Zhezhi He

3.3k total citations
94 papers, 2.1k citations indexed

About

Zhezhi He is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Zhezhi He has authored 94 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 66 papers in Electrical and Electronic Engineering, 33 papers in Artificial Intelligence and 32 papers in Computer Vision and Pattern Recognition. Recurrent topics in Zhezhi He's work include Advanced Memory and Neural Computing (54 papers), Ferroelectric and Negative Capacitance Devices (40 papers) and Advanced Neural Network Applications (32 papers). Zhezhi He is often cited by papers focused on Advanced Memory and Neural Computing (54 papers), Ferroelectric and Negative Capacitance Devices (40 papers) and Advanced Neural Network Applications (32 papers). Zhezhi He collaborates with scholars based in United States, China and Taiwan. Zhezhi He's co-authors include Deliang Fan, Shaahin Angizi, Adnan Siraj Rakin, Farhana Parveen, Li Jiang, Chaitali Chakrabarti, Jingtao Li, Jie Lin, Fangxin Liu and J.S. Yuan and has published in prestigious journals such as Nature Communications, Bioinformatics and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Zhezhi He

87 papers receiving 2.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zhezhi He United States 26 1.3k 857 531 302 235 94 2.1k
Yufei Ding United States 23 832 0.7× 1.1k 1.3× 361 0.7× 450 1.5× 268 1.1× 106 2.0k
Deliang Fan United States 33 2.3k 1.8× 1.2k 1.4× 538 1.0× 498 1.6× 342 1.5× 179 3.2k
Ajay Joshi United States 25 1.6k 1.3× 641 0.7× 183 0.3× 654 2.2× 695 3.0× 124 2.4k
Cong Xu China 19 2.2k 1.7× 724 0.8× 658 1.2× 457 1.5× 558 2.4× 47 3.0k
Mark Anders United States 29 1.9k 1.5× 552 0.6× 408 0.8× 1.3k 4.2× 364 1.5× 143 3.0k
Xing Hu China 19 851 0.7× 618 0.7× 327 0.6× 273 0.9× 205 0.9× 64 1.4k
Xuecheng Zou China 19 1.1k 0.9× 338 0.4× 221 0.4× 268 0.9× 175 0.7× 254 1.9k
Swaroop Ghosh United States 27 1.9k 1.5× 730 0.9× 110 0.2× 981 3.2× 299 1.3× 204 2.6k
Rangharajan Venkatesan United States 21 1.8k 1.4× 682 0.8× 1.0k 1.9× 840 2.8× 540 2.3× 50 2.7k
Massimo Alioto Singapore 38 3.8k 3.0× 582 0.7× 488 0.9× 1.2k 3.9× 308 1.3× 302 4.7k

