Team

Our interdisciplinay team brings together experts in quantum algorithms, theoretical physics, theoretical computer science, and discrete optimization who are accustomed to working in interdisciplinary teams. We also provide opportunities for computer scientists and applied mathematicians, who may have not done extensive work on quantum computing, to rapidly come to the forefront of the field

Sandia National Laboratories

  • Ojas Parekh (Project Director)
    Quantum approaches to discrete optimization, Theoretical computer science
     
  • Andrew Baczewski
    Quantum and classical simulation of many-body quantum systems
     
  • Matthew Grace
     
  • Kenneth Rudinger
    Quantum characterization, verification, and validation; Quantum algorithms
     
  • Mohan Sarovar
    Quantum control, Quantum dynamics

Los Alamos National Laboratory

  • Rolando Somma
    Quantum computing, Condensed matter
     
  • Yigit Subasi

University of Maryland, College Park 

  • Andrew Childs
    Quantum algorithms
     
  • Stephen Jordan (also affiliated with Microsoft Research)
    Quantum algorithms for simulating and optimization, Quantum complexity theory
     
  • Yi-Kai Liu (also affiliated with NIST)
    Quantum algorithms, Machine learning
     
  • Brian Swingle
    Quantum Many-Body Physics, Quantum Gravity
     
  • Jacob Taylor (also affiliated with NIST)
    Quantum machine learning, Many-body quantum systems
     
  • Xiaodi Wu
    Quantum machine learning, Optimization

California Institute of Technology

  • John Preskill

Virginia Commonwealth University

  • Sevag Gharibian (also affiliated with Universität Paderborn, Germany)
    Quantum algorithms and complexity theory