Summary
Andrew Kruger is a founder and applied scientist with six years of machine learning and computer vision experience, currently building a stealth AI startup after developing predictive capacity and throughput optimization models for Amazon's inbound logistics. He previously led ML research at Tempus, creating scalable pipelines and deep learning Histogenomics™ models to infer molecular profiles from whole-slide pathology images. Earlier work spans production-focused 3D object detection for last-mile logistics and academic research in planetary science and experimental optics, reflecting a rare blend of rigorous physics training (Ph.D., UC Davis) and applied ML. He combines hands-on model development with systems thinking—designing data pipelines, operating large instruments, and shipping production ML in regulated domains. Colleagues describe him as someone who moves smoothly between deep technical research and pragmatic product delivery, bringing experimental rigor to startup execution. An educator at heart, he has mentored students in NASA-funded projects and classroom settings, underscoring a long-standing commitment to translating complex science into practical outcomes.
6 years of coding experience
18 years of employment as a software developer
Ph.D. Physics, Ph.D. Physics at University of California, Davis
B.S. Physics, B.S. Physics at Walla Walla University
Data Science Bootcamp, Data Science Bootcamp at Metis