Dr. Muhammad Sajjad
Research Assistant Professor, Department of Geography and Resource Management, CUHK
muhammadsajjad@cuhk.edu.hk
Expertise: multi‑hazard assessment, extreme weather resilience, experiential learning & AI pedagogy.
Safety + realism gap
Fieldwork limited by extreme weather & logistics. Students miss authentic disaster rehearsal. GenAI+VR fills the void with safe, repeatable plan‑act‑reflect‑retry loops.
False sense of security
HK residents underestimate local landslide/typhoon risk. Place‑based immersion plus adaptive AI avatars builds real decision confidence and risk perception.
Transferable learning
From slope inspection to emergency coordination: students apply skills across hazards, supported by GenAI that calibrates trust & scaffolding.
Core VR slope scene + learner archetype mapping (PLSPQ). AI prompt refinement & pilot (n≥120). Non‑HMD participation >80%.
4 full disaster scenarios: slope, drainage, typhoon shelter, emergency centre. Auto‑archetype personalization, 300+ students.
Launch A3GIF, cross‑faculty pilot (English Dept). Open repository, CUHK Teaching Expo, Q1 publications.
Slope inspection & Landslide
GEO thresholds, inclinometers, evacuation decisions. Roleplay with Site Supervisor AI avatar.
Urban drainage / flooding
Sensor‑based prediction, real‑time stormwater response (Amber/Red/Black signals).
Aberdeen Typhoon Shelter
Operational management, vessel safety, coordination with emergency crews.
Emergency Ops Centre
Multi‑hazard (typhoon+landslide+flood) decision making, stress & empathy training.
Short‑term (2026–2028)
- ≥550 CUHK students: GRMD2221, UGEB2222, UGEB2871, ENGE3950
- 12–20 faculty members adopting VR/GenAI modules & rubrics
- 6 immersive HMD workshops + direct disaster simulation training
- Skill gains: decision‑making, hazard calibration, AI collaboration
Long‑term (2028 onwards)
- Cross‑disciplinary replication (engineering, urban planning, public health)
- Open VR scene library + prompt templates → low‑cost adoption across HEIs
- HK Red Cross Community Resilience Service — scaling citywide disaster literacy
- Policy influence: evidence‑based disaster preparedness education framework
Global relevance: Supports Sendai Framework for Disaster Risk Reduction (2015-2030) and UNESCO’s ESD for 2030. The project builds climate-resilient communities through AI-enhanced place-based education, directly advancing disaster literacy, risk perception, and inclusive capacity building in the face of increasing extreme weather events.