Spencer Veatch

Hello! I’m Spencer Veatch, a master’s student in Data Science at Willamette University with a passion for solving hard problems. In my most recent role, I developed software tools and models to generate projections of climate similarity to aid in the development of renewable agriculture, and developed a cutting-edge approach to extract high-resolution irrigation estimates from Sentinel-2 to identify water waste.

The primary focus of my research is in using machine learning to further scientific applications, be it greener ways to grow plants or faster and more accurate ways to diagnose disease. My specific interests span computational biology and machine learning, with special focus on computer vision algorithms, clustering, image denoising, and optimization theory. I’m currently working on using complex-valued convolutional neural networks (CVNNs) for joint super resolution and denoising in widefield and SIM fluorescence microscopy. I am also developing models for disease diagnosis using imaging technologies (like CT scans and MRIs), as well as disease discovery using multi-omic clustering.

Outside of academia, I love to channel my energy into puzzles and projects. A special favorite of mine is Project Euler, which hosts a wide variety of tricky mathematical puzzles. I’ll also occasionally browse the ACA’s crypotograms and more algorithmic exercises. When I’m not immersed in data and algorithms, you’ll find me outside hiking, climbing, or (on very rainy days) inside baking delicious treats.