Yu Cao

18.4k total citations · 4 hit papers
409 papers, 13.9k citations indexed

About

Yu Cao is a scholar working on Electrical and Electronic Engineering, Biomedical Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Yu Cao has authored 409 papers receiving a total of 13.9k indexed citations (citations by other indexed papers that have themselves been cited), including 326 papers in Electrical and Electronic Engineering, 55 papers in Biomedical Engineering and 49 papers in Computer Vision and Pattern Recognition. Recurrent topics in Yu Cao's work include Semiconductor materials and devices (143 papers), Advancements in Semiconductor Devices and Circuit Design (139 papers) and Advanced Memory and Neural Computing (89 papers). Yu Cao is often cited by papers focused on Semiconductor materials and devices (143 papers), Advancements in Semiconductor Devices and Circuit Design (139 papers) and Advanced Memory and Neural Computing (89 papers). Yu Cao collaborates with scholars based in United States, China and Japan. Yu Cao's co-authors include Wei Zhao, Sarma Vrudhula, Jae-sun Seo, Wenping Wang, Yufei Ma, Rakesh Vattikonda, Wei Zhao, Shimeng Yu, Sarvesh Bhardwaj and Chongwu Zhou and has published in prestigious journals such as Advanced Materials, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Yu Cao

392 papers receiving 13.4k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

New Generation of Predictive Technology Model for Sub-45 nm Early Design Exploration

2006 677 citations Yu Cao et al. profile →
Flexible Hybrid Electronics for Digital Healthcare

2019 513 citations Yu Cao et al. profile →
New paradigm of predictive MOSFET and interconnect modeling for early circuit simulation

2002 398 citations Yu Cao et al. profile →
Throughput-Optimized OpenCL-based FPGA Accelerator for Large-Scale Convolutional Neural Networks

2016 393 citations Abinash Mohanty, Yufei Ma et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Yu Cao United States	55	10.8k	2.6k	2.3k	1.4k	1.1k	409	13.9k
Meng‐Fan Chang Taiwan	54	9.2k 0.9×	1.5k 0.6×	514 0.2×	752 0.5×	1.3k 1.2×	289	10.1k
Yusuf Leblebici Switzerland	38	6.9k 0.6×	700 0.3×	2.3k 1.0×	384 0.3×	728 0.7×	473	8.2k
Jie Han Canada	46	7.1k 0.7×	1.9k 0.7×	2.2k 1.0×	400 0.3×	1.0k 1.0×	258	8.9k
Hoi‐Jun Yoo South Korea	49	6.5k 0.6×	1.2k 0.5×	4.1k 1.7×	2.2k 1.6×	1.1k 1.1×	545	10.8k
Arijit Raychowdhury United States	42	4.9k 0.5×	878 0.3×	1.1k 0.5×	383 0.3×	1.1k 1.0×	292	6.0k
Subhasish Mitra United States	59	10.8k 1.0×	5.1k 2.0×	1.6k 0.7×	164 0.1×	723 0.7×	353	13.2k
Dennis Sylvester United States	71	16.6k 1.5×	5.6k 2.2×	4.4k 1.9×	756 0.6×	774 0.7×	602	19.0k
Kaushik Roy United States	85	28.4k 2.6×	8.3k 3.2×	3.8k 1.7×	1.3k 1.0×	3.5k 3.3×	1.0k	32.6k
Jan M. Rabaey United States	70	17.1k 1.6×	5.6k 2.1×	6.7k 2.9×	768 0.6×	1.4k 1.3×	438	24.8k
David Blaauw United States	79	20.8k 1.9×	9.9k 3.8×	4.2k 1.8×	1.1k 0.8×	1.3k 1.2×	684	24.7k

Countries citing papers authored by Yu Cao

Since Specialization

Citations

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

Fields of papers citing papers by Yu Cao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yu Cao

This figure shows the co-authorship network connecting the top 25 collaborators of Yu Cao. A scholar is included among the top collaborators of Yu Cao 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 Yu Cao. Yu Cao 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:

20 of 20 papers shown

Li, Sijie, T. J. Jiang, Yu Cao, et al.. (2025). TiO2 Nanorod Array for Betavoltaic Cells: Performance Validation and Enhancement with Electron Beam and 63Ni Irradiations. Nanomaterials. 15(12). 923–923.

