World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
41
Citations
4449
World Ranking
9002
National Ranking
277

Overview

Zehong Cao is affiliated with the University of South Australia in Australia. The primary fields of study for this researcher include Computer Science and Neuroscience, with a substantial focus on Cognitive Neuroscience and Artificial Intelligence as subfields. Their scientific contributions integrate topics such as EEG and Brain-Computer Interfaces, neural dynamics and brain function, and functional brain connectivity studies.

The researcher has published extensively across well-recognized venues. Frequent publication outlets include arXiv (Cornell University), IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Fuzzy Systems, Information Sciences, and IEEE Transactions on Neural Systems and Rehabilitation Engineering.

Zehong Cao's collaborative network features frequent co-authors, including Chin-Teng Lin, Fali Li, Peng Xu, Feng Shi, and Dinggang Shen. These co-authors have contributed to a variety of projects, demonstrating an interdisciplinary approach that spans neural engineering, fuzzy logic, and decision-making systems.

Recent publications highlight a range of research topics. Notable papers include:

  • EEG-based Brain-Computer Interfaces (BCIs): A Survey of Recent Studies on Signal Sensing Technologies and Computational Intelligence Approaches and their Applications, 2021, Open Publications Of UTS Scholars (University of Technology Sydney)
  • A Novel Conflict Measurement in Decision-Making and Its Application in Fault Diagnosis, 2020, IEEE Transactions on Fuzzy Systems
  • Attribute reduction with fuzzy rough self-information measures, 2020, Information Sciences
  • A Reinforcement Learning-Based Vehicle Platoon Control Strategy for Reducing Energy Consumption in Traffic Oscillations, 2021, IEEE Transactions on Neural Networks and Learning Systems
  • Seizure Prediction Using Directed Transfer Function and Convolution Neural Network on Intracranial EEG, 2020, IEEE Transactions on Neural Systems and Rehabilitation Engineering

The scientist's research topics cover diverse areas including multi-criteria decision making, rough sets and fuzzy logic, traffic control and management, and neural networks and applications. These topics reflect a blend of computational intelligence methods and their applications in neuroscience and engineering domains.

Best Publications

  • 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

  • Multi-channel EEG recordings during a sustained-attention driving task.

    Zehong Cao;Chun-Hsiang Chuang;Jung-Kai King;Chin-Teng Lin

  • Real-time detection of gene expression in cancer cells using molecular beacon imaging: new strategies for cancer research.

    Xiang-Hong Peng;Ze-Hong Cao;Jin-Tang Xia;Grant W. Carlson

  • Inherent Fuzzy Entropy for the Improvement of EEG Complexity Evaluation

    Zehong Cao;Chin-Teng Lin

  • A Novel Conflict Measurement in Decision-Making and Its Application in Fault Diagnosis

    Fuyuan Xiao;Zehong Cao;Alireza Jolfaei

  • Attribute reduction with fuzzy rough self-information measures

    Changzhong Wang;Yang Huang;Weiping Ding;Zehong Cao;Zehong Cao

  • Cloud-Assisted Multiview Video Summarization Using CNN and Bidirectional LSTM

    Tanveer Hussain;Khan Muhammad;Amin Ullah;Zehong Cao

  • A Complex Weighted Discounting Multisource Information Fusion With its Application in Pattern Classification

    Unknown

  • Development of Receptor Targeted Magnetic Iron Oxide Nanoparticles for Efficient Drug Delivery and Tumor Imaging.

    Lily Yang;Zehong Cao;Hari Krishna Sajja;Hui Mao

  • A Reinforcement Learning-Based Vehicle Platoon Control Strategy for Reducing Energy Consumption in Traffic Oscillations.

