I am eager to join the Hong Kong Laureate Forum to engage with fellow young scientists and distinguished researchers, exchanging insights and experiences that drive scientific progress. As a PhD candidate in fire science, my research focuses on wildfire behavior and firebrand generation, where I integrate experimental data with computational simulations and emerging technologies like Artificial Intelligence and Quantum Computing. Understanding the mechanics of wildfires is crucial for mitigating their devastating impact on ecosystems and communities, making interdisciplinary collaboration essential.

This forum presents a unique opportunity to discuss cutting-edge advancements with experts across disciplines, gaining perspectives that could enhance my research methodologies. The prospect of presenting my work in a stimulating intellectual environment and receiving feedback from renowned scientists is invaluable. Additionally, exploring Hong Kong’s scientific institutions and development projects will provide fresh insights into applying technology to real-world challenges.

Beyond academia, I am eager to connect with like-minded peers from diverse backgrounds, fostering collaborations that extend beyond the forum. The cross-cultural social activities will further enrich this experience, reinforcing my commitment to contributing to the global scientific community while broadening my interdisciplinary expertise.

Firebrands, small burning particles, are a key driver of wildfire spread. Generated from burning vegetation, they are carried by wind to ignite spot fires ahead of the main fire front. Fire behaviour models aim to predict this spread, but limited data on firebrand properties introduces uncertainty. Developing a fast and reliable method for firebrand fuel characterization is essential. Our study uses Terrestrial Laser Scanning (TLS) data to quantify the fine fuels in near surface, elevated and canopy forest layers. TLS scans were collected from three forest type sites in Victoria, Australia. A set of algorithms were used to extract and build characteristics of firebrand fuel from the TLS point-cloud data. We categorised firebrand fuel into three types: twigs (diameter < 5 cm), candle bark and stringybark.