World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
42
Citations
6547
World Ranking
8475
National Ranking
1106

Overview

Yong Qin is affiliated with Lanzhou University in China and specializes in research primarily focused on engineering and materials science. Their scholarly contributions encompass a range of studies that intersect advanced sensing technologies, energy harvesting materials, and polymer science.

The main fields of study for Yong Qin include:

  • Engineering
  • Materials Science

Within these broader fields, Yong Qin has contributed significantly to the following subfields:

  • Biomedical Engineering
  • Polymers and Plastics
  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Electronic, Optical and Magnetic Materials

The scientist's research focuses on several key topics, including:

  • Advanced Sensor and Energy Harvesting Materials
  • Conducting polymers and applications
  • Supercapacitor Materials and Fabrication
  • Innovative Energy Harvesting Technologies
  • Gas Sensing Nanomaterials and Sensors
  • Tactile and Sensory Interactions
  • Dielectric materials and actuators

Yong Qin has coauthored numerous papers with frequent collaborators such as Shuhai Liu, Qi Xu, Xiuhan Li, Suo Bai, and Juan Wen.

The scientist has published extensively in several venues. The most frequent publication outlets include:

  • Nano Energy
  • ACS Applied Materials & Interfaces
  • Nature Communications
  • SSRN Electronic Journal
  • Advanced Materials

Significant recent publications by Yong Qin include:

  • Flexoelectronics of centrosymmetric semiconductors, 2020, Nature Nanotechnology
  • Enhancing the current density of a piezoelectric nanogenerator using a three-dimensional intercalation electrode, 2020, Nature Communications
  • High performance temperature difference triboelectric nanogenerator, 2021, Nature Communications
  • Development and outlook of high output piezoelectric nanogenerators, 2021, Nano Energy
  • Highly sensitive strain sensors based on piezotronic tunneling junction, 2022, Nature Communications

Best Publications

  • Understanding and Learning Discriminant Features based on Multiattention 1DCNN for Wheelset Bearing Fault Diagnosis

    Huan Wang;Zhiliang Liu;Dandan Peng;Yong Qin

  • A Novel Deeper One-Dimensional CNN With Residual Learning for Fault Diagnosis of Wheelset Bearings in High-Speed Trains

    Dandan Peng;Zhiliang Liu;Huan Wang;Yong Qin

  • Multi-attribute group decision making models under interval type-2 fuzzy environment

    Unknown

  • A risk evaluation and prioritization method for FMEA with prospect theory and Choquet integral

    Weizhong Wang;Xinwang Liu;Yong Qin;Yong Fu

  • A simple and fast guideline for generating enhanced/squared envelope spectra from spectral coherence for bearing fault diagnosis

    Dong Wang;Dong Wang;Xuejun Zhao;Lin-Lin Kou;Yong Qin

  • Traffic zone division based on big data from mobile phone base stations

    Honghui Dong;Mingchao Wu;Xiaoqing Ding;Lianyu Chu

  • Real-time road traffic state prediction based on ARIMA and Kalman filter

    Dong-wei Xu;Yong-dong Wang;Li-min Jia;Yong Qin

  • Hybrid deep learning architecture for rail surface segmentation and surface defect detection

    Yunpeng Wu;Yunpeng Wu;Yong Qin;Yu Qian;Feng Guo

  • Feature-Level Attention-Guided Multitask CNN for Fault Diagnosis and Working Conditions Identification of Rolling Bearing.

    Huan Wang;Zhiliang Liu;Dandan Peng;Mei Yang

  • Multitask Learning Based on Lightweight 1DCNN for Fault Diagnosis of Wheelset Bearings

    Zhiliang Liu;Huan Wang;Junjie Liu;Yong Qin

  • Short-Term Abnormal Passenger Flow Prediction Based on the Fusion of SVR and LSTM

    Jianyuan Guo;Zhen Xie;Yong Qin;Limin Jia

  • A UAV-Based Visual Inspection Method for Rail Surface Defects

    Yunpeng Wu;Yong Qin;Zhipeng Wang;Limin Jia

  • Improved Hilbert-Huang transform with soft sifting stopping criterion and its application to fault diagnosis of wheelset bearings.

    Zhiliang Liu;Dandan Peng;Ming J. Zuo;Ming J. Zuo;Jianshuo Xia

  • Self-powered triboelectric nano vibration accelerometer based wireless sensor system for railway state health monitoring

    Xuejun Zhao;Guowu Wei;Xiuhan Li;Yong Qin

  • Optimal Number and Location Planning of Evacuation Signage in Public Space

    Zhe Zhang;Limin Jia;Yong Qin

  • A fuzzy Fine-Kinney-based risk evaluation approach with extended MULTIMOORA method based on Choquet integral

    Weizhong Wang;Xinwang Liu;Yong Qin

  • Remaining useful life prediction of rolling element bearings based on health state assessment

    Zhiliang Liu;Zhiliang Liu;Ming J Zuo;Ming J Zuo;Yong Qin

  • Automatic bearing fault diagnosis using particle swarm clustering and Hidden Markov Model

    Mitchell Yuwono;Yong Qin;Jing Zhou;Ying Guo

  • Interval-valued intuitionistic fuzzy aggregation operators

    Unknown

  • UAV imagery based potential safety hazard evaluation for high-speed railroad using Real-time instance segmentation

    Unknown

  • Roller bearing safety region estimation and state identification based on LMD–PCA–LSSVM

    Yuan Zhang;Yong Qin;Zong-yi Xing;Li-min Jia

  • Optimization of segmentation fragments in empirical wavelet transform and its applications to extracting industrial bearing fault features

    Dong Wang;Dong Wang;Kwok-Leung Tsui;Yong Qin

  • Risk assessment based on hybrid FMEA framework by considering decision maker’s psychological behavior character

    Weizhong Wang;Xinwang Liu;Xiaoqing Chen;Yong Qin

Frequent Co-Authors

Limin Jia
Limin Jia Beijing Jiaotong University
Ming J. Zuo
Ming J. Zuo University of Alberta
Dong Wang
Dong Wang Shanghai Jiao Tong University
Kwok-Leung Tsui
Kwok-Leung Tsui Virginia Tech
Xuesong Zhou
Xuesong Zhou Arizona State University
Yang Zhao
Yang Zhao Beijing Institute of Technology
Ruisi He
Ruisi He Beijing Jiaotong University
Klaus Bengler
Klaus Bengler Technical University of Munich

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