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PUBLICATIONS

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In total, over 400 publications were published for the last 30 years. These include:

  • 3 monographs, which set new directions of research

  • over 120 peer reviewed journal papers mostly with high impact factor, e.g. TPAMI, Information Fusion, IEEE TCYB, IEEE TFS, etc

  • over 160 papers in peer reviewed proceedings of international conferences (at conferences such as CVPR, ICCV, ECCV, ICLR, IJCNN, etc.)

  • 5 edited books

  • 18 conference proceedings published as edited volumes

  • 27 chapters in books

  • 6 filed patents (3 granted in USA), etc.

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These publications attracted over 16300+ citations (according to Google Scholar), h-index 64 (i-10 index 217).

He is international leader in AI area ((in the top 1% of researchers in AI world-wide, he features in the Stanford University study (Ioannidis J. P. A., Boyack K. W., Baas J. (2020) Updated science-wide author databases of standardized citation indicators. PLoS Biol 18(10): e3000918. doi:10.1371/journal.pbio.3000918 as well as in Research.com, where his record is).  

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Topic-wise, the publications can be separated in the following categories (the symbol ‘*’ denotes a research topics introduced by Prof. Angelov; the symbol ‘†’ denotes a research topic for which Dr. Angelov is one of the first few who introduced it world-wide):

  • * Explainable deep rule-base classifiers, semi-supervised learning

  • Explainable deep learning

  • * Empirical data analytics

  • † Autonomous learning systems 

    • * Self-evolving fuzzy rule-based classifiers

    • † Dynamically self-evolving predictive neuro-fuzzy models with proven convergence and local optimality

    • * Autonomous fault detection and identification/anomaly detection 

    • † Dynamically evolving clustering

    • * Dynamically self-evolving controllers

    • Drift detection, stability, correntropy analysis

  • * New direction aware distance metric

  • Applications:

    • Flood detection and Earth Observation

    • (Lithium-ion) electric batteries degradation modelling 

    • Covid-19 and SARS-CoV2

    • Autonomous driving

    • Autonomous aerial systems

    • * Evolving human behaviour modelling

    • * eSensor

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