Dr Hossam FRAIHAT

Associate Researcher
Dr. Hossam FRAIHAT

Biography

Hossam FRAIHAT, a research associate at aivancity, is a lecturer in artificial intelligence and computer networks, and holds a PhD in signal processing, imaging and robotics from the University of Paris-Est. He teaches at La Salle Passy Buzenval and at the CFA; he was an assistant professor in the Department of Electrical Engineering at Al-Ahliyya University in Amman, Jordan; and he conducts research into AI applied to computer vision, biomedical signals and energy forecasting. He is the author of several publications in Scopus-indexed international journals (Q1/Q2), notably in journals such as *Future Internet*, *MDPI* and *IEEE Access*.

Education & Qualifications

YearUniversityQualification/Position
2017University of Paris-Est PhD in Signals, Images and Robotics
2010 University of Nantes Master’s 2: Design of Electronic and Optoelectronic Components

Work experience

YearPosition
2025 – present Associate Researcher at aivancity
2022 – present Lecturer in computer networks and cybersecurity at La Salle Passy Buzenval
2024–2025 Teacher of computer networks and cybersecurity at the CFA-SDMI
2018–2022 Assistant Lecturer in Electrical Engineering at Al-Ahliyya University, Amman, Jordan
2013–2017 PhD student in computer vision

Publications

  • Hossam et al. (2022): Solar Radiation Forecasting by Pearson Correlation Using LSTM Neural Network and ANFIS Method: Application in West-Central Jordan, Future Internet MDPI (Scopus Q2)
  • Bassam et al. (2022): Automated Detection of Left Bundle Branch Block from ECG Signal Utilising the Maximal Overlap Discrete Wavelet Transform with ANFIS, MDPI (Scopus Q2).
  • Bassam et al. (2022): Assessment of the Dual-Tree Complex Wavelet Transform to Improve SNR in Conjunction with a Neuro-Fuzzy System for Heart-Sound Identification, Electronics MDPI (Scopus Q2).
  • Bassam et al. (2020): A Framework for the Classification of Heart Sound Signals in the PhysioNet Challenge 2016 Using High-Order Statistics and an Adaptive Neuro-Fuzzy Inference System, IEEE Access (Scopus Q1).
  • Bassam et al. (2020): Quantitative Analysis of a Signal-Based Approach Using the Dual-Tree Complex Wavelet Transform for Studying Heart Sound Conditions, 5th IEEE Middle East and Africa Conference on Biomedical Engineering (MECBME2020), Amman, Jordan, 24–26 March 2020.
  • Fraihat et al. (2017): A Pseudo-3D Vision-Based Dual Approach for Machine-Awareness in Indoor Environments Combining Multi-Resolution Visual Information, IWANN 2017, CĂĄdiz, Spain, 14–16 June 2017, Springer, LNCS series, Vol. 10306, Part II.
  • Madani et al. (2017): Machine-Awareness in Indoor Environments: A Pseudo-3D Vision-Based Approach Combining Multi-Resolution Visual Information, IEEE/IDAACS 2017, Bucharest, Romania, 21–23 September 2017.
  • Fraihat et al. (2015b): Soft-Computing-Based Fast Visual Objects’ Distance Evaluation for Robots’ Vision, IEEE/IDAACS 2015, Warsaw, Poland, 24–26 September 2015.

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