Summary
Maria Vincenzi is a postdoctoral researcher at Duke University with eight years of experience applying Bayesian methods and data-intensive techniques to cosmology, notably measuring key cosmological parameters from the Dark Energy Survey supernova sample. Her PhD work combines advanced statistical modeling, high-performance computing, and machine learning, and she was one of 22 students selected for DISCnet’s elite data science training. Maria has hands-on software engineering experience from Berkeley Lab, where she developed multi-language pipelines and database-integrated tools for scientific collaborations. Comfortable across Python, C++, R and SQL, she bridges rigorous research and production-ready code to turn complex astronomical data into robust inferences.
8 years of coding experience
Master Final Thesis, Cosmology, Master Final Thesis, Cosmology at University of California, Berkeley
University of Milan
Institute of Cosmology and Gravitation