World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
96
Citations
37010
World Ranking
227
National Ranking
114

Yu Cao publication distribution in Electronics and Electrical Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Electronics and Electrical Engineering in 2026. The highlighted bar marks where Yu Cao sits on this spectrum.

34–53 publications: 24 scientists 54–73 publications: 52 scientists 74–93 publications: 114 scientists 94–113 publications: 203 scientists 114–133 publications: 269 scientists 134–153 publications: 355 scientists 154–173 publications: 403 scientists 174–193 publications: 445 scientists 194–213 publications: 430 scientists 214–233 publications: 431 scientists 234–253 publications: 399 scientists 254–273 publications: 366 scientists 274–293 publications: 335 scientists 294–313 publications: 300 scientists 314–333 publications: 276 scientists 334–353 publications: 250 scientists 354–373 publications: 214 scientists 374–393 publications: 187 scientists 394–413 publications: 152 scientists 414–433 publications: 169 scientists 434–453 publications: 147 scientists 454–473 publications: 111 scientists 474–493 publications: 117 scientists 494–513 publications: 103 scientists 514–533 publications: 99 scientists 534–553 publications: 92 scientists 554–573 publications: 75 scientists 574–593 publications: 58 scientists 594–613 publications: 69 scientists 614–633 publications: 50 scientists 634–653 publications: 62 scientists 654–673 publications: 54 scientists 674–693 publications: 44 scientists 694–713 publications: 37 scientists 714–733 publications: 28 scientists 734–753 publications: 26 scientists 754–773 publications: 26 scientists 774–793 publications: 19 scientists 794–813 publications: 23 scientists 814–833 publications: 20 scientists 834–853 publications: 16 scientists 854–873 publications: 20 scientists 874–893 publications: 11 scientists 894–913 publications: 11 scientists 914–933 publications: 16 scientists 934–953 publications: 13 scientists 954–973 publications: 10 scientists 974–993 publications: 11 scientists 994–1,013 publications: 9 scientists 1,014–1,033 publications: 9 scientists 1,034–1,053 publications: 10 scientists 1,054–1,064 publications: 6 scientists 1,065+ publications: 99 scientists
34 publications 1,065+

This scientist: 875 publications — 97th percentile

97% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,065 publications or more.

Yu Cao D-index placement in Electronics and Electrical Engineering in 2026

The chart shows the D-index (discipline H-index) distribution of Electronics and Electrical Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Yu Cao sits on this spectrum.

30 D-Index: 178 scientists 31 D-Index: 257 scientists 32 D-Index: 263 scientists 33 D-Index: 262 scientists 34 D-Index: 244 scientists 35 D-Index: 236 scientists 36 D-Index: 211 scientists 37 D-Index: 220 scientists 38 D-Index: 214 scientists 39 D-Index: 214 scientists 40 D-Index: 205 scientists 41 D-Index: 187 scientists 42 D-Index: 194 scientists 43 D-Index: 201 scientists 44 D-Index: 155 scientists 45 D-Index: 189 scientists 46 D-Index: 148 scientists 47 D-Index: 160 scientists 48 D-Index: 134 scientists 49 D-Index: 130 scientists 50 D-Index: 141 scientists 51 D-Index: 156 scientists 52 D-Index: 108 scientists 53 D-Index: 130 scientists 54 D-Index: 112 scientists 55 D-Index: 97 scientists 56 D-Index: 111 scientists 57 D-Index: 102 scientists 58 D-Index: 108 scientists 59 D-Index: 120 scientists 60 D-Index: 103 scientists 61 D-Index: 93 scientists 62 D-Index: 92 scientists 63 D-Index: 74 scientists 64 D-Index: 77 scientists 65 D-Index: 73 scientists 66 D-Index: 64 scientists 67 D-Index: 69 scientists 68 D-Index: 60 scientists 69 D-Index: 39 scientists 70 D-Index: 57 scientists 71 D-Index: 59 scientists 72 D-Index: 46 scientists 73 D-Index: 49 scientists 74 D-Index: 38 scientists 75 D-Index: 35 scientists 76 D-Index: 32 scientists 77 D-Index: 35 scientists 78 D-Index: 31 scientists 79 D-Index: 22 scientists 80 D-Index: 34 scientists 81 D-Index: 31 scientists 82 D-Index: 34 scientists 83 D-Index: 23 scientists 84 D-Index: 18 scientists 85 D-Index: 30 scientists 86 D-Index: 19 scientists 87 D-Index: 19 scientists 88 D-Index: 20 scientists 89 D-Index: 8 scientists 90 D-Index: 17 scientists 91 D-Index: 7 scientists 92 D-Index: 14 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 12 scientists 97 D-Index: 10 scientists 98 D-Index: 10 scientists 99 D-Index: 12 scientists 100 D-Index: 16 scientists 101 D-Index: 5 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 8 scientists 105 D-Index: 9 scientists 106 D-Index: 13 scientists 107 D-Index: 4 scientists 108 D-Index: 5 scientists 109 D-Index: 10 scientists 110 D-Index: 8 scientists 111+ D-Index: 96 scientists
30 D-Index 111+

