Hi! I’m Tom Colligan, a scientific software engineer by training, currently working at NASA Goddard Space Flight Center. At NASA, I lead our efforts to operationalize the LPJ-EOSIM Dynamic Global Vegetation model, a process-based model developed for carbon cycle applications. Currently, I’m interested in carbon cycle modeling and ML, and believe that clean code is a research accelerant.

I am the main author of the LPJ-EOSIM Wetland Methane products on the US Greenhouse Gas Center website, and the LPJ-EOSIM products on the Land Processes Distributed Active Archive Center. This project provides state of the art estimates of wetland methane emissions on a near-real-time basis, allowing quick quantification of the response of wetlands to climate change. In the past, I was employed as a research scientist at the University of Arizona and University of Montana. My main research focus was basic machine learning in bioinformatics, where I applied LLMs to protein retrieval. I have extensive experience in carbon cycle modeling, deep learning, machine learning, HPC systems, and AWS.