Vinicius Mikuni
Postdoc - Employee
National Energy Research Scientific Computing Center (NERSC)
Science Engagement & Workflows Dept.
Data & AI Services Group
Vinicius Mikuni is a NESAP for Learning Postdoctoral Fellow at NERSC. His current research focuses on machine learning development and application for experimental High Energy Physics, including Likelihood-free deep learning for detector simulation, unfolding, and anomaly detection on the search for new physics processes. He received his PhD in 2021 from the University of Zurich, measuring the production cross-section of top quark pairs in association to b quarks and the search for new physics in signatures involving third-generation fermions using the data collected by the CMS Collaboration.
Recent Publications
Unifying simulation and inference with normalizing flows
Authors: Du, H; Krause, C; Mikuni, V; Nachman, B; Pang, I; Shih, D
April 2025, Physical Review D
Solving key challenges in collider physics with foundation models
Authors: Mikuni, V; Nachman, B
March 2025, Physical Review D
Generative unfolding with distribution mapping
Authors: Butter, A; Diefenbacher, S; Huetsch, N; Mikuni, V; Nachman, B; Palacios Schweitzer, S
June 2025, SciPost Physics
Tools for unbinned unfolding
Authors: Milton, R; Mikuni, V; Lee, T; Arratia, M; Wamorkar, T; Nachman, B
May 2025, Journal of Instrumentation
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