    Meng Li;Zehong Cao;Zhibin Li

  • Extraction of SSVEPs-Based Inherent Fuzzy Entropy Using a Wearable Headband EEG in Migraine Patients

    Zehong Cao;Chin-Teng Lin;Kuan-Lin Lai;Li-Wei Ko

  • Seizure Prediction Using Directed Transfer Function and Convolution Neural Network on Intracranial EEG

    Gang Wang;Dong Wang;Changwang Du;Kuo Li

  • Effects of repetitive SSVEPs on EEG complexity using multiscale inherent fuzzy entropy

    Zehong Cao;Weiping Ding;Yu-Kai Wang;Farookh Khadeer Hussain

  • Deep Neuro-Cognitive Co-Evolution for Fuzzy Attribute Reduction by Quantum Leaping PSO With Nearest-Neighbor Memeplexes

    Weiping Ding;Chin-Teng Lin;Zehong Cao

  • uPAR-targeted optical imaging contrasts as theranostic agents for tumor margin detection.

    Lily Yang;Hari Krishna Sajja;Zehong Cao;Wei Ping Qian

  • An interval-valued Pythagorean prioritized operator-based game theoretical framework with its applications in multicriteria group decision making

    Yuzhen Han;Yuzhen Han;Yong Deng;Yong Deng;Zehong Cao;Zehong Cao;Chin-Teng Lin

  • Reliability of EEG microstate analysis at different electrode densities during propofol-induced transitions of brain states

    Kexu Zhang;Wen Shi;Chang Wang;Yamin Li

  • A review of artificial intelligence for EEG‐based brain−computer interfaces and applications:

    Zehong Cao

  • Predicting individual decision-making responses based on single-trial EEG

    Yajing Si;Fali Li;Keyi Duan;Qin Tao

  • A Fuzzy Interval Time-Series Energy and Financial Forecasting Model Using Network-Based Multiple Time-Frequency Spaces and the Induced-Ordered Weighted Averaging Aggregation Operation

    Gang Liu;Fuyuan Xiao;Chin-Teng Lin;Zehong Cao

  • Enhancing Transferability of Deep Reinforcement Learning-Based Variable Speed Limit Control Using Transfer Learning

    Zemian Ke;Zhibin Li;Zehong Cao;Pan Liu

  • Multigranulation Supertrust Model for Attribute Reduction

    Weiping Ding;Witold Pedrycz;Isaac Triguero;Zehong Cao

  • A fuzzy preference-based Dempster-Shafer evidence theory for decision fusion

    Chaosheng Zhu;Bowen Qin;Fuyuan Xiao;Zehong Cao

  • A Layered-Coevolution-Based Attribute-Boosted Reduction Using Adaptive Quantum-Behavior PSO and Its Consistent Segmentation for Neonates Brain Tissue

    Weiping Ding;Chin-Teng Lin;Mukesh Prasad;Zehong Cao

Frequent Co-Authors

Chin-Teng Lin
Chin-Teng Lin University of Technology Sydney
Weiping Ding
Weiping Ding Nantong University
Shuming Nie
Shuming Nie University of Illinois at Urbana-Champaign
Alireza Jolfaei
Alireza Jolfaei Flinders University
Dezhong Yao
Dezhong Yao University of Electronic Science and Technology of China
Nikhil R. Pal
Nikhil R. Pal Indian Statistical Institute
Shuu-Jiun Wang
Shuu-Jiun Wang National Yang Ming Chiao Tung University
Peng Xu
Peng Xu Chinese Academy of Sciences
Xinge You
Xinge You Huazhong University of Science and Technology
Xiaohu Gao
Xiaohu Gao University of Washington

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

If you’re exploring Computer Science education in the USA, online degree programs offer significant flexibility and value. For those looking to quickly advance their education, consider the quickest cheapest masters degree options, which can help you save both time and money while boosting your qualifications.

Computer Science is also listed among the most in demand masters degrees, making it a smart choice for those aiming for strong job prospects and higher earnings in tech-driven careers.

If you’re not ready for a master’s program, an associates degree online is a great stepping stone. It allows you to enter the tech workforce sooner or transfer to a bachelor’s program later.

Budget-conscious learners can also explore affordable online colleges, which provide accredited Computer Science degrees without the high tuition costs. These pathways collectively support various career ambitions—whether you’re starting out or advancing in the field.

Best Scientists Citing Zehong Cao

Trending Scientists