Fall 2023

Muhammad Hasham Qazi

Muhammad Hasham Qazi

Visiting Student
Texas A&M University, Habib University


Friday, 10/20/23 at 12:30 PM - 1:00 PM (Central)


Developing VR-based Training Simulations for Emergency Fire Handling Services

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Training firefighters for real-world scenarios is not only costly but also challenging to execute comprehensively. Given the critical importance of thorough training against the backdrop of these significant expenses, there's a pressing need for innovative yet effective alternatives. This work delves into developing a modular Virtual Reality (VR) training platform tailored towards the experiential learning of firefighters. Designed to address the limitations of traditional hands-on training, this platform offers diverse and realistic fire simulation scenarios. Drawing from real-world events typically faced by firefighters in urban settings, the simulations are informed by existing literature, training manuals, and user feedback from online firefighting communities. Training in this VR environment exposes trainees to a wide range of potential issues and scenarios in urban environments, better preparing them for the challenges they might encounter in real-life firefighting emergencies. This project lays the foundation for developing modular simulations, providing principles that can be adapted and customized to suit specific training requirements.


Muhammad Hasham Qazi is currently a Product Research and Documentation Associate at Astera Software, where he researches enterprise-ready data management solutions. He earned his BS in Electrical Engineering from Habib University, during which he garnered multiple awards and distinctions. Additionally, Hasham is a visiting member of the HCIED (Human-Computer Interaction Engineering and Design) Lab, led by Dr. Jeeeun Kim. His research primarily centers on leveraging VR and MR technologies to revolutionize education, training, and collaborative work. Through the integration of HCI, XR, and AI technologies, Hasham aspires to improve traditional learning and training approaches.