World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
67
Citations
14971
World Ranking
2228
National Ranking
306

Overview

Dongrui Wu is affiliated with Huazhong University of Science and Technology in China. Their research predominantly focuses on computer science, with significant work in the subfields of artificial intelligence, cognitive neuroscience, electrical and electronic engineering, computer vision and pattern recognition, and cellular and molecular neuroscience.

The main topics covered by Dongrui Wu's work include:

  • EEG and Brain-Computer Interfaces
  • Advanced Memory and Neural Computing
  • Neuroscience and Neural Engineering
  • Neural Networks and Applications
  • Neural dynamics and brain function
  • Machine Learning and Data Classification
  • Fuzzy Logic and Control Systems

Some of their recent papers are:

  • "EEG-based Brain-Computer Interfaces (BCIs): A Survey of Recent Studies on Signal Sensing Technologies and Computational Intelligence Approaches and their Applications" (2021), published in Open Publications Of UTS Scholars (University of Technology Sydney)
  • "Transfer Learning for EEG-Based Brain-Computer Interfaces: A Review of Progress Made Since 2016" (2020), published in IEEE Transactions on Cognitive and Developmental Systems
  • "A Survey on Negative Transfer" (2022), published in IEEE/CAA Journal of Automatica Sinica
  • "Wasserstein distance based deep adversarial transfer learning for intelligent fault diagnosis with unlabeled or insufficient labeled data" (2020), published in Neurocomputing
  • "Manifold Embedded Knowledge Transfer for Brain-Computer Interfaces" (2020), published in IEEE Transactions on Neural Systems and Rehabilitation Engineering

Dongrui Wu frequently publishes in the following venues:

  • arXiv (Cornell University)
  • IEEE Transactions on Systems Man and Cybernetics Systems
  • IEEE Transactions on Neural Systems and Rehabilitation Engineering
  • IEEE Computational Intelligence Magazine
  • IEEE Transactions on Human-Machine Systems

Frequent coauthors collaborating with Dongrui Wu include:

  • Giancarlo Fortino
  • Sam Kwong
  • Karen Panetta
  • Gina Tang
  • Tiago H. Falk

Best Publications

  • Enhanced Karnik--Mendel Algorithms

    Dongrui Wu;J.M. Mendel

  • Perceptual Computing: Aiding People in Making Subjective Judgments

    Jerry Mendel;Dongrui Wu

  • Uncertainty measures for interval type-2 fuzzy sets

    Dongrui Wu;Jerry M. Mendel

  • A comparative study of ranking methods, similarity measures and uncertainty measures for interval type-2 fuzzy sets

    Dongrui Wu;Jerry M. Mendel

  • Transfer Learning for Brain–Computer Interfaces: A Euclidean Space Data Alignment Approach

    He He;Dongrui Wu

  • EEG-Based Brain-Computer Interfaces (BCIs): A Survey of Recent Studies on Signal Sensing Technologies and Computational Intelligence Approaches and Their Applications

    Xiaotong Gu;Zehong Cao;Alireza Jolfaei;Peng Xu

  • A Survey on Negative Transfer

    Unknown

  • On the Fundamental Differences Between Interval Type-2 and Type-1 Fuzzy Logic Controllers

    Dongrui Wu

  • Aggregation Using the Linguistic Weighted Average and Interval Type-2 Fuzzy Sets

    Dongrui Wu;J.M. Mendel

  • Transfer Learning for EEG-Based Brain-Computer Interfaces: A Review of Progress Made Since 2016

    Dongrui Wu;Yifan Xu;Bao-Liang Lu

  • Genetic learning and performance evaluation of interval type-2 fuzzy logic controllers

    Dongrui Wu;Woei Wan Tan

  • Approaches for Reducing the Computational Cost of Interval Type-2 Fuzzy Logic Systems: Overview and Comparisons

    Dongrui Wu

  • Comparison and practical implementation of type-reduction algorithms for type-2 fuzzy sets and systems

    Dongrui Wu;Maowen Nie

  • Wasserstein distance based deep adversarial transfer learning for intelligent fault diagnosis with unlabeled or insufficient labeled data

    Cheng Cheng;Beitong Zhou;Guijun Ma;Dongrui Wu

  • A vector similarity measure for linguistic approximation: Interval type-2 and type-1 fuzzy sets

    Dongrui Wu;Jerry M. Mendel

  • Seizure Classification From EEG Signals Using Transfer Learning, Semi-Supervised Learning and TSK Fuzzy System

    Yizhang Jiang;Dongrui Wu;Zhaohong Deng;Pengjiang Qian

  • A type-2 fuzzy logic controller for the liquid-level process

    D. Wu;W.W. Tan

  • Enhanced Interval Approach for Encoding Words Into Interval Type-2 Fuzzy Sets and Its Convergence Analysis

    Dongrui Wu;J. M. Mendel;S. Coupland

  • Interval Type-2 Fuzzy Logic Modeling and Control of a Mobile Two-Wheeled Inverted Pendulum

    Jian Huang;MyongHyok Ri;Dongrui Wu;Songhyok Ri

  • Optimal Arousal Identification and Classification for Affective Computing Using Physiological Signals: Virtual Reality Stroop Task

    Dongrui Wu;C G Courtney;B J Lance;S S Narayanan

  • Computing With Words for Hierarchical Decision Making Applied to Evaluating a Weapon System

    Dongrui Wu;Jerry M Mendel

  • Wasserstein Distance based Deep Adversarial Transfer Learning for Intelligent Fault Diagnosis.

    Cheng Cheng;Beitong Zhou;Guijun Ma;Dongrui Wu

Frequent Co-Authors

Jerry M. Mendel
Jerry M. Mendel University of Southern California
Chin-Teng Lin
Chin-Teng Lin University of Technology Sydney
Jian Huang
Jian Huang University of Iowa
Tzyy-Ping Jung
Tzyy-Ping Jung University of California, San Diego
Thomas D. Parsons
Thomas D. Parsons University of North Texas
Saeid Nahavandi
Saeid Nahavandi Swinburne University of Technology
Abbas Khosravi
Abbas Khosravi Deakin University
Shitong Wang
Shitong Wang Jiangnan University
Zhigang Zeng
Zhigang Zeng Huazhong University of Science and Technology
Hai-Tao Zhang
Hai-Tao Zhang Huazhong University of Science and Technology

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

As you consider studying Computer Science in the USA, exploring related online degrees can boost your skillset and career options. Data Science is a fast-growing field, and many students want to know what is the cheapest data science course in the us?. Affordable programs can help reduce your educational expenses while opening doors to rewarding tech roles.

If you're interested in practical, technical skills, check out the best online electrical engineering programs USA. These programs combine flexibility with in-demand expertise, making them excellent options for tech-minded students.

Time is also a major consideration. For those looking to quickly enter the workforce, 3-month certificate programs that pay well are a smart choice. These certifications offer focused, career-ready training without a long-term commitment.

Finally, if you’re eager to earn an advanced degree efficiently, there are options for the fastest masters degree online. These accelerated programs allow you to upskill and move up your career ladder in less time.

Best Scientists Citing Dongrui Wu

Trending Scientists

Recently Published Articles