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Zachary Grey (Fed)

Dr. Zach Grey graduated from the University Colorado - Boulder (CU) Aerospace Engineering Sciences department. His research began in the Applied Mathematics and Statistics Department at Colorado School of Mines (Mines) where he qualified for the Ph.D. and later transferred to CU following his research advisor, Prof. Paul Constantine. Prior to CU and Mines, Zach graduated with a B.S. in Aerospace Engineering from Embry-Riddle Aeronautical University and later an M.S. in Aeronautical and Astronautical Engineering from Purdue with an emphasis in optimization and minor in applied mathematics. In conjunction with earning his master's degree, Zach worked at the Rolls-Royce Corporation designing/analyzing gas-turbine flow-path components and eventually ending his tenure as Robust Design Technical Lead.

His research at NIST involves model-based dimension reduction and manifold learning for facilitating novel explanations and interpretations related to artificial intelligence and machine learning. Specifically, he often works with data-driven applications involving imaging/signal processing, geometry, and optimization.

External Resources:


  • Applied & Comp. Math Dept., Math Modeling & Analysis Group, NIST:
    Staff (Nov. 2022 - Present)
  • Applied & Comp. Math Dept., Math Modeling & Analysis Group, NIST:
    National Research Center Post-Doctoral Researcher (Nov. 2019 - Nov. 2022)
  • Aerospace Engineering Sciences Dept., Univ. Colorado-Boulder:
    Ph.D. Research Assistant (Aug. 2017 - Nov. 2019)
  • Applied Mathematics & Statistics Dept., Colorado School of Mines:
    Fryrear Fellow - Ph.D. Research Assistant (Aug. 2015 - Aug. 2017)
  • Rolls-Royce Corporation:
    Robust Design Technical Lead, (Mar. 2011 - Aug. 2015, full-time & Aug. 2015 - Nov. 2019, part-time)
    F136 LP Turbine Blades & Vanes Design, (Jul. 2010 - Mar. 2011, full time)
  • Embry-Riddle Aero. Univ.:
    NASA Space Grant Research Assistant, (Oct. 2008 - May 2010)

Selected Publications


G2Aero: A Python package for separable shape tensors

Olga Doronina, Zachary J. Grey, Andrew Glaws
G2Aero is a Python package for the design and deformation of discrete planar curves and tubular surfaces using a geometric data-driven approach. G2Aero utilizes

Separable Shape Tensors for Aerodynamic Design

Zachary J. Grey, Andrew Glaws, Olga Doronina
Airfoil shape design is a classical problem in engineering and manufacturing. In this work, we combine principled physics-based considerations for the shape
Created December 8, 2019, Updated August 10, 2023