Adam J Aurisano

Dr. Adam Aurisano is an experimental particle physicist, and his primary research interest is search for physics beyond the Standard Model in long-baseline neutrino oscillations.  He is particularly interested in testing the anomalies found at the LSND and MiniBooNE experiments, typically explained by positing the existence of new sterile neutrino states.  More generally, he has been developing searches for tau neutrino appearance, which could constrain many possible deviations from the standard three flavor paradigm.  To facilitate these interests at the MINOS/MINOS+, NOvA, and DUNE experiments, Dr. Aurisano has led efforts to develop deep learning tools for improved event selection and reconstruction.  He is currently exploring the use of hierarchical graph neural networks for full event reconstruction at DUNE.

As a graduate student at Texas A&M University, Dr. Aurisano worked on the collider experiments CDF at Fermilab and CMS at CERN.  His thesis, supervised by Dr. David Toback, detailed a search for new physics at CDF using the exclusive delayed photon + missing energy final state.

A.B.: University of Chicago Chicago, IL, 2004 (Physics)

S.B.: University of Chicago Chicago, IL, 2004 (Mathematics)

M.S.: Texas A&M University College Station, TX, 2007 (Physics)

Ph.D.: Texas A&M University College Station, TX, 2012 (Physics)

Grant: #Check 46634 Investigators:Aurisano, Adam 06-01-2019 -05-31-2020 Oak Ridge Associated Universities Adam Aurisano's ORAU Powe application Role:PI $5,000.00 Awarded Level:Private Non-Profit

Grant: #DE-SC0020110 Investigators:Aurisano, Adam 07-01-2019 -03-31-2020 Department of Energy Searches for New Physics in Neutrino Oscillations at the MINOS+, NOvA, and DUNE Experiments. Role:PI $100,000.00 Awarded Level:Federal

Grant: #DOE DE-AC02-07CH11359 - FermiLab #304943 Investigators:Aurisano, Adam 12-01-2019 -12-31-2022 Department of Energy Exa.TrkX - Machine Learning for HEP Tracking at Extreme Scales Role:PI $75,000.00 Awarded Level:Federal

Grant: #OAC-2018617 Investigators:Atluri, Gowtham; Aurisano, Adam; Beck, Thomas; Cohen, Kelly; Khare, Prashant; Lee, James 08-01-2020 -07-31-2023 National Science Foundation MRI: Acquisition of High-Performance Computing Cluster for Research and Workforce Development at University of Cincinnati Role:Collaborator $600,000.00 Awarded Level:Federal

Grant: #Action Fund 1817 (See 013171) Investigators:Atluri, Gowtham; Aurisano, Adam; Beck, Thomas; Cohen, Kelly; Khare, Prashant; Lee, James 08-01-2020 -07-31-2023 Ohio Department of Higher Education MRI: Acquisition of High-Performance Computing Cluster for Research and Workforce Development at University of Cincinnati Role:Collaborator $128,571.50 Awarded Level:State of Ohio

Grant: #DE-SC0011784 Investigators:Argyres, Philip; Aurisano, Adam; Bischoff, Colin; Brod, Joachim; Kagan, Alexander; Kinoshita, Kay; Schwartz, Alan; Sousa, Alexandre; Wijewardhana, L.C.R.; Zupan, Jure 04-01-2020 -03-31-2023 Department of Energy Research in Particle and Cosmology Theory and Experiment at the University of Cincinnati Role:Collaborator $1,250,000.00 Awarded Level:Federal

Grant: #DE-SC0011784 Investigators:Argyres, Philip; Aurisano, Adam; Bischoff, Colin; Brod, Joachim; Kinoshita, Kay; Pereira E Sousa, Alexandre; Schwartz, Alan; Wijewardhana, L.C.R.; Zupan, Jure 07-01-2023 -06-30-2026 Department of Energy Research in Particle and Cosmology Theory and Experiment at the University of Cincinnati Role:PI 1353000.00 Hold Level:Federal

Grant: #DE-SC0024698 Investigators:Aurisano, Adam 09-01-2023 -08-31-2026 Department of Energy Reconstructing Tau Neutrinos at DUNE Using Hirearchical Graph Neural Networks Role:PI 72131.00 Awarded Level:Federal

Peer Reviewed Publications

A. Aurisano, V. Hewes, G. Cerati, J. Kowalkowski, C.S. Lee, W. Liao, D. Grzenda, K. Gumpula, X. Zhang (2024. ) NuGraph2: A Graph Neural Network for Neutrino Physics Event Reconstruction.Phys. Rev. D (accepted), , More Information

M.A. Acero et al (NOvA Collaboration) (2024. ) Search for CP-violating Neutrino Non-Standard Interactions with the NOvA Experiment.Phys. Rev. Lett., , More Information

Book Chapter

Adam Aurisano and Leigh H. Whitehead (2022 ) End-to-End Analyses Using Image Classification Artificial Intelligence for High Energy Physics .(pp. 313 -353).World Scientific (Author)