang, Ping-Chun Wu, Yen-Cheng Chiu, & Meng‐Fan Chang. (2021). Challenges and Trends of Nonvolatile In-Memory-Computation Circuits for AI Edge Devices. SHILAP Revista de lepidopterología. 1. 171–183. 40 indexed citations

10.

Jhang, Chuan-Jia, Cheng-Xin Xue, Je-Min Hung, Fu-Chun Chang, & Meng‐Fan Chang. (2021). Challenges and Trends of SRAM-Based Computing-In-Memory for AI Edge Devices. IEEE Transactions on Circuits and Systems I Regular Papers. 68(5). 1773–1786. 170 indexed citations

11.

Hung, Je-Min, Cheng-Xin Xue, Hui-Yao Kao, et al.. (2021). A four-megabit compute-in-memory macro with eight-bit precision based on CMOS and resistive random-access memory for AI edge devices. Nature Electronics. 4(12). 921–930. 86 indexed citations

12.

Chang, Tung-Cheng, Yen-Cheng Chiu, Chun‐Ying Lee, et al.. (2020). 13.4 A 22nm 1Mb 1024b-Read and Near-Memory-Computing Dual-Mode STT-MRAM Macro with 42.6GB/s Read Bandwidth for Security-Aware Mobile Devices. 31 indexed citations

13.

Chiu, Yen-Cheng, Zhixiao Zhang, Jiajing Chen, et al.. (2020). A 4-Kb 1-to-8-bit Configurable 6T SRAM-Based Computation-in-Memory Unit-Macro for CNN-Based AI Edge Processors. IEEE Journal of Solid-State Circuits. 55(10). 2790–2801. 65 indexed citations

14.

Hung, Je-Min, Xueqing Li, Juejian Wu, & Meng‐Fan Chang. (2020). Challenges and Trends inDeveloping Nonvolatile Memory-Enabled Computing Chips for Intelligent Edge Devices. IEEE Transactions on Electron Devices. 67(4). 1444–1453. 37 indexed citations

15.

Hung, Je-Min, Chun‐Ying Lee, Cheng-Xin Xue, et al.. (2020). Monolithic 3D+-IC Based Massively Parallel Compute-in-Memory Macro for Accelerating Database and Machine Learning Primitives. 28.5.1–28.5.4. 11 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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