Noemi Petra

Noemi Petra is an Associate Professor in the Department of Applied Mathematics at the University of California, Merced, with research focusing on large-scale inverse problems, PDE-constrained optimization, uncertainty quantification, and optimal experimental design. Her work bridges mathematical theory with practical applications in geophysics and energy systems.

• Current Role: Associate Professor at UC Merced
• Research Interests: Large-scale inverse problems, PDE-constrained optimization, uncertainty quantification

Her research has produced significant contributions in Bayesian inference for ice sheet modeling, power system estimation, and scalable optimization algorithms. She has developed open-source software frameworks like hIPPYlib-MUQ for data-model integration.

Key research trends include:

• Bayesian Methods for geophysical inverse problems
• Optimization Techniques for power systems and ice dynamics
• Scalable Algorithms for high-dimensional uncertainty quantification
• Software Development for large-scale inverse problems

Scientific awards:

• NSF CAREER award (2017) for large-scale Bayesian inverse problems

She actively collaborates on ice sheet dynamics and power grid modeling, with software tools adopted in academic and industrial applications.