About Me

I am a postdoctoral researcher at the Argonne National Laboratory, the principal developer for the Toolkit for Advanced Optimization (TAO), and an active contributor to the PETSc library. My current work is focused on developing gradient-based optimization algorithms for large-scale problems in machine learning, plasma physics and geophysics.

My research interests lie in the mathematical, algorithmic and software design challenges in promoting the use of numerical optimization techniques in scientific research and industrial design, with emphasis on high performance computing applications and efficient treatment of nonlinear constraints.


  • Numerical Optimization
  • Simulation-based Design
  • High Performance Computing
  • Open Source Software


  • Aeronautical Engineering, Ph.D., 2017

    Rensselaer Polytechnic Institute

  • Mechanical Engineering, B.S., 2012

    University of Maryland, Baltimore County



Postdoctoral Appointee

Argonne National Laboratory

Feb 2018 – Present Lemont, Illinois
  • Principal developer on Toolkit for Advanced Optimization (TAO) and contributor to PETSc
  • Research large-scale optimization algorithms with efficient treatment of nonlinear constraints
  • Promote TAO, expand its user base, and provide software support for external researchers

Graduate Research Assistant

Rensselaer Polytechnic Institute

Feb 2013 – Dec 2017 Troy, New York
  • Investigate PDE-constrained multi-disciplinary design optimization problems
  • Research gradient-based, reduced-space, matrix-free optimization algorithms
  • Develop a parallel-agnostic optimization library tailored for large-scale engineering systems

Undergraduate Research Assistant

University of Maryland, Baltimore County

Oct 2010 – May 2011 Baltimore, Maryland
  • Construction of an optical aerosol measurement instrument
  • Design and manufacture of high-precision optical component mounts
  • Propose instrument mounting solutions for the NASA GSFC science fleet aircraft

Recent & Upcoming Talks

Investigating Quasi-Newton Outer Product Representations on GPUs

PDE-constrained Optimization Using PETSc/TAO

Acelerating Quasi-Newton and Conjugate Gradient Convergence for Large-Scale Optimization