Jose Luis Preciado Arreola

Jose Luis Preciado Arreola

Research Assistant

Department of Industrial and Systems Engineering, Texas A&M University
3021 Emerging Technologies Building, College Station, TX, 77843-3131



Ph.D., Industrial and Systems Engineering, Texas A&M University.
(September 2011- Present)

M.S., Management Science and Engineering, Stanford University.
(September 2008- July 2009)

B.S., Industrial and Systems Engineering, ITESM Monterrey, Mexico.
(August 2003- December 2007)

Work Experience

Modeling Specialist, Cal y Mayor y Asociados, Mexico City, Mexico
(July 2009 – June 2011)

Manufacturing Analyst, Nemak, Monterrey, Mexico
(May 2008 – August 2008)

Research Interest

Productivity and Efficiency Analysis related
  • Bayesian Stochastic Frontier Analysis
  • State-contingent production
  • Bayesian shape-constrained estimation
  • Robust convex nonparametric regression for survey datasets

Management Science related
  • Performance Metrics
  • Business Analytics and Optimization
  • Applied Decision Analysis


Mention to excellence (highest undergraduate honors) at ITESM Monterrey
Stanford Alumni, Monterrey Chapter, Scholarship for Engineering Masters degrees


Preciado Arreola, J.L. and A.L. Johnson. "Convex Adaptively Partitioned Least Squares". Working Paper

Preciado Arreola, J.L. and A.L. Johnson. "Estimating Stochastic Production Frontiers: A One-stage Multivariate Semi-Nonparametric Bayesian Concave Regression Method". Working Paper available at Arxiv.

Preciado Arreola, J.L. and A.L. Johnson. "A Birth-Death Markov Chain Monte Carlo Method to Estimate the Number of States in a State-Contingent Production Frontier Model". American Journal of Agricultural Economics, Accepted 09/2014.