General Lab Information

Anthony DeGennaro

Assistant Computational Scientist

Expertise

  • Reduced-Order Modeling
  • Uncertainty Quantification
  • Dynamical Systems
  • Machine Learning

Education

  • Ph.D., Mechanical and Aerospace Engineering, Princeton University, 2016
  • M.A., Mechanical and Aerospace Engineering, Princeton University, 2013
  • B.S., Mechanical and Aerospace Engineering, University of Virginia, 2011

Professional Appointments

  • June 2018 – Present, Assistant Computational Scientist, Brookhaven National Laboratory
  • October 2016 – June 2018, Postdoctoral Research Associate, Los Alamos National Laboratory

Selected Publications & Research Highlights

DeGennaro AM and NM Urban (2019). Scalable extended dynamic mode decomposition using random kernel approximation. SIAM Journal on Scientific Computing 41(3):A1482-A1499. DOI: 10.1137/17M115414x.

DeGennaro AM, NM Urban, BT Nadiga, and TS Haut (2019). Model structural inference using local dynamic operators. International Journal for Uncertainty Quantification 9(1):59-83. DOI: 10.1615/Int.J.UncertaintyQuantification.2019025828.

DeGennaro AM, CW Rowley, and L Martinelli (2015). Uncertainty Quantification for Airfoil Icing using Polynomial Chaos Expansions. Journal of Aircraft 52(5):1404-1411. DOI: 10.2514/1.C032698.