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Tim is a NASA-SERVIR Data Scientist SERVIR – a joint development initiative between NASA and the U.S. Agency for International Development (USAID) – I focus on strengthening the Earth observation application and data accessibility in developing nations. Focusing on Machine Learning, Deep Learning, and Artificial Intelligence approaches and works with the aim to build capacity with partners to leverage cutting edge technologies to address localized environmental challenges.

Tim is also a Research Scientist with the University of Alabama in Huntsville (UAH) and member of the Laboratory for Applied Science (LAS).

Tim is also a Google Developer Expert for Google Earth Engine (GEE) working with GEE and Google Cloud Platform to use ML, DL, AI to address environmental issue around the world.

Tim Mayer's Projects

datacardsplaybook icon datacardsplaybook

The Data Cards Playbook helps dataset producers and publishers adopt a people-centered approach to transparency in dataset documentation.

fsh icon fsh

This software performs the automated forest height inversion and mosaicking from spaceborne repeat-pass L-band HV-pol InSAR correlation magnitude data (e.g. JAXA’s ALOS-1/2, and the future NASA-ISRO’s NISAR) that have been pre-processed by JPL’s ROI_PAC and/or ISCE programs.

highrescanopyheight icon highrescanopyheight

This repository provides inference code to compute canopy height maps from aerial images, as described in the paper "Very high resolution canopy height maps from RGB imagery using self-supervised vision transformer and convolutional decoder trained on Aerial Lidar".

hydra-floods icon hydra-floods

HYDrologic Remote sensing Analysis for Floods Python package

presto icon presto

Lightweight, Pre-trained Transformers for Remote Sensing Timeseries

rheas icon rheas

Regional Hydrologic Extremes Assessment System

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