Zachary James

Hi! I'm a PhD student at Cornell CIS advised by Joe Guinness, using AI to analyze satellite imagery and geospatial data. My research focuses on using generative AI and high performance computing to more efficiently interpolate and forecast enviornmental data.

email  /  linkedin  /  github

Research

I am interested in using diffusion models, Gaussian processes, and high-performance computing to analyze geospatial data, particularly with applications to climate science and ecology.

We model the nonstationary parameters of a Gaussian process as functions of space using neural networks, enabling scalable inference on large datasets while maintaining interpretability.

Vecchia Approximation can be high efficient on GPUs for large spatial datasets. We present memory and synchronization optimizations that improve performance by up to 20x over existing implementations.

Work done with the New York City Department of Emergencency Management to improve real-time forecasting using high-resolution meteorological data and scalable spatial models.

We built an image classifier to identify fruit bats in camera trap images to help epidemiologists study the transmission of Nipah virus. This was done by fine-tuning a pretrained vgg16 model on a labeled dataset of images collected in Bangladesh.

A random graph model reveals that the urban-rural divide is a major determinant of opioid abuse in the state of Georgia.

Miscellanea

This website's source code is borowed from Jon Barron.