Resume

• 2001

  Ph.D.

  Systems and Industrial Engineering

  INFORMS

  IIE

  IEEE

• 1999

  MS

  Mining and Geological Engineering

  Mining robotics and automation

  SME

• 1996

  BS

  Dean's List

  Magna Cum Laude

  Mining Engineering

  Golden Key Honor Society

  SME

• Research

  Operations Research

  Mathematical Programming

  Statistics

  SAS

  Optimization

  Arena Simulation Software

  Mathematical Modeling

  Matlab

  Applied Mathematics

  Statistical Modeling

  Systems Engineering

  Simulations

  Data Mining

  LaTeX

  Linear Programming

  CPLEX

  Data Analysis

  Communications Audits

  Stochastic Online Appointment Scheduling of Multi-Step Medical Procedures in Nuclear Medicine

  Cesar O. Malave

  Peter McCormack

  Modeling and Simulation of Nuclear Medicine Patient Service Management in DEVS

  Wilbert Wilhelm

  Patient and Resource Scheduling of Multi-Step Medical Procedures in Nuclear Medicine

  Yu Ding

  Simulation of Wind Farm Maintenance Operations using DEVS

  Natarajan Gautam

  Ronny Polansky

  Julian A. Gallego

  Integrating Virtualization

  Voltage Scaling and Powering On/Off Servers in Data Centers for Energy Efficiency

  Andy Banerjee

  Kiavash Kianfar

  Michelle M. Alvarado

  Reducing pediatric medication errors: A survey and taxonomy

  Natarajan Gautam

  Ronny Polansky

  Julian A. Gallego

  Integrating Virtualization

  Voltage Scaling and Powering On/Off Servers in Data Centers for Energy Efficiency

  Andrew Schaefer

  Outer linearization methods for two-stage stochastic linear programs with recourse

  such as the L-shaped algorithm

  generally apply a single optimality cut on the nonlinear objective at each major iteration

  while the multicut version of the algorithm allows for several cuts to be placed at once. In general

  the L-shaped algorithm tends to have more major iterations than the multicut algorithm. However

  the trade-offs in terms of computational time are problem dependent. This paper investigates the computational trade-offs of adjusting the level of optimality cut aggregation from single cut to pure multicut. Specifically

  an adaptive multicut algorithm that dynamically adjusts the aggregation level of the optimality cuts in the master program

  is presented and tested on standard large-scale instances from the literature. Computational results reveal that a cut aggregation level that is between the single cut and the multicut can result in substantial computational savings over the single cut method.

  Adaptive multicut aggregation for two-stage stochastic linear programs with recourse

  A Stochastic DEVS Wind Turbine Component Model for Wind Farm Simulation

  Yu Ding

  A Stochastic DEVS Wind Turbine Component Model for Wind Farm Simulation

  Ntaimo

  Texas A&M University

  Texas A&M University-Qatar

  TexasA&M University-Qatar

  INFORMS Optimization Society

  University of Arizona

  University of Milan-Biccoca

  Teