Summary
Roberto Reydecastro is a Machine Learning Research Scientist with eight years of experience and nearly six years at Peraton (formerly Perspecta) Labs, specializing in applied ML for signal and RF-spectrum problems. He brings a strong academic foundation—a PhD in Ultrafast Materials Science/Applied Physics from the University of Rochester and a top-ranked undergraduate degree in Physics—to research-driven engineering. His career spans national labs, academia, and industry, including postdoctoral work at Argonne and programmatic roles at Princeton, evidencing an ability to bridge fundamental science and deployable ML systems. At SRC he developed AI for detecting and classifying RF signals, and at Peraton he focuses on advancing research that translates into operational capability. Colleagues describe him as someone who pairs deep physics intuition with practical model-building, often tackling noisy, real-world data where domain knowledge matters as much as algorithms. Based in Hopewell, NJ, he blends rigorous experimentation with production-minded engineering to deliver robust, mission-aligned solutions.
8 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD, Ultrafast Materials Science / Applied Physics, Doctor of Philosophy - PhD, Ultrafast Materials Science / Applied Physics at University of Rochester
Bachelor's degree, Physics, 4.0, Bachelor's degree, Physics, 4.0 at Pontificia Universidad Católica del Perú