Mark Balas

About

Mark Balas is a Professor of Mechanical Engineering at Texas A&M University and holds the title of Leland T. Jordan Professor. His educational background includes a Ph.D. in Applied Mathematics and M.S. degrees in Electrical Engineering and Mathematics from the University of Denver, as well as a B.S. in Electrical Engineering from the University of Akron. His research interests focus on control and estimation of quantum systems. Throughout his career, he has received several prestigious awards and honors, including the AIAA GNC Control Heritage Award (Lifetime Achievement Award) in 2018, and he is recognized as a Fellow by ASME, IEEE, and AIAA. His professional profile can be found on Google Scholar, and he is actively involved in research and academic activities within the Department of Mechanical Engineering at Texas A&M University.

Research topics

• Computer Science
• Artificial Intelligence
• Mechanical engineering
• Physics
• Quantum mechanics
• Engineering ethics
• Mathematics
• Engineering
• Statistical physics
• Algorithm

Selected publications

• Conclusions and Future Work

  Synthesis lectures on biomedical engineering · 2023 · 13 citations

  Senior authorCorresponding
  PublisherDOI

• Exponential Convergent Nonlinear Estimation of the Quantum Density Operator for a Quantum Mechanical Statistical System Using Metric Projection Operators

  AIAA SCITECH 2022 Forum · 2022 · 4 citations

  1st authorCorresponding

  View Video Presentation: https://doi.org/10.2514/6.2022-2211.vid The fundamental element of quantum statistical mechanics is the quantum density operator. Once determined, this operator reveals the statistics of observables in a quantum process. In this paper, we present our results on the estimation and approximation of the quantum density operator from the Liouville-Von Neumann Quantum Master Equation description of a dynamical Quantum System. We illustrate these results with an application of…

  PublisherDOI

• Closed-Form Hilbert Projection for Quantum State Observers

  2023-05-31 · 3 citations

  article

  Designing an observer of an unknown quantum density operator is difficult because the operator must be Hermitian positive semidefinite with unit trace. In this paper, we derive a closed-form solution for projecting an arbitrary matrix onto the set of valid density operators. This allows us to design linear quantum state observers and retract the observer’s state back to this set while retaining the exponential convergence rate of the linear observer. The derived closed-form projection can be use…

  PublisherDOI

• An adaptive unknown input approach to brain wave EEG estimation

  Biomedical Signal Processing and Control · 2022-08-22 · 3 citations

  article
  PublisherDOI

• A Path to Solving Robotic Differential Equations Using Quantum Computing

  Journal of Autonomous Vehicles and Systems · 2022-07-01 · 3 citations

  article

  Abstract Quantum computing and quantum information science is a burgeoning engineering field at the cusp of solving challenging robotic applications. This paper introduces a hybrid (gate-based) quantum computing and classical computing architecture to solve the motion propagation problem for a robotic system. This paper presents the quantum-classical architecture for linear differential equations defined by two types of linear operators: unitary and non-unitary system matrices, thereby solving a…

  PublisherDOI

Frequent coauthors

• Susan A. Frost

  Birmingham Women’s and Children’s NHS Foundation Trust

  84 shared

• Vinod P. Gehlot

  32 shared

• Kaman Thapa Magar

  University of Dayton

  24 shared

• Alan Wright

  National Renewable Energy Laboratory

  20 shared

• Tristan D. Griffith

  Texas A&M University

  20 shared

• Nailu Li

  Yangzhou University

  14 shared

• Robert J. Fuentes

  14 shared

• James E. Hubbard

  Edward Via College of Osteopathic Medicine

  12 shared

Awards & honors

• AIAA GNC Control Heritage Award (Lifetime Achievement Award)…
• ASME Fellow, 2015
• IEEE Fellow, 2006
• AIAA Fellow, 2001

Similar researchers at Texas A&M University

• Guillermo Aguilarh-42
• Iman Borazjanih-39
• David Claridgeh-34