Google Scholar | ORCID.
A BibTeX file with all publications below.

Peer-Reviewed Papers


  • Haytham M. Fayek, Lawrence Cavedon, and Hong Ren Wu.
    On the transferability of representations in neural networks between datasets and tasks.
    Continual Learning Workshop, 32nd Neural Information Processing Systems (NeurIPS 2018), Montréal, Canada, Dec 2018.
    pdf arXiv bib


  • Haytham M. Fayek.
    MatDL: A lightweight deep learning library in MATLAB.
    The Journal of Open Source Software, vol. 2, no. 19, pp. 413, Nov 2017.
    pdf code url bib

  • Haytham M. Fayek, Laurens van der Maaten, Griffin D. Romigh, and Ravish Mehra.
    On data-driven approaches to head-related transfer function personalization.
    In Audio Engineering Society (AES) Convention 143, New York, USA, Oct 2017.
    pdf url bib

  • Haytham M. Fayek, Margaret Lech, and Lawrence Cavedon.
    Evaluating deep learning architectures for speech emotion recognition.
    Neural Networks, vol. 92, pp. 60–68, Aug 2017.
    url bib


  • Haytham M. Fayek.
    A deep learning framework for hybrid linguistic-paralinguistic speech systems.
    In 2nd Doctoral Consortium at Interspeech, Berkeley, USA, Sep 2016.
    pdf url bib

  • Haytham M. Fayek, Margaret Lech, and Lawrence Cavedon.
    On the correlation and transferability of features between automatic speech recognition and speech emotion recognition.
    In 17th Annual Conference of the International Speech Communication Association (Interspeech), San Francisco, USA, pp. 3618–3622, Sep 2016.
    pdf url slides bib

  • Haytham M. Fayek, Margaret Lech, and Lawrence Cavedon.
    Modeling subjectiveness in emotion recognition with deep neural networks: Ensembles vs soft labels.
    In International Joint Conference on Neural Networks (IJCNN), Vancouver, Canada, pp. 566–570, Jul 2016.
    url poster bib


  • Haytham M. Fayek, Margaret Lech, and Lawrence Cavedon.
    Towards real-time speech emotion recognition using deep neural networks.
    In 9th International Conference on Signal Processing and Communication Systems (ICSPCS), Cairns, Australia, pp. 1–5, Dec 2015.
    url bib


  • P. N. Q. Nhon, Irraivan Elamvazuthi, Haytham M. Fayek, S. Parasuraman, and M.K.A. Ahamed Khan.
    Intelligent control of rehabilitation robot: Auto tuning PID controller with interval type 2 fuzzy for DC servomotor.
    Procedia Computer Science, vol. 42, Medical and Rehabilitation Robotics and Instrumentation (MRRI2013), pp. 183–190, Dec 2014.
    url bib

  • Haytham M. Fayek, Irraivan Elamvazuthi, N. Perumal, and Bala Venkatesh.
    A controller based on optimal type-2 fuzzy logic: Systematic design, optimization and real-time implementation.
    ISA Transactions, vol. 53(5), pp. 1583–1591, Sep 2014.
    url bib

  • Haytham M. Fayek, Irraivan Elamvazuthi, N. Perumal, and Bala Venkatesh.
    The impact of DFIG and FSIG wind farms on the small signal stability of a power system.
    In 5th International Conference on Intelligent and Advanced Systems (ICIAS), Kuala Lumpur, Malaysia, pp. 1–6, Jun 2014.
    url slides bib


  • Haytham M. Fayek and Irraivan Elamvazuthi.
    Real-time implementation of a type-2 fuzzy logic controller to control a DC servomotor with different defuzzification methods.
    In 18th International Conference on Methods and Models in Automation and Robotics (MMAR), Miedzyzdroje, Poland, pp. 86–91, Aug 2013.
    url bib (Runner up Best Young Author)


  • Haytham M. Fayek and Irraivan Elamvazuthi.
    Type-2 fuzzy logic PI (T2FLPI) based DC servomotor control.
    Journal of Applied Sciences Research, vol. 8(5), pp. 2564–-2574, 2012.
    pdf bib


  • Haytham M. Fayek.
    Continual deep learning via progressive learning.
    PhD Thesis, RMIT University, 2019.
    pdf url bib

  • Haytham M. Fayek.
    Systematic design Of optimal type II fuzzy logic controllers with applications to wind power.
    MSc Thesis, Petronas University, 2014.

  • Haytham M. Fayek.
    Fuzzy logic based motor control.
    BEng Thesis, Petronas University, 2012.


  • Irraivan Elamvazuthi and Haytham M. Fayek.
    Method for controlling a high speed DC servomotor that controls a robotic arm for the PCB industry (FT2RC).
    Patent Filing No. PI2012700978, Nov 2012.