H.‐S. Philip Wong

52.0k total citations · 20 hit papers
643 papers, 39.6k citations indexed

About

H.‐S. Philip Wong is a scholar working on Electrical and Electronic Engineering, Materials Chemistry and Biomedical Engineering. According to data from OpenAlex, H.‐S. Philip Wong has authored 643 papers receiving a total of 39.6k indexed citations (citations by other indexed papers that have themselves been cited), including 535 papers in Electrical and Electronic Engineering, 285 papers in Materials Chemistry and 112 papers in Biomedical Engineering. Recurrent topics in H.‐S. Philip Wong's work include Semiconductor materials and devices (239 papers), Advanced Memory and Neural Computing (215 papers) and Advancements in Semiconductor Devices and Circuit Design (181 papers). H.‐S. Philip Wong is often cited by papers focused on Semiconductor materials and devices (239 papers), Advanced Memory and Neural Computing (215 papers) and Advancements in Semiconductor Devices and Circuit Design (181 papers). H.‐S. Philip Wong collaborates with scholars based in United States, Taiwan and China. H.‐S. Philip Wong's co-authors include Shimeng Yu, Daniele Ielmini, Subhasish Mitra, D.J. Frank, Yuan Taur, Ximeng Guan, Jie Deng, Jie Deng, Rakesh Jeyasingh and Duygu Kuzum and has published in prestigious journals such as Nature, Science and Journal of the American Chemical Society.

In The Last Decade

H.‐S. Philip Wong

624 papers receiving 38.3k citations

Hit Papers

In-memory computing with ... 1997 2026 2006 2016 2018 2010 2019 2016 2019 500 1000 1.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
H.‐S. Philip Wong United States 96 32.9k 14.8k 6.7k 5.3k 3.7k 643 39.6k
Wei Lü United States 86 27.6k 0.8× 7.6k 0.5× 5.8k 0.9× 9.9k 1.9× 4.4k 1.2× 398 33.7k
Cheol Seong Hwang South Korea 90 33.6k 1.0× 20.9k 1.4× 3.8k 0.6× 4.9k 0.9× 5.9k 1.6× 802 38.2k
Rainer Waser Germany 103 38.1k 1.2× 25.2k 1.7× 6.3k 0.9× 10.1k 1.9× 8.5k 2.3× 852 49.2k
J. Joshua Yang United States 77 31.7k 1.0× 6.3k 0.4× 1.6k 0.2× 13.8k 2.6× 5.9k 1.6× 266 35.7k
Daniele Ielmini Italy 72 17.9k 0.5× 6.3k 0.4× 862 0.1× 4.7k 0.9× 3.7k 1.0× 388 19.0k
Jianshi Tang China 54 8.9k 0.3× 3.7k 0.3× 1.4k 0.2× 2.4k 0.5× 1.5k 0.4× 217 13.2k
Duncan R. Stewart United States 31 18.7k 0.6× 2.9k 0.2× 1.1k 0.2× 7.5k 1.4× 3.1k 0.8× 50 20.2k
Qiangfei Xia United States 51 14.8k 0.5× 3.0k 0.2× 1.4k 0.2× 6.2k 1.2× 2.1k 0.6× 137 16.4k
Massimiliano Di Ventra United States 58 10.9k 0.3× 3.2k 0.2× 2.9k 0.4× 2.2k 0.4× 842 0.2× 267 15.5k
Suman Datta United States 68 15.6k 0.5× 5.5k 0.4× 2.4k 0.4× 492 0.1× 1.1k 0.3× 514 18.1k

Countries citing papers authored by H.‐S. Philip Wong

Since Specialization
Citations

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

Fields of papers citing papers by H.‐S. Philip Wong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by H.‐S. Philip Wong. 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 H.‐S. Philip Wong. The network helps show where H.‐S. Philip Wong may publish in the future.

