World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
59
Citations
12794
World Ranking
3451
National Ranking
464

Overview

Junfei Qiao is affiliated with Beijing University of Technology in China, focusing on interdisciplinary research spanning computer science, engineering, and environmental science. Their work encompasses a range of fields with prominent contributions to artificial intelligence, control and systems engineering, and water science and technology.

Their research covers several subfields of study, including:

  • Artificial Intelligence
  • Control and Systems Engineering
  • Computational Theory and Mathematics
  • Water Science and Technology
  • Environmental Engineering

Junfei Qiao has published extensively on topics such as neural networks and applications, adaptive dynamic programming control, and advanced control systems optimization. Other key areas include machine learning and extreme learning machines (ELM), water quality monitoring technologies, fault detection and control systems, and air quality monitoring and forecasting.

Main topics of work identified are:

  • Neural Networks and Applications
  • Machine Learning and ELM
  • Adaptive Dynamic Programming Control
  • Advanced Control Systems Optimization
  • Water Quality Monitoring Technologies
  • Fault Detection and Control Systems
  • Air Quality Monitoring and Forecasting

They have contributed to numerous scholarly publications, frequently appearing in prominent venues, including:

  • IEEE Transactions on Fuzzy Systems
  • IEEE Transactions on Industrial Informatics
  • Neurocomputing
  • IEEE Transactions on Neural Networks and Learning Systems
  • IEEE Transactions on Automation Science and Engineering

Significant recent papers by Junfei Qiao include:

  • "Data-Driven Iterative Adaptive Critic Control Toward an Urban Wastewater Treatment Plant" (2020), published in IEEE Transactions on Industrial Electronics
  • "Artificial neural networks for water quality soft-sensing in wastewater treatment: a review" (2021), published in Artificial Intelligence Review
  • "Adaptive Fuzzy Fast Finite-Time Dynamic Surface Tracking Control for Nonlinear Systems" (2021), published in IEEE Transactions on Circuits and Systems I Regular Papers
  • "A multi-objective particle swarm optimization algorithm based on two-archive mechanism" (2022), published in Applied Soft Computing
  • "Deep Learning-Based Model Predictive Control for Continuous Stirred-Tank Reactor System" (2020), published in IEEE Transactions on Neural Networks and Learning Systems

Collaboration has been a significant aspect of Qiao's work. Frequent co-authors include:

  • Honggui Han
  • Ding Wang
  • Jian Tang
  • Mingming Zhao
  • Wenjing Li

The research conducted by Junfei Qiao integrates advanced computational methods and control strategies applied to environmental engineering and water treatment systems, reflecting a broad spectrum of interdisciplinary competencies.

Best Publications

  • Learning a No-Reference Quality Assessment Model of Enhanced Images With Big Data

    Ke Gu;Dacheng Tao;Jun-Fei Qiao;Weisi Lin

  • An efficient self-organizing RBF neural network for water quality prediction

    Hong-Gui Han;Qi-li Chen;Jun-Fei Qiao

  • No-Reference Quality Assessment of Screen Content Pictures

    Ke Gu;Jun Zhou;Jun-Fei Qiao;Guangtao Zhai

  • Model predictive control of dissolved oxygen concentration based on a self-organizing RBF neural network

    Hong-Gui Han;Jun-Fei Qiao;Qi-Li Chen

  • Growing Echo-State Network With Multiple Subreservoirs

    Junfei Qiao;Fanjun Li;Honggui Han;Wenjing Li

  • A Self-Organizing Fuzzy Neural Network Based on a Growing-and-Pruning Algorithm

    Honggui Han;Junfei Qiao

  • Data-Driven Iterative Adaptive Critic Control Toward an Urban Wastewater Treatment Plant

    Ding Wang;Mingming Ha;Junfei Qiao

  • Deep Dual-Channel Neural Network for Image-Based Smoke Detection

    Ke Gu;Zhifang Xia;Junfei Qiao;Weisi Lin

  • Nonlinear Model-Predictive Control for Industrial Processes: An Application to Wastewater Treatment Process

    Honggui Han;Junfei Qiao

  • Self-Learning Optimal Regulation for Discrete-Time Nonlinear Systems Under Event-Driven Formulation

    Ding Wang;Mingming Ha;Junfei Qiao

  • Nonlinear Model Predictive Control Based on a Self-Organizing Recurrent Neural Network

    Hong-Gui Han;Lu Zhang;Ying Hou;Jun-Fei Qiao

  • A multi-objective particle swarm optimization algorithm based on two-archive mechanism

    Unknown

  • Recurrent Air Quality Predictor Based on Meteorology- and Pollution-Related Factors

    Ke Gu;Junfei Qiao;Weisi Lin

  • Artificial neural networks for water quality soft-sensing in wastewater treatment: a review

    Gongming Wang;Qing Shan Jia;Meng Chu Zhou;Jing Bi

  • Model-Based Referenceless Quality Metric of 3D Synthesized Images Using Local Image Description

    Ke Gu;Vinit Jakhetiya;Jun-Fei Qiao;Xiaoli Li

  • An Adaptive-PSO-Based Self-Organizing RBF Neural Network

    Hong-Gui Han;Wei Lu;Ying Hou;Jun-Fei Qiao

  • Highly Efficient Picture-Based Prediction of PM2.5 Concentration

    Ke Gu;Junfei Qiao;Xiaoli Li

  • Adaptive fuzzy neural network control of wastewater treatment process with multiobjective operation

    Jun-Fei Qiao;Ying Hou;Lu Zhang;Hong-Gui Han

  • TL-GDBN: Growing Deep Belief Network With Transfer Learning

    GongMing Wang;JunFei Qiao;Jing Bi;WenJing Li

  • Evaluating Quality of Screen Content Images Via Structural Variation Analysis

    Ke Gu;Junfei Qiao;Xiongkuo Min;Guanghui Yue

  • Deep Learning-Based Model Predictive Control for Continuous Stirred-Tank Reactor System

    Gongming Wang;Qing-Shan Jia;Junfei Qiao;Jing Bi

  • An Adaptive Multiobjective Particle Swarm Optimization Based on Multiple Adaptive Methods

    Honggui Han;Wei Lu;Junfei Qiao

Frequent Co-Authors

Ke Gu
Ke Gu Beijing University of Technology
Weisi Lin
Weisi Lin Nanyang Technological University
Ding Wang
Ding Wang Beijing University of Technology
Wen Yu
Wen Yu CINVESTAV
Qing-Shan Jia
Qing-Shan Jia Tsinghua University
Xiaoli Li
Xiaoli Li Singapore University of Technology and Design
Xiao-Jun Zeng
Xiao-Jun Zeng University of Manchester
MengChu Zhou
MengChu Zhou New Jersey Institute of Technology
Daniel Thalmann
Daniel Thalmann École Polytechnique Fédérale de Lausanne
Tianyou Chai
Tianyou Chai Northeastern University

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