![NIWA Flood](https://ml4sg.auckland.ac.nz/files/2023/03/NIWA-Flood.jpg)
Project Code: SCI088
Project Description:
Floods, the most prevalent of natural disasters, impact over 250 million people annually, leading to economic damages of approximately $10 billion. Our project aims to address this pressing issue by developing an advanced warning system that leverages multi-modality generative machine learning.
By investigating the potential of extreme weather events, particularly flooding, and integrating valuable data on green, grey, and blue infrastructure, we strive to equip policymakers with the necessary tools to make informed decisions. Our ultimate goal is to empower organizations and individuals, enabling them to take proactive measures to mitigate damage and save lives.
Be a part of the Centre of Machine Learning for Social Good: Join our dynamic team. We are committed to advancing fundamental knowledge in machine learning and data analytics while tackling the most challenging health, environmental, and societal problems of our time.
By participating in this project, you will contribute to the development of a prototype for an open-sourced early event warning system. This system will revolutionize the way extreme weather events, such as floods, are predicted and managed. Your role will involve engaging in meaningful discussions with our collaborators to refine the system’s design and functionality, ensuring its effectiveness and usability.
Project Output:
Supervisors:
Yun Sing Koh,
Requirements:
To excel in this project, proficiency in Python programming, including Keras or Pytorch, and a strong understanding of machine learning fundamentals are essential. Familiarity with large-language models is considered advantageous. We are seeking individuals who possess a deep passion for creating impactful outcomes that positively influence society.