This scientist: 96 D-Index — 97th percentile

97% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 111 D-Index or more.

Overview

Yu Cao is affiliated with the University of Minnesota in the United States and has contributed extensively to the fields of engineering and computer science. Their research spans multiple subfields including biomedical engineering, computer vision and pattern recognition, control and systems engineering, electrical and electronic engineering, and artificial intelligence.

The researcher's recent papers cover a range of topics primarily focused on control systems, robotics, and neural network applications. Notable publications include:

  • Neural-network-based nonlinear model predictive tracking control of a pneumatic muscle actuator-driven exoskeleton, 2020, IEEE/CAA Journal of Automatica Sinica
  • Adaptive Proxy-Based Robust Control Integrated With Nonlinear Disturbance Observer for Pneumatic Muscle Actuators, 2020, IEEE/ASME Transactions on Mechatronics
  • A Model-agnostic Data Manipulation Method for Persona-based Dialogue Generation, 2022, Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Yu Cao's research interests include prosthetics and rehabilitation robotics, advanced neural network applications, muscle activation and electromyography studies, adaptive control of nonlinear systems, soft robotics and applications, optical imaging and spectroscopy techniques, and electrical and bioimpedance tomography.

The author has published frequently in the following venues:

  • arXiv (Cornell University)
  • IEEE/ASME Transactions on Mechatronics
  • Remote Sensing
  • ISA Transactions
  • IEEE Transactions on Cognitive and Developmental Systems

Collaborations have been an important aspect of Yu Cao's research, with frequent co-authors including Jian Huang, Mengshi Zhang, Caihua Xiong, Jindong Liu, and Dongrui Wu. These partnerships have contributed to a broad output across multiple domains of engineering and computer science.

Best Publications

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

    Wei Zhao;Yu Cao

  • CrackTree: Automatic crack detection from pavement images

    Qin Zou;Yu Cao;Qingquan Li;Qingzhou Mao

  • New paradigm of predictive MOSFET and interconnect modeling for early circuit simulation

    Y. Cao;T. Sato;M. Orshansky;D. Sylvester

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

    Wei Zhao;Yu Cao

  • Throughput-Optimized OpenCL-based FPGA Accelerator for Large-Scale Convolutional Neural Networks

    Naveen Suda;Vikas Chandra;Ganesh Dasika;Abinash Mohanty

  • Modeling and minimization of PMOS NBTI effect for robust nanometer design

    Rakesh Vattikonda;Wenping Wang;Yu Cao

  • Flexible Hybrid Electronics for Digital Healthcare.

