D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Electronics and Electrical Engineering D-index 30 Citations 3,835 154 World Ranking 3714 National Ranking 438

Overview

What is he best known for?

The fields of study he is best known for:

  • Electrical engineering
  • Semiconductor
  • Artificial intelligence

His scientific interests lie mostly in Resistive random-access memory, Optoelectronics, Neuromorphic engineering, Nanotechnology and Artificial neural network. His Resistive random-access memory research is multidisciplinary, incorporating elements of Resistor, Non-volatile memory, Electronic engineering and Efficient energy use. The various areas that He Qian examines in his Optoelectronics study include Layer and Electrical engineering, Voltage.

He Qian interconnects Computer hardware, Converters, Convolutional neural network and Modulation in the investigation of issues within Neuromorphic engineering. His work on Graphene as part of his general Nanotechnology study is frequently connected to Current density, thereby bridging the divide between different branches of science. His Artificial neural network research is multidisciplinary, relying on both Memristor and Task.

His most cited work include:

  • Face classification using electronic synapses (347 citations)
  • Fully hardware-implemented memristor convolutional neural network. (185 citations)
  • Binary neural network with 16 Mb RRAM macro chip for classification and online training (107 citations)

What are the main themes of his work throughout his whole career to date?

He Qian spends much of his time researching Resistive random-access memory, Electronic engineering, Optoelectronics, Neuromorphic engineering and Artificial neural network. His research in Resistive random-access memory intersects with topics in Chip, Resistive switching and Reliability. His work on CMOS as part of general Electronic engineering study is frequently linked to Physical unclonable function and Process, bridging the gap between disciplines.

His Optoelectronics research is multidisciplinary, relying on both Layer, Nanotechnology, Graphene and Transistor. In his study, Signal processing is inextricably linked to Memristor, which falls within the broad field of Neuromorphic engineering. His work deals with themes such as Computer hardware and Nonlinear system, which intersect with Artificial neural network.

He most often published in these fields:

  • Resistive random-access memory (48.76%)
  • Electronic engineering (32.23%)
  • Optoelectronics (30.99%)

What were the highlights of his more recent work (between 2019-2021)?

  • Resistive random-access memory (48.76%)
  • Electronic engineering (32.23%)
  • Artificial neural network (15.70%)

In recent papers he was focusing on the following fields of study:

He Qian mainly focuses on Resistive random-access memory, Electronic engineering, Artificial neural network, Neuromorphic engineering and Memristor. He Qian has researched Resistive random-access memory in several fields, including Relaxation effect, Chip, Hardware security module, Computation and Reliability. His Electronic engineering research includes elements of Capacitance and Analog computer.

His Artificial neural network research incorporates themes from Temperature coefficient, Computer hardware, Efficient energy use and Nonlinear system. He Qian combines subjects such as Crossbar switch, Optoelectronics, Voltage, Conductance and Resistive touchscreen with his study of Neuromorphic engineering. His Optoelectronics study integrates concerns from other disciplines, such as Layer and Transistor.

Between 2019 and 2021, his most popular works were:

  • Fully hardware-implemented memristor convolutional neural network. (185 citations)
  • Reliability of analog resistive switching memory for neuromorphic computing (40 citations)
  • Neuro-inspired computing chips (32 citations)

In his most recent research, the most cited papers focused on:

  • Electrical engineering
  • Semiconductor
  • Integrated circuit

His primary areas of investigation include Electronic engineering, Artificial neural network, Neuromorphic engineering, Memristor and Resistive random-access memory. His Electronic engineering study incorporates themes from Reliability, Efficient energy use, Computer data storage and Analog computer. His work in the fields of Spiking neural network overlaps with other areas such as Benchmarking.

His work focuses on many connections between Neuromorphic engineering and other disciplines, such as Crossbar switch, that overlap with his field of interest in Optoelectronics, Nanodot, Fast switching and Computer hardware. His work in Memristor tackles topics such as Signal processing which are related to areas like Electrical efficiency and CMOS. His Resistive random-access memory study combines topics in areas such as Memory chip and Nonlinear system.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Face classification using electronic synapses

Peng Yao;Huaqiang Wu;Bin Gao;Sukru Burc Eryilmaz.
Nature Communications (2017)

422 Citations

Fully hardware-implemented memristor convolutional neural network.

Peng Yao;Huaqiang Wu;Bin Gao;Jianshi Tang.
Nature (2020)

227 Citations

Synthesis and characterization of vertically standing MoS2 nanosheets.

Han Li;Huaqiang Wu;Shuoguo Yuan;He Qian.
Scientific Reports (2016)

162 Citations

Binary neural network with 16 Mb RRAM macro chip for classification and online training

Shimeng Yu;Zhiwei Li;Pai-Yu Chen;Huaqiang Wu.
international electron devices meeting (2016)

140 Citations

Bridging Biological and Artificial Neural Networks with Emerging Neuromorphic Devices: Fundamentals, Progress, and Challenges.

Jianshi Tang;Fang Yuan;Xinke Shen;Zhongrui Wang.
Advanced Materials (2019)

118 Citations

Improving Analog Switching in HfO x -Based Resistive Memory With a Thermal Enhanced Layer

Wei Wu;Huaqiang Wu;Bin Gao;Ning Deng.
IEEE Electron Device Letters (2017)

111 Citations

Metallic to hopping conduction transition in Ta2O5−x/TaOy resistive switching device

Ye Zhang;Ning Deng;Huaqiang Wu;Zhiping Yu.
Applied Physics Letters (2014)

101 Citations

Study of conduction and switching mechanisms in Al/AlOx/WOx/W resistive switching memory for multilevel applications

Ye Zhang;Huaqiang Wu;Yue Bai;An Chen.
Applied Physics Letters (2013)

99 Citations

Study of Multi-level Characteristics for 3D Vertical Resistive Switching Memory

Yue Bai;Huaqiang Wu;Riga Wu;Ye Zhang.
Scientific Reports (2015)

92 Citations

Experimental Characterization of Physical Unclonable Function Based on 1 kb Resistive Random Access Memory Arrays

Rui Liu;Huaqiang Wu;Yachuan Pang;He Qian.
IEEE Electron Device Letters (2015)

89 Citations

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