Contact:

    email: michael.dolce@tufts.edu
    LinkedIn: www.linkedin.com/in/mikedolce8
    Handshake: https://app.joinhandshake.com/users/6887068
    

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About Me

I am a PhD student studying experimental high energy neutrino physics at Tufts University, and a collaborator on the NOvA experiment located at Fermi National Accelerator Laboratory (FNAL).

I received my B.S. in physics from the University at Albany in 2017. During my time, I worked with Vivek Jain on the ATLAS detector at CERN.

In 2020, I received my M.S. in Physics at Tufts University.

My thesis work is within the Tufts High Energy Physics group, under my advisor Professor Hugh Gallagher, to measure neutrino oscillation parameters with data from the NOvA experiment.

For the 2020-2021 academic year, I was funded by the Universities Research Association (URA) Visiting Scholars Program (VSP) for graduate students and faculty to study at Fermi National Accelerator Laboratory to complete research.

For the 2021-2022 academic year, I am funded by the Tufts University Data-Driven Decision Making (D3M) program Research Fellowship funded by the National Science Foundation (NSF). This program is part of the NSF's Research Traineeship (NRT) and the NSF's Harnessing Data Revolution (HDR) initiative to promote:
(1) connecting numbers to narratives,
(2) learning how to learn, and
(3) embracing complexity.

A link to my full CV is here.

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PhD Thesis Research

My thesis research is to use Monte Carlo Markov Chain (MCMC) -- a Bayesian inference tool -- with Hamiltonian Monte Carlo on the NOvA Near and Far Detector data to obtain best fit values for NOvA's systematic uncertainty model and the neutrino oscillation parameters.