Summary
Cristian Pena is an undergraduate mechanical engineer and applied-maths researcher focused on computational inverse problems and stochastic modeling, with 11 years of hands-on experience across experimental and computational labs. He develops Python and R frameworks that combine Bayesian inversion, PDE-constrained optimization, reduced-order models, and adjoint methods to estimate physical parameters—most recently for Fokker–Planck modeling of Jupiter’s radiation belts in collaboration with JPL. His work spans lab microfluidics and laser thermometry to video-processing and climate SDEs with Lévy jumps, demonstrating a rare blend of experimental validation and high-performance inference. Cristian consistently drives down computational and experimental bottlenecks (e.g., 90% faster image analysis, <1% parameter recovery errors) and designs trajectories and controls that trade off ∆v with posterior uncertainty. Based in Fort Lauderdale and studying at Florida Atlantic University, he brings solid interdisciplinary tooling and an appetite for mission-scale problems that bridge theory and practice.
11 years of coding experience
Bachelor's degree, Mechanical Engineering w/ minor in Mathematics, Bachelor's degree, Mechanical Engineering w/ minor in Mathematics at Florida Atlantic University