Co-authorship network of co-authors of H.‐S. Philip Wong

This figure shows the co-authorship network connecting the top 25 collaborators of H.‐S. Philip Wong. A scholar is included among the top collaborators of H.‐S. Philip Wong 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 H.‐S. Philip Wong. H.‐S. Philip Wong 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.
Liu, Shuhan, Robert M. Radway, Xinxin Wang, et al.. (2025). Monolithic 3-D Integration of Diverse Memories: Resistive Switching (RRAM) and Gain Cell (GC) Memory Integrated on Si CMOS. IEEE Transactions on Electron Devices. 72(5). 2685–2690.
2.
Liu, Shuhan, Robert M. Radway, Xinxin Wang, et al.. (2024). Future of Memory: Massive, Diverse, Tightly Integrated with Compute - from Device to Software. 1–4. 4 indexed citations
3.
Liu, Shuhan, Robert M. Radway, Xinxin Wang, et al.. (2024). Edge Continual Training and Inference with RRAM-Gain Cell Memory Integrated on Si CMOS. 1–4. 1 indexed citations
4.
Sathaiya, D. Mahaveer, Edward Chen, Chen-Feng Hsu, et al.. (2024). On the Extreme Scaling of Transistors with Monolayer MOS2 Channel. 1–2. 6 indexed citations
5.
6.
Lin, Qing, Sheng‐Kai Su, Zichen Zhang, et al.. (2023). Band-to-Band Tunneling Leakage Current Characterization and Projection in Carbon Nanotube Transistors. ACS Nano. 17(21). 21083–21092. 11 indexed citations
7.
Chuu, Chih‐Piao, Sheng‐Kai Su, Shengman Li, et al.. (2023). Small Molecule Additives to Suppress Bundling in Dimensional‐Limited Self‐Alignment Method for High‐Density Aligned Carbon Nanotube Array. Advanced Materials Interfaces. 11(6). 7 indexed citations
8.
Bishop, Mindy D., H.‐S. Philip Wong, Subhasish Mitra, & Max M. Shulaker. (2019). Monolithic 3-D Integration. IEEE Micro. 39(6). 16–27. 44 indexed citations
9.
Johnston, Scott R., Edwin Ng, Scott W. Fong, et al.. (2019). Scanning microwave imaging of optically patterned Ge2Sb2Te5. Applied Physics Letters. 114(9). 3 indexed citations
10.
Aly, Mohamed M. Sabry, Tony F. Wu, Gage Hills, et al.. (2018). The N3XT Approach to Energy-Efficient Abundant-Data Computing. Proceedings of the IEEE. 107(1). 19–48. 87 indexed citations
11.
Fong, Scott W., Christopher M. Neumann, Eilam Yalon, et al.. (2017). Dual-Layer Dielectric Stack for Thermally Isolated Low-Energy Phase-Change Memory. IEEE Transactions on Electron Devices. 64(11). 4496–4502. 29 indexed citations
12.
Aly, Mohamed M. Sabry, Mingyu Gao, Tony F. Wu, et al.. (2017). Special session paper 3D nanosystems enable embedded abundant-data computing. 3 indexed citations
13.
14.
Shulaker, Max M., Tony F. Wu, Mohamed M. Sabry, et al.. (2015). Monolithic 3D integration: a path from concept to reality. Design, Automation, and Test in Europe. 1197–1202. 21 indexed citations
15.
Yu, Shimeng, Hongyu Chen, Yexin Deng, et al.. (2013). 3D vertical RRAM - Scaling limit analysis and demonstration of 3D array operation. Symposium on VLSI Technology. 39 indexed citations
16.
Shulaker, Max M., Gage Hills, Nishant Patil, et al.. (2013). Carbon nanotube computer. Nature. 501(7468). 526–530. 763 indexed citations breakdown →
17.
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
18.
Wei, Hai, Jie Zhang, Lan Wei, et al.. (2011). Carbon nanotube imperfection-immune digital VLSI: frequently asked questions updated. International Conference on Computer Aided Design. 227–230. 6 indexed citations
19.
Wong, H.‐S. Philip, Simone Raoux, Sang‐Bum Kim, et al.. (2010). Phase Change Memory. Proceedings of the IEEE. 98(12). 2201–2227. 1402 indexed citations breakdown →
20.
Frank, D.J., Yuan Taur, M. Ieong, & H.‐S. Philip Wong. (1999). Monte Carlo modeling of threshold variation due to dopant fluctuations. 169–170. 139 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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