Computing Educator and Researcher
I make reasoning visible.I make computing accessible.I turn coursework into contribution.
Prof. Dr. MOHAMMED Aquil Mirza, 马安奎(FIES, FIETE, FMHKCS, SGIETE, SMIEEE, LMACM)Computing Educator and Researcher
I teach computing to large, diverse classes at PolyU — making reasoning visible, making concepts accessible across disciplines, and mentoring coursework into publications, patents, and award-winning innovation.
2,000+
Students Reached
6
Books Authored
500+
Student Outputs Since 2025
4.6–4.8
Student Feedback (eSFQ)
Teaching & Research
Featured Projects
HCR — Hair Cutting Robot 3D Learning Simulator
An adaptive coding game platform for programming a five-joint hair-cutting robot in the browser. Learners arrange Blockly commands while a computerized adaptive testing engine adjusts challenge difficulty and a deterministic digital twin refuses any movement that would reach the head. Built by Pmine Research at Field of Dream Studio.
PulmoSight — Lung Cancer Rapid Screening & Triage
A cross-institutional PolyU–HKUST student research prototype for AI-assisted chest CT review. PulmoSight is designed to flag suspicious lung nodules, classify risk, segment high-risk regions, and produce structured outputs that help clinical teams prioritise cases for physician review. It is a triage-support instrument, not an autonomous diagnostic system or replacement for clinical judgement.
Arona — Adaptive Assessment Engine
An adaptive assessment engine that adjusts challenge based on verified learner performance, supporting personalised, scalable assessment. The work behind the IEEE ICCSP 2026 Best Paper on Smart Education Systems, a Hong Kong short-term patent, and a PCT international application, with dissemination through QS Reimagine Education 2026 and the eLFA Symposium 2026.
Scholarship
Featured Publication
Best Paper Awards
Award Certificates & Recognition
High Performance Adaptive Learning and Testing System with Safe Dynamic Plugin System
Smart Construction Safety Platform: Integrating AI and IoT for Proactive Hazard Management
Texture-Based Classification Techniques for Sports Surface and Equipment Analysis Using Deep Learning
About
About Me
Computing educator and researcher at The Hong Kong Polytechnic University, teaching large, highly diverse cohorts across computing, engineering, design, and the sciences. My teaching is built on a visible-to-impact pedagogy — making reasoning visible, translating concepts across disciplines, adapting support to learner needs, and converting coursework into research papers, competition wins, patents, and start-up pathways. Alongside teaching, I research adaptive assessment, AIoT, robotics, and smart health systems, and author books spanning robot control, operating systems, and computing education.
Senior Lecturer in the Department of Computing at The Hong Kong Polytechnic University and IEEE Senior Member. University Nominee for the UGC Teaching Award (Early Career Faculty Sector, 2026), recipient of the PolyU Early Career Teaching Faculty Award (2025) and the IETI Teaching Excellence Award (2026).
Documents & profiles
Focus
Research Themes
- Software engineering
- AI
- AIoT
- Robotics
- LLMs/VLMs
- Agentic AI
- Deep learning
- Complex sensor networks
- Medical imaging and diagnostics
- Robotics for surgery and rehabilitation
- Structural health monitoring
- Inclusive computing education
- Computerized adaptive testing
- Service-learning & community-engaged pedagogy