Countries citing papers authored by Zhezhi He

Since Specialization
Citations

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

Fields of papers citing papers by Zhezhi He

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhezhi He

This figure shows the co-authorship network connecting the top 25 collaborators of Zhezhi He. A scholar is included among the top collaborators of Zhezhi He 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 Zhezhi He. Zhezhi He 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.
2.
Fu, Teng, Miao Pan, Xuhong Zhang, et al.. (2025). VeriRL: Boosting the LLM-based Verilog Code Generation via Reinforcement Learning. 1–9.
3.
Liu, Zihan, Jingwen Leng, Minyi Guo, et al.. (2025). StreamGrid: Streaming Point Cloud Analytics via Compulsory Splitting and Deterministic Termination. 1189–1202.
4.
Qian, Weikang, et al.. (2024). PIMLC: Logic Compiler for Bit-Serial Based PIM. 1–6. 1 indexed citations
5.
Lin, Jie, Huan Hu, Weifeng Zhang, et al.. (2023). VSPIM: SRAM Processing-in-Memory DNN Acceleration via Vector-Scalar Operations. IEEE Transactions on Computers. 73(10). 2378–2390. 3 indexed citations
6.
Yang, Li, Zhezhi He, Yu Cao, & Deliang Fan. (2022). A Progressive Subnetwork Searching Framework for Dynamic Inference. IEEE Transactions on Neural Networks and Learning Systems. 35(3). 3809–3820. 5 indexed citations
7.
Li, Xiaoling, et al.. (2022). DTATrans: Leveraging Dynamic Token-Based Quantization With Accuracy Compensation Mechanism for Efficient Transformer Architecture. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 42(2). 509–520. 12 indexed citations
8.
Liu, Fangxin, et al.. (2022). SoBS-X: Squeeze-Out Bit Sparsity for ReRAM-Crossbar-Based Neural Network Accelerator. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 42(1). 204–217. 8 indexed citations
9.
Ma, Xiaolong, Sheng Lin, Shaokai Ye, et al.. (2021). Non-Structured DNN Weight Pruning—Is It Beneficial in Any Platform?. IEEE Transactions on Neural Networks and Learning Systems. 33(9). 4930–4944. 55 indexed citations
10.
Liu, Fangxin, Wenbo Zhao, Zhezhi He, et al.. (2021). SME: ReRAM-based Sparse-Multiplication-Engine to Squeeze-Out Bit Sparsity of Neural Network. 417–424. 16 indexed citations
11.
Sun, Yanan, Yilong Zhao, Jiachen Jiang, et al.. (2021). Unary Coding and Variation-Aware Optimal Mapping Scheme for Reliable ReRAM-Based Neuromorphic Computing. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 40(12). 2495–2507. 18 indexed citations
12.
Angizi, Shaahin, Zhezhi He, An Chen, & Deliang Fan. (2020). Hybrid Spin-CMOS Polymorphic Logic Gate With Application in In-Memory Computing. IEEE Transactions on Magnetics. 56(2). 1–15. 20 indexed citations
13.
Dev, Durjoy, Adithi Krishnaprasad, Zhezhi He, et al.. (2019). Artificial Neuron using Ag/2D-MoS 2 /Au Threshold Switching Memristor. IEEE Conference Proceedings. 2019. 193–194. 2 indexed citations
14.
Angizi, Shaahin, Zhezhi He, & Deliang Fan. (2018). PIMA-Logic: A Novel Processing-in-Memory Architecture for Highly Flexible and Energy-Efficient Logic Computation. 1–6. 25 indexed citations
15.
Angizi, Shaahin, Zhezhi He, Adnan Siraj Rakin, & Deliang Fan. (2018). CMP-PIM: An Energy-Efficient Comparator-based Processing-In-Memory Neural Network Accelerator. 1–6. 16 indexed citations
16.
Parveen, Farhana, Zhezhi He, Shaahin Angizi, & Deliang Fan. (2018). HieIM: highly flexible in-memory computing using STT MRAM. Asia and South Pacific Design Automation Conference. 361–366. 8 indexed citations
17.
Parveen, Farhana, Shaahin Angizi, Zhezhi He, & Deliang Fan. (2018). IMCS2: Novel Device-to-Architecture Co-Design for Low-Power In-Memory Computing Platform Using Coterminous Spin Switch. IEEE Transactions on Magnetics. 54(7). 1–14. 14 indexed citations
18.
He, Zhezhi, et al.. (2018). Exploring a SOT-MRAM Based In-Memory Computing for Data Processing. Journal of International Crisis and Risk Communication Research. 4(4). 676–685. 29 indexed citations
19.
Angizi, Shaahin, Zhezhi He, Nader Bagherzadeh, & Deliang Fan. (2017). Design and Evaluation of a Spintronic In-Memory Processing Platform for Nonvolatile Data Encryption. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 37(9). 1788–1801. 43 indexed citations
20.
Parveen, Farhana, Shaahin Angizi, Zhezhi He, & Deliang Fan. (2017). Hybrid polymorphic logic gate using 6 terminal magnetic domain wall motion device. Journal of International Crisis and Risk Communication Research. 1–4. 3 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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