Wang, Xiaobo, et al.. (2025). Unified neural network model for predicting optical responses in gold nanostructures. Journal of Applied Physics. 137(6). 2 indexed citations

Zhang, Fan, Wei Zhang, Nathaniel C. Cady, et al.. (2024). A 65-nm RRAM Compute-in-Memory Macro for Genome Processing. IEEE Journal of Solid-State Circuits. 59(7). 2093–2104. 6 indexed citations

Krishnan, Gokul, et al.. (2024). 3-D In-Sensor Computing for Real-Time DVS Data Compression: 65-nm Hardware-Algorithm Co-Design. IEEE Solid-State Circuits Letters. 7. 119–122. 4 indexed citations

Gaidhane, Amol D., et al.. (2023). Graph-based Compact Modeling (GCM) of CMOS transistors for efficient parameter extraction: A machine learning approach. Solid-State Electronics. 201. 108580–108580. 4 indexed citations

Sun, Lijuan, Yu Cao, Xiaojie Chen, & Qing Liang. (2023). Interactions between amphiphilic nanoparticles coated with striped hydrophilic/hydrophobic ligands and a lipid bilayer. Communications in Theoretical Physics. 75(6). 65601–65601. 4 indexed citations

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

Wu, Chunlei, et al.. (2022). Ferroelectric-Gated GaN HEMTs for RF and mm-Wave Switch Applications. 1–2. 6 indexed citations

Charan, Gouranga, Karsten Beckmann, Gokul Krishnan, et al.. (2020). Accurate Inference with Inaccurate RRAM Devices: Statistical Data, Model Transfer, and On-line Adaptation. 1–6. 30 indexed citations

10.

Dai, Baomin, Shengchun Liu, Qianru Yang, et al.. (2020). Heating and cooling of residential annual application using DMS transcritical CO2 reversible system and traditional solutions: An environment and economic feasibility analysis. Energy Conversion and Management. 210. 112714–112714. 41 indexed citations

11.

Ma, Yufei, Yu Cao, Sarma Vrudhula, & Jae-sun Seo. (2019). Performance Modeling for CNN Inference Accelerators on FPGA. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 39(4). 843–856. 43 indexed citations

12.

Ma, Yufei, Yu Cao, Sarma Vrudhula, & Jae-sun Seo. (2018). Automatic Compilation of Diverse CNNs Onto High-Performance FPGA Accelerators. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 39(2). 424–437. 54 indexed citations

13.

Ma, Yufei, Yu Cao, Sarma Vrudhula, & Jae-sun Seo. (2018). Optimizing the Convolution Operation to Accelerate Deep Neural Networks on FPGA. IEEE Transactions on Very Large Scale Integration (VLSI) Systems. 26(7). 1354–1367. 247 indexed citations

14.

Salthouse, Christopher, et al.. (2018). Process Scalability of Pulse-Based Circuits for Analog Image Convolution. IEEE Transactions on Circuits and Systems I Regular Papers. 65(9). 2929–2938.

15.

Chen, Pai-Yu, Deepak Kadetotad, Zihan Xu, et al.. (2015). Technology-design co-optimization of resistive cross-point array for accelerating learning algorithms on chip. Design, Automation, and Test in Europe. 854–859. 38 indexed citations

16.

Read, Nick D., et al.. (2011). Loss resilient strategy in body sensor networks. 99–102. 1 indexed citations

17.

Cao, Yu. (2011). Calculation and improvement on amplification effect of MEMS leverage mechanism. Journal of Chinese Inertial Technology. 1 indexed citations

18.

Velamala, Jyothi, et al.. (2010). On the bias dependence of time exponent in NBTI and CHC effects. 650–654. 5 indexed citations

19.

DeBole, Michael, K. K. Ramakrishnan, Varsha Balakrishnan, et al.. (2009). A framework for estimating NBTI degradation of microarchitectural components. Asia and South Pacific Design Automation Conference. 455–460. 10 indexed citations

20.

Weiss, Paul R., et al.. (2004). Session 10: Applied technologies – II. Human Antibodies. 13(1-2). 33–37. 1 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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