Xiongren Chen

Interpretable Machine Learning for the Early Smoke Wild-fire Detection

University of South Australia

Xiongren has a Master of Philosophy in Computer Science from the University of Adelaide and an MSc in computational finance from the University of Essex. Currently, he is pursuing a PhD in the field of machine learning at the University of South Australia.

His research is focused on explainable machine learning, which is a rapidly expanding area of study that aims to make machine learning more accessible to non-experts by providing clear and understandable explanations for how the system reaches its conclusions. Specifically, Xiongren is interested in improving explainable machine learning methods for satellite images in computer vision. Through his work, he hopes to advance the field and develop techniques that enhance the effectiveness of machine learning while also making it more transparent and interpretable.

Project Title: Interpretable Machine Learning for the Early Smoke Wild-fire Detection

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