Maria Brigida Brunetti
- Assistant Professor
- Research Interests: Experimental neutrino physics, particle physics software and computing techniques, machine learning
- Physics & Astronomy
Contact Info
1251 Wescoe Hall Dr.
Lawrence, KS 66045
Biography —
2024–present: Assistant Professor - The University of Kansas
2024: Assistant Professor (senior researcher-equivalent) - The University of Warwick, UK
2019–2024: Postdoctoral Research Fellow - The University of Warwick, UK
Education —
Research —
I study the fundamental properties of neutrinos, which are some of the most peculiar and least well understood particles in the Standard Model. Despite being the second most abundant particles in our universe, they are highly elusive, which makes them challenging to detect. In the Standard Model, neutrinos are massless. However, experimental observations showed that they must have tiny masses, smaller by at least hundreds of thousand times the mass of the electron. By studying them, we could answer questions such as: which is the lightest, and which is the heaviest neutrino? Do neutrinos and antineutrinos behave in the same way? How precisely do neutrinos transform between three types as they travel? Are there additional neutrinos we don’t know of? By detecting neutrinos coming from space, can we shed light onto cosmic processes such as a core-collapse supernova?
At the Fermilab Deep Underground Neutrino Experiment (DUNE) and the Fermilab short-baseline experiments, we are tackling this challenge head-on: we are producing the most powerful neutrino beam in the world, and our Liquid Argon Time Projection Chambers are akin to very large and extremely sophisticated subatomic particle “cameras”, that yield very high resolution* 2D images or 3D scans of the varied and often complex signatures of neutrino interactions.
Once we have collected the data, understanding exactly what interactions, how many and what particles we are looking at, and what their energies are, and then being able to perform our physics analyses often poses complex challenges. Having a large number of algorithms that can be tailored to neutrinos from different sources and of different energies has proven to be an effective strategy. I am a developer of the Pandora reconstruction framework, which takes exactly this approach, seamlessly blending in different techniques, including deep learning, to enable the most precise measurements and reach the maximum physics sensitivity at these experiments. DUNE and the short-baseline experiments are large international collaborations, and I routinely do my research together with more than a thousand scientists worldwide.
If you are interested in learning more about my work, or would like to discuss research opportunities within the group, please email me (mbbrunetti@ku.edu) or visit my office (Malott Hall, room 4075).