Ping-Chun Wu

779 total citations
16 papers, 364 citations indexed

About

Ping-Chun Wu is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Hardware and Architecture. According to data from OpenAlex, Ping-Chun Wu has authored 16 papers receiving a total of 364 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Electrical and Electronic Engineering, 4 papers in Artificial Intelligence and 3 papers in Hardware and Architecture. Recurrent topics in Ping-Chun Wu's work include Advanced Memory and Neural Computing (12 papers), Semiconductor materials and devices (8 papers) and Ferroelectric and Negative Capacitance Devices (7 papers). Ping-Chun Wu is often cited by papers focused on Advanced Memory and Neural Computing (12 papers), Semiconductor materials and devices (8 papers) and Ferroelectric and Negative Capacitance Devices (7 papers). Ping-Chun Wu collaborates with scholars based in Taiwan, China and United States. Ping-Chun Wu's co-authors include Meng‐Fan Chang, Jian-Wei Su, Yen-Lin Chung, Chih-Cheng Hsieh, Kea‐Tiong Tang, Chung‐Chuan Lo, Ren-Shuo Liu, Shih-Chieh Chang, Shyh-Shyuan Sheu and Jin-Sheng Ren and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Journal of Solid-State Circuits and Future Internet.

In The Last Decade

Ping-Chun Wu

13 papers receiving 357 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ping-Chun Wu Taiwan 8 323 92 72 51 39 16 364
Hung-Sheng Chang Taiwan 9 223 0.7× 91 1.0× 70 1.0× 80 1.6× 88 2.3× 19 322
Ameya D. Patil United States 6 233 0.7× 40 0.4× 69 1.0× 35 0.7× 28 0.7× 12 265
Yung-Ning Tu Taiwan 9 495 1.5× 88 1.0× 81 1.1× 72 1.4× 32 0.8× 11 525
Ioannis A. Papistas Belgium 9 232 0.7× 33 0.4× 47 0.7× 42 0.8× 23 0.6× 17 259
Zihan Wu China 8 195 0.6× 92 1.0× 69 1.0× 30 0.6× 37 0.9× 17 263
Jan Moritz Joseph Germany 6 142 0.4× 87 0.9× 44 0.6× 49 1.0× 75 1.9× 34 215
Wei-Hsing Huang Taiwan 7 501 1.6× 85 0.9× 93 1.3× 66 1.3× 27 0.7× 10 540
Chengshuo Yu Singapore 7 268 0.8× 71 0.8× 58 0.8× 19 0.4× 32 0.8× 17 305
Shanshan Xie United States 9 233 0.7× 66 0.7× 98 1.4× 26 0.5× 39 1.0× 19 293

Countries citing papers authored by Ping-Chun Wu

Since Specialization
Citations

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

Fields of papers citing papers by Ping-Chun Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ping-Chun Wu. 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 Ping-Chun Wu. The network helps show where Ping-Chun Wu may publish in the future.

Co-authorship network of co-authors of Ping-Chun Wu

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

All Works

16 of 16 papers shown
1.
Wu, Ping-Chun, Win-San Khwa, Ashwin Sanjay Lele, et al.. (2025). A Microscaling Multi-Mode Gain-Cell Computing-in-Memory Macro for Advanced AI Edge Device. IEEE Journal of Solid-State Circuits. 61(1). 211–224.
2.
Khwa, Win-San, Ping-Chun Wu, Jian-Wei Su, et al.. (2025). 14.2 A 16nm 216kb, 188.4TOPS/W and 133.5TFLOPS/W Microscaling Multi-Mode Gain-Cell CIM Macro Edge-AI Devices. 1–3. 1 indexed citations
3.
Jhang, Chuan-Jia, Win-San Khwa, Ping-Chun Wu, et al.. (2024). A 22 nm 10.03-237.99 TOPS/W Time-Digital-Hybrid SRAM Compute-in-Memory AI Accelerator for GNN Edge Device Applications. 1(1). 15–25. 1 indexed citations
4.
Wu, Ping-Chun, Win-San Khwa, Jui-Jen Wu, et al.. (2024). An Integer-Floating-Point Dual-Mode Gain-Cell Computing-in-Memory Macro for Advanced AI Edge Chips. IEEE Journal of Solid-State Circuits. 60(1). 158–170. 1 indexed citations
5.
Lin, Ming-Yen, Ping-Chun Wu, & Sue-Chen Hsueh. (2024). Optimizing Session-Aware Recommenders: A Deep Dive into GRU-Based Latent Interaction Integration. Future Internet. 16(2). 51–51.
6.
7.
Wu, Ping-Chun, et al.. (2023). Session 7 Overview: SRAM Compute-In-Memory: Memory Subcommittee. 124–125. 1 indexed citations
8.
Yue, Jinshan, Yongpan Liu, Xiaoyu Feng, et al.. (2023). An Energy-Efficient Computing-in-Memory NN Processor With Set-Associate Blockwise Sparsity and Ping-Pong Weight Update. IEEE Journal of Solid-State Circuits. 59(5). 1612–1627. 9 indexed citations
9.
Wu, Ping-Chun, Jian-Wei Su, Jin-Sheng Ren, et al.. (2023). A Floating-Point 6T SRAM In-Memory-Compute Macro Using Hybrid-Domain Structure for Advanced AI Edge Chips. IEEE Journal of Solid-State Circuits. 59(1). 196–207. 11 indexed citations
10.
Wu, Ping-Chun, Jian-Wei Su, Yen-Lin Chung, et al.. (2023). An 8b-Precision 6T SRAM Computing-in-Memory Macro Using Time-Domain Incremental Accumulation for AI Edge Chips. IEEE Journal of Solid-State Circuits. 59(7). 2297–2309. 10 indexed citations
11.
12.
Wu, Ping-Chun, Jian-Wei Su, Jin-Sheng Ren, et al.. (2023). A 22nm 832Kb Hybrid-Domain Floating-Point SRAM In-Memory-Compute Macro with 16.2-70.2TFLOPS/W for High-Accuracy AI-Edge Devices. 126–128. 55 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.
15.
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
16.
Chen, Yiren, Ping-Chun Wu, Yu‐Te Lin, et al.. (2021). A Miniature Electronic Nose for Breath Analysis. 2021 IEEE International Electron Devices Meeting (IEDM). 35.2.1–35.2.4. 5 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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2026