    Yinji Ma;Yingchao Zhang;Shisheng Cai;Zhiyuan Han

  • Frequency-independent equivalent-circuit model for on-chip spiral inductors

    Yu Cao;R.A. Groves;Xuejue Huang;N.D. Zamdmer

  • Predictive Modeling of the NBTI Effect for Reliable Design

    S. Bhardwaj;Wenping Wang;R. Vattikonda;Y. Cao

  • Cooperative mobile robotics: antecedents and directions

    Y.U. Cao;A.S. Fukunaga;A.B. Kahng;F. Meng

  • Compact Modeling and Simulation of Circuit Reliability for 65-nm CMOS Technology

    Wenping Wang;V. Reddy;A.T. Krishnan;R. Vattikonda

  • Frequency-independent equivalent circuit model for on-chip spiral inductors

    Yu Cao;R.A. Groves;N.D. Zamdmer;J.-O. Plouchart

  • Switch-mediated activation and retargeting of CAR-T cells for B-cell malignancies

    David T. Rodgers;Magdalena Mazagova;Eric N. Hampton;Yu Cao

  • Optimizing Loop Operation and Dataflow in FPGA Acceleration of Deep Convolutional Neural Networks

    Yufei Ma;Yu Cao;Sarma Vrudhula;Jae-sun Seo

  • Minimising efficiency roll-off in high-brightness perovskite light-emitting diodes.

    Wei Zou;Renzhi Li;Shuting Zhang;Yunlong Liu;Yunlong Liu

  • Mapping Statistical Process Variations Toward Circuit Performance Variability: An Analytical Modeling Approach

    Yu Cao;L.T. Clark

  • Exploring sub-20nm FinFET design with predictive technology models

    Saurabh Sinha;Greg Yeric;Vikas Chandra;Brian Cline

  • The Impact of NBTI Effect on Combinational Circuit: Modeling, Simulation, and Analysis

    Wenping Wang;Shengqi Yang;S. Bhardwaj;S. Vrudhula

  • Hybrid structure of zinc oxide nanorods and three dimensional graphene foam for supercapacitor and electrochemical sensor applications

    Xiaochen Dong;Yunfa Cao;Jing Wang;Mary B. Chan-Park

  • Optimizing the Convolution Operation to Accelerate Deep Neural Networks on FPGA

    Yufei Ma;Yu Cao;Sarma Vrudhula;Jae-sun Seo

  • DeepFood: Deep Learning-Based Food Image Recognition for Computer-Aided Dietary Assessment

    Chang Liu;Yu Cao;Yan Luo;Guanling Chen

  • A New Deep Learning-Based Food Recognition System for Dietary Assessment on An Edge Computing Service Infrastructure

    Chang Liu;Yu Cao;Yan Luo;Guanling Chen

Frequent Co-Authors

Jae-sun Seo
Jae-sun Seo Cornell University
Sarma Vrudhula
Sarma Vrudhula Arizona State University
Shimeng Yu
Shimeng Yu Georgia Institute of Technology
Benyuan Liu
Benyuan Liu University of Massachusetts Lowell
Chenming Hu
Chenming Hu University of California, Berkeley
Chaitali Chakrabarti
Chaitali Chakrabarti Arizona State University
Dennis Sylvester
Dennis Sylvester University of Michigan–Ann Arbor
Peter G. Schultz
Peter G. Schultz Scripps Research Institute
Pai-Yu Chen
Pai-Yu Chen Arizona State University
Chongwu Zhou
Chongwu Zhou University of Southern California

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Related Online Degrees & Career Pathways

For those interested in pursuing Electronics and Electrical Engineering, exploring flexible online options can be highly beneficial. Many learners opt for competency based masters degrees, which allow students to progress by demonstrating skills rather than relying solely on traditional coursework. This approach is especially helpful for those balancing work and study commitments.

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Time-sensitive students might find value in online colleges that start soon, which provide multiple enrollment opportunities throughout the year. This continuous intake process ensures prospective engineers can commence their studies without waiting for traditional semester start dates.

Additionally, pursuing short term certificate programs can serve as a quick, focused way to gain industry-relevant skills, boosting employability in a shorter timeframe. These certificates often complement traditional degrees and support career advancement in specialized areas within electrical and electronics engineering.

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