David Huckleberry Gutman

Assistant Professor
Department of Industrial, Manufacturing, and Systems Engineering
Texas Tech University

Research Interests

Optimization theory and algorithms. Applications of optimization to statistics and machine learning. Operations research.

Publications & Working Papers

  1. Gutman, D. & Nguyen, N., "Coordinate Descent Without Coordinates: Tangent Subspace Descent on Riemannian Manifolds"
    Working Paper, arXiv: 1912.10627, Dec. 2019
  2. Gutman, D. & Peña, J., "The Condition of a Function Relative to a Set"
    Revision Requested at Mathematical Programming, Series A, arXiv:1901.08359, Jan. 2019
  3. Gutman, D. & Peña, J., "A Unified Framework for Bregman Proximal Methods: Subgradient, Gradient, & Accelerated Gradient Schemes"
    Working Paper, arXiv: 1812.10198, Dec. 2018
  4. Gutman, D., "Enhanced Basic Procedures for the Projection and Rescaling Algorithm"
    Optimization Letters (2019) 13: 1259
  5. Gutman, D. & Peña, J., "Convergences Rates of Proximal Gradient Methods via the Convex Conjugate"
    SIAM Journal on Optimization 29-1 (2019), pp. 162-174
Google Scholar


Texas Tech University

Carnegie Mellon University


Ph.D., Mathematical Sciences, Carnegie Mellon University, (2019)
M.S., Pure Mathematics, Tulane University, (2010)
B.S.B.A, Finance & Accounting, Georgetown University, (2008)

Prospective Graduate Students

I am searching for PhD students for Fall 2020. Due to the mathematical nature of my work, a strong math background is required. A prospective student should have taken and done well in, or be currently taking, courses in linear algebra and basic real analysis. If you would like to discuss the prospect of working with me then please feel free to send me an email. Make sure to include the following items in your first email: Mathematics, statistics, operations research, and management science majors are encouraged to apply.

Please note that I will not respond to mass/copy-paste form emails.

Contact Information

Email: David dot Gutman at ttu dot edu
Phone: 806 834 6845
Office: IMSE 214