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CURRICULUM VITAE

DR. MUHAMMAD HUSAINI BIN AB AZIZ
DR. MUHAMMAD HUSAINI BIN AB AZIZ
Dental Lecturer
Department of Restorative Dentistry
Faculty of Dentistry

BIOGRAPHY


Dr. Muhammad Husaini Ab Aziz graduated from the Universiti Malaya in 2019 and subsequently served in the government service before pursuing his specialist training in 2022. He completed the training in Endodontology through the Master of Clinical Dentistry programme at King’s College London, where he graduated with Distinction.

He is currently a clinical endodontic lecturer, actively involved in undergraduate and postgraduate teaching, clinical supervision, and research development. His master’s research focused on the prognostic factors influencing the survival of endodontically treated teeth, with particular emphasis on the impact of residual tooth structure and cuspal coverage restorations using CAD/CAM materials. He also has a growing interest in digital dentistry and artificial intelligence applications in endodontics, including radiographic segmentation and AI-assisted detection models.

ACADEMIC QUALIFICATION


  • Master of Clinical (Equal to PhD)
    King's College London
  • SARJANA MUDA PEMBEDAHAN PERGIGIAN, (Dental Surgery)
    Universiti Malaya (UM)

ADMINISTRATIVE DUTIES


  • Task Force Member for The Interviews for the Master in Oral Science (Endodontology) Programme, 2026/2027 Academic Session
    13 Mar 2026 - 19 Mar 2026 (Department of Restorative Dentistry, Faculty of Dentistry)

MEMBERSHIPS


  • ORDINARY MEMBER FOR THE INTERNATIONAL ASSOCIATION FOR DENTAL, ORAL, AND CRANIOFACIAL RESEARCH MALAYSIAN SECTION (IADR-MALSEC), MEMBER
    2026 to present (National)

PUBLICATIONS


Other Publications
  1. Special Issue: European Society of Endodontology: Abstracts from the 22nd Biennial Congress ‘Challenges, Opportunities, and New Perspectives in Endodontology’ 3rd to 6th September 2025 Paris, France. R093 - The Impact of Tooth Structure Preservation on the Outcome of Endodontically Treated Teeth Following CAD/CAM Cuspal Coverage Restorations: a 6-Year Follow-Up 59 (S1), 46 - Meeting Abstract

RESEARCH PROJECT


University
  1. 2026 - 2027, University Grant
    Comparison of U-Net and K-Net deep learning models for pulp chamber segmentation of first molars on cone-beam computed tomography-A pilot study ( Co-Researcher)

SUPERVISION


PATENT/ IPR


  • Jaga Gigi Semudah ABC Buku Aktiviti Kanak-Kanak
    COPYRIGHT