H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 98 Citations 28,854 322 World Ranking 152 National Ranking 92

Research.com Recognitions

Awards & Achievements

2018 - Member of Academia Europaea

2017 - Polish Academy of Science

2008 - Fellow of the American Association for the Advancement of Science (AAAS)

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Artificial neural network

His scientific interests lie mostly in Artificial intelligence, Artificial neural network, Wavelet, Pattern recognition and Electroencephalography. His Artificial intelligence study combines topics from a wide range of disciplines, such as Machine learning and Data mining. His research integrates issues of Mathematical optimization, Traffic engineering, Simulation and Fuzzy logic in his study of Artificial neural network.

His studies in Fuzzy logic integrate themes in fields like Algorithm, Structural engineering and Genetic algorithm. His biological study spans a wide range of topics, including Linear discriminant analysis, Correlation dimension and Signal processing. His work in the fields of Pattern recognition, such as Feature vector, intersects with other areas such as Gaussian function.

His most cited work include:

  • Analysis of EEG records in an epileptic patient using wavelet transform. (858 citations)
  • Deep convolutional neural network for the automated detection and diagnosis of seizure using EEG signals. (568 citations)
  • A Wavelet-Chaos Methodology for Analysis of EEGs and EEG Subbands to Detect Seizure and Epilepsy (528 citations)

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

Artificial intelligence, Artificial neural network, Structural engineering, Algorithm and Electroencephalography are his primary areas of study. The concepts of his Artificial intelligence study are interwoven with issues in Machine learning and Pattern recognition. His research in Artificial neural network intersects with topics in Cluster analysis, Simulation and Fuzzy logic.

His biological study spans a wide range of topics, including Vibration and Vibration control. His Algorithm study integrates concerns from other disciplines, such as Mathematical optimization and Parallel computing. His research on Electroencephalography frequently links to adjacent areas such as Epilepsy.

He most often published in these fields:

  • Artificial intelligence (21.77%)
  • Artificial neural network (16.57%)
  • Structural engineering (14.64%)

What were the highlights of his more recent work (between 2014-2021)?

  • Artificial intelligence (21.77%)
  • Electroencephalography (10.02%)
  • Algorithm (12.91%)

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

Hojjat Adeli focuses on Artificial intelligence, Electroencephalography, Algorithm, Artificial neural network and Pattern recognition. Artificial intelligence is closely attributed to Machine learning in his study. His research integrates issues of Dementia, Disease, Convolutional neural network and Epilepsy in his study of Electroencephalography.

The Algorithm study combines topics in areas such as Frequency domain, Wavelet transform and Robustness. The subject of his Wavelet transform research is within the realm of Wavelet. His Artificial neural network research is multidisciplinary, incorporating perspectives in Genetic algorithm, Cluster analysis and Fuzzy logic.

Between 2014 and 2021, his most popular works were:

  • Deep convolutional neural network for the automated detection and diagnosis of seizure using EEG signals. (568 citations)
  • Wavelet-based EEG processing for computer-aided seizure detection and epilepsy diagnosis. (263 citations)
  • Signal Processing Techniques for Vibration-Based Health Monitoring of Smart Structures (203 citations)

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

  • Artificial intelligence
  • Machine learning
  • Operating system

His main research concerns Artificial intelligence, Electroencephalography, Algorithm, Artificial neural network and Wavelet transform. His Artificial intelligence research is multidisciplinary, incorporating elements of Machine learning and Computer vision. His studies in Electroencephalography integrate themes in fields like Epilepsy, Dementia, CAD and Pattern recognition.

His Algorithm study incorporates themes from Structural system, Set, Nonlinear system, Generalization and Robustness. His Artificial neural network study combines topics from a wide range of disciplines, such as Ensemble learning, Unsupervised learning and Fuzzy logic. His Wavelet transform study is associated with Wavelet.

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

Analysis of EEG records in an epileptic patient using wavelet transform.

Hojjat Adeli;Ziqin Zhou;Nahid Dadmehr.
Journal of Neuroscience Methods (2003)

1143 Citations

A Wavelet-Chaos Methodology for Analysis of EEGs and EEG Subbands to Detect Seizure and Epilepsy

H. Adeli;S. Ghosh-Dastidar;N. Dadmehr.
IEEE Transactions on Biomedical Engineering (2007)

685 Citations

Neural Networks in Civil Engineering: 1989–2000

Hojjat Adeli.
Computer-aided Civil and Infrastructure Engineering (2001)

676 Citations

Machine Learning: Neural Networks, Genetic Algorithms, and Fuzzy Systems

Hojjat Adeli;Shih-Lin Hung.
(1994)

666 Citations

Deep convolutional neural network for the automated detection and diagnosis of seizure using EEG signals.

U. Rajendra Acharya;U. Rajendra Acharya;U. Rajendra Acharya;Shu Lih Oh;Yuki Hagiwara;Jen Hong Tan.
Computers in Biology and Medicine (2017)

547 Citations

A New Approach for Health Monitoring of Structures: Terrestrial Laser Scanning

H. S. Park;H. M. Lee;Hojjat Adeli;I. Lee.
Computer-aided Civil and Infrastructure Engineering (2007)

508 Citations

Principal Component Analysis-Enhanced Cosine Radial Basis Function Neural Network for Robust Epilepsy and Seizure Detection

S. Ghosh-Dastidar;H. Adeli;N. Dadmehr.
IEEE Transactions on Biomedical Engineering (2008)

467 Citations

Mixed-Band Wavelet-Chaos-Neural Network Methodology for Epilepsy and Epileptic Seizure Detection

S. Ghosh-Dastidar;H. Adeli;N. Dadmehr.
IEEE Transactions on Biomedical Engineering (2007)

464 Citations

Spiking neural networks.

Samanwoy Ghosh-Dastidar;Hojjat Adeli.
International Journal of Neural Systems (2009)

464 Citations

A new supervised learning algorithm for multiple spiking neural networks with application in epilepsy and seizure detection

Samanwoy Ghosh-Dastidar;Hojjat Adeli.
Neural Networks (2009)

398 Citations

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