Ruizhe Cai

467 total citations
14 papers, 261 citations indexed

About

Ruizhe Cai is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Ruizhe Cai has authored 14 papers receiving a total of 261 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Electrical and Electronic Engineering, 4 papers in Artificial Intelligence and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Ruizhe Cai's work include Advanced Memory and Neural Computing (6 papers), Ferroelectric and Negative Capacitance Devices (4 papers) and Semiconductor materials and devices (4 papers). Ruizhe Cai is often cited by papers focused on Advanced Memory and Neural Computing (6 papers), Ferroelectric and Negative Capacitance Devices (4 papers) and Semiconductor materials and devices (4 papers). Ruizhe Cai collaborates with scholars based in United States and Japan. Ruizhe Cai's co-authors include Yanzhi Wang, Ao Ren, Caiwen Ding, Bo Yuan, Olivia Chen, Nobuyuki Yoshikawa, Xuehai Qian, Ning Liu, Qinru Qiu and Zhe Li and has published in prestigious journals such as Scientific Reports, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems and ACM SIGPLAN Notices.

In The Last Decade

Ruizhe Cai

14 papers receiving 258 citations

Peers

Countries citing papers authored by Ruizhe Cai

Since Specialization

Citations

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

Fields of papers citing papers by Ruizhe Cai

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ruizhe Cai

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

All Works

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14 of 14 papers shown

#	Work	Indexed citations
1	Emerging opportunities in machine learning hardware acceleration: from advanced neural networks implementation to ultra-efficient deep learning framework using next generation technology. 2020 ·Ruizhe Cai	1
2	Adiabatic Quantum-Flux-Parametron: Towards Building Extremely Energy-Efficient Circuits and Systems 2019 ·Scientific Reports ·Olivia Chen, Ruizhe Cai, Yanzhi Wang, (unknown), (unknown), (unknown), Naoki Takeuchi, Nobuyuki Yoshikawa	35
3	A Majority Logic Synthesis Framework for Adiabatic Quantum-Flux-Parametron Superconducting Circuits 2019 ·Ruizhe Cai, Olivia Chen, Ao Ren, Ning Liu, Caiwen Ding, Nobuyuki Yoshikawa, Yanzhi Wang	22
4	A Buffer and Splitter Insertion Framework for Adiabatic Quantum-Flux-Parametron Superconducting Circuits 2019 ·Ruizhe Cai, Olivia Chen, Ao Ren, (unknown), Nobuyuki Yoshikawa, Yanzhi Wang	18
5	IDE Development, Logic Synthesis and Buffer/Splitter Insertion Framework for Adiabatic Quantum-Flux-Parametron Superconducting Circuits 2019 ·Ruizhe Cai, Xiaolong Ma, Olivia Chen, Ao Ren, Ning Liu, Nobuyuki Yoshikawa, Yanzhi Wang	5
6	HEIF: Highly Efficient Stochastic Computing-Based Inference Framework for Deep Neural Networks 2018 ·IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems ·Zhe Li, Ji Li, Ao Ren, Ruizhe Cai, Caiwen Ding, Xuehai Qian, Jeffrey Draper, Bo Yuan, Jian Tang, Qinru Qiu, Yanzhi Wang	67
7	Deep reinforcement learning: Algorithm, applications, and ultra-low-power implementation 2018 ·Nano Communication Networks ·Hongjia Li, Ruizhe Cai, Ning Liu, Xue Lin, Yanzhi Wang	27
8	VIBNN 2018 ·ACM SIGPLAN Notices ·Ruizhe Cai, Ao Ren, Ning Liu, Caiwen Ding, Luhao Wang, Xuehai Qian, Massoud Pedram, Yanzhi Wang	36
9	A low-computation-complexity, energy-efficient, and high-performance linear program solver based on primal–dual interior point method using memristor crossbars 2018 ·Nano Communication Networks ·Ruizhe Cai, Ao Ren, Sucheta Soundarajan, Yanzhi Wang	5
10	Hardware Acceleration of Bayesian Neural Networks Using RAM Based Linear Feedback Gaussian Random Number Generators 2017 ·Ruizhe Cai, Ao Ren, (unknown), (unknown), Yanzhi Wang	4
11	Algorithm-hardware co-optimization of the memristor-based framework for solving SOCP and homogeneous QCQP problems 2017 ·Ao Ren, Sijia Liu, Ruizhe Cai, Wujie Wen, Pramod K. Varshney, Yanzhi Wang	3
12	Memristor crossbar-based ultra-efficient next-generation baseband processors 2017 ·Geng Yuan, Caiwen Ding, Ruizhe Cai, Xiaolong Ma, (unknown), Ao Ren, Bo Yuan, Yanzhi Wang	22
13	A low-computation-complexity, energy-efficient, and high-performance linear program solver using memristor crossbars 2016 ·Ruizhe Cai, Ao Ren, Yanzhi Wang, Sucheta Soundarajan, Qinru Qiu, Bo Yuan, Paul Bogdan	6
14	Memristor-Based Discrete Fourier Transform for Improving Performance and Energy Efficiency 2016 ·Ruizhe Cai, Ao Ren, Yanzhi Wang, Bo Yuan	10

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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