Summary
Diane Oyen is a seasoned information science leader and machine learning researcher with over a decade of experience developing probabilistic and data-driven methods for scientific discovery. As Deputy Director of the Information Science and Technology Institute and AI Team Leader at Los Alamos National Laboratory, she builds algorithms for anomaly detection, data fusion, and transfer learning applied to problems from Mars rover geochemistry to cybersecurity. Her expertise spans Bayesian networks, active learning, and interactive intelligent systems, and she codes in C/C++, Matlab, Python, Java, and R. Diane’s work uniquely blends rigorous academic foundations—earned through a Ph.D. in computer science—with hands-on engineering across VLSI, teaching, and national-lab scale projects, enabling practical tools that help scientists make sense of noisy, complex datasets.
10 years of coding experience
12 years of employment as a software developer
Ph.D., Computer Science, Ph.D., Computer Science at The University of New Mexico
B.S., Electrical and Computer Engineering, B.S., Electrical and Computer Engineering at Carnegie Mellon University