Ph.D. Student

Stephen Naboth

Computational Applied Mathematics and Operations Research

Rice University Houston, Texas

Portrait of Stephen Naboth

I am a Ph.D. student in the Department of Computational Applied Mathematics and Operations Research at Rice University, where I am advised by Professor Illya V. Hicks. My research centers on mathematical optimization, with an emphasis on mixed-integer nonlinear optimization and its connections to machine learning and scientific computing.

I develop computational methods for challenging decision problems, including bound tightening, convex relaxations, cutting planes, decomposition, and branch-and-bound techniques. I am particularly interested in applications involving energy systems, symbolic regression, multi-fidelity modeling, and scientific decision-making.

Before beginning my doctoral studies at Rice, I earned an M.S. in Financial Engineering from WorldQuant University, an M.S. in Mathematical Modelling from the University of L’Aquila, and a B.S. in Mathematics from the University of Nairobi.

You can view or download my CV.

My current research includes mixed-integer nonlinear, stochastic, and fairness-constrained optimization. Across these areas, I study how stronger formulations and tailored computational techniques can make difficult models more reliable and tractable.

Naboth, S., and I. V. Hicks. “Weighted, Dynamic, and Endogenous Fairness in Mathematical Optimization.” Manuscript in preparation.

Naboth, S. “A New Approach for Automatic Defect Detection via Thermal Image Processing and Deep Learning Tools.” Master’s thesis, University of L’Aquila.

Email: sn82@rice.edu

I welcome conversations about research, collaboration, internships, and applied optimization projects.