Jake
Vikoren

I'm a physics-trained machine learning engineer specializing in AI for scientific discovery. My work spans atomic-scale modeling, geometric deep learning, and computer vision, with an emphasis on developing robust ML systems for large-scale scientific data. I excel at operating in multidisciplinary environments and translating cutting-edge research into practical solutions.

I've developed predictive and generative models across domains leveraging techniques such as VAEs, transformers, diffusion models, flow-matching, equivariant neural networks, and self-supervised learning. Throughout my career, I've demonstrated a capcity to communicate complex technical concepts to diverse audiences, from research scientists to industry stakeholders.

I'm passionate about advancing the state of the art in machine learning and applying AI to solve real-world problems in science and engineering.