Offshore fault zones are often the origin of great seismologic activity; the ways the seafloor shifts and changes in these areas could be the key to unlocking a greater understanding of the factors which cause earthquakes and tsunamis. However, Current methods of mapping the seafloor are still done manually, which makes them time consuming and inconsistent. Our team plans to address this problem by developing a machine learning tool to detect and characterize faults in bathymetric data.

With the help of our sponsors we are developing a tool which takes in high resolution sea floor topology and applies trained models to identify faults on tectonic plates in subduction zones across the globe. While humans will likely still need to check the work of the machine, this will accelerate the mapping process ultimately shaving off years of time from the research of our sponsors.

Mini Intro Presentation - September 26th 2025

Tech Fesability - October 24th 2025

Prototyping - November 2025

Requirements Document - November 26th 2025

Technical Demo - December 2025

Implementation - Spring 2026