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Assistant Professor

Muhamed Fauzi Abbas

Doctor of Philosophy, Nanyang Technological University, Singapore
Cluster:
Infocomm Technology
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Biography

Muhamed Fauzi Bin Abbas is an Assistant Professor in the Infocomm Technology cluster at the Singapore Institute of Technology. His teaching and academic interests span software and embedded systems, computer architecture, Internet of Things, real-time operating systems, and edge computing. His work emphasises the application of computing principles to practical engineering problems and the development of hands-on, industry-relevant learning experiences.

His research and development interests include embedded and real-time systems, lightweight computing for resource-constrained devices, IoT and edge systems, and the application of artificial intelligence to engineering and computing education. More recently, his work has explored AI-assisted approaches for providing evidence-based feedback on student software and embedded-system projects.

Beyond teaching and research, he contributes to curriculum and assessment development, student project supervision, sustainability education, and academic service. He has also been involved in developing tools to support educational analysis and in external professional and community engagement.

SIT Appointments

  • Member, CLASIC Project Grant Evaluation Committee (PGEC)
    –
  • Member, Sustainability Education Committee (SEC)
    –
  • Cluster/CCS Teaching & Learning Lead (ICT)
    –
  • ICT Cluster representative to the IT Committee

Education

  • Doctor of Philosophy
    Nanyang Technological University , Singapore
  • Master of Engineering
    Nanyang Technological University , Singapore
  • Bachelor of Engineering
    Nanyang Technological University , Singapore

Achievements

  • Invited Speaker, DEF CON Singapore 2026, Home Team Science & Technology Agency (HTX)
  • Presenter, Black Hat MEA 2022 Briefings
  • Presenter, Black Hat Europe 2022 Arsenal
  • SIT Teaching Excellence Award, 2023

Professional Memberships

  • Member, Institute of Electrical and Electronics Engineers (IEEE)
  • Member, Association of Information Security Professionals (AiSP), Singapore
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Research Interests

  • Lightweight Intrusion Detection Technique on Resource-Constrained Computing

    Development of efficient intrusion and anomaly detection techniques suitable for embedded, IoT and resource-constrained systems.
  • IoT, Edge Computing and Embedded AI

    Development of intelligent, connected systems that bring sensing, computation and AI closer to resource-constrained edge devices.
  • AI-Assisted Engineering and Computing Education

    Application of AI and software analysis to provide evidence-grounded feedback and support learning in engineering and computing.

Current Projects

  • STRIDE: AI-Assisted Evidence-Grounded Feedback for Student Software Projects
    – Present

    An AI-supported formative feedback environment combining code analysis, build validation and AI to provide timely feedback on software projects while maintaining human academic judgement and traceability to supporting evidence.
  • μT-Kernel 3.0 for Modern Embedded and Multicore Platforms
    – Present

    Development and evaluation of μT-Kernel 3.0 ports for contemporary Arm- and RISC-V-based embedded platforms, including ESP32 and Raspberry Pi Pico devices, with ongoing work on multicore support, portability and performance evaluation.
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Teaching Modules

Computing Science, BSc (Hons)

  • INF2004 - Embedded Systems Programming
  • CSC2006 - Internet of Things: Protocols and Networks

Information and Communications Technology (Information Security), BEng (Hons)

  • INF2004 - Embedded Systems Programming

Information and Communications Technology (Software Engineering), BEng (Hons)

  • INF2004 - Embedded Systems Programming

Applied Artificial Intelligence, BSc (Hons)

  • INF2004 - Embedded Systems Programming

Past

  • ICT1001 - Introduction to ICT
  • ICT1007 - Operating Systems
  • ICT3001 - Self-Learning Module
  • ICT1010 - Computer Networks
  • CSC2003 - Embedded Systems and Sensor Programming
  • ICT2104 - Embedded Systems Programming
  • INF2009 - Edge Computing and Anaytics
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