IMPACT’s machine learning (ML) team is heading to AGU to share their latest accomplishments and research.
Shubhankar Gahlot will present “Leveraging citizen science and artificial intelligence for monitoring and estimating hazardous events,” discussing the importance of incorporating citizen science in detecting and estimating the extent of natural disasters. Floods and hurricanes are examples of natural disasters that cause immense damage to property and lives. Knowing the extent of these disasters is crucial for emergency management and resource allocation by federal agencies like FEMA, local authorities, and nonprofit aid organizations. This information is also important for climate scientists for predicting the impacts of climate change on any such future events.
IMPACT hosted competitions to involve the broader science community in the estimation of hurricane wind speeds and flood extents based on satellite images. Teams created labels, formulated an extent detection problem for floods, and a wind speed estimation problem for hurricanes using the imagery to find computational solutions. This presentation discusses the methods used to generate the datasets, results from the competition, and the lessons learned.
The presentation “Trend analysis of AI/ML tools and services in NASA,” given by Slesa Adhikari. She examines the extent to which the use of machine learning (ML) algorithms within NASA’s Science Mission Directorate (SMD) have been increasing over the years by analyzing publications and presentations available through NASA Technical Reports Server and PubMed Central. Identifying the problem types and class of ML algorithms used to tackle them across the divisions presents opportunities for collaborations, interdisciplinary projects and knowledge transfer for sustainable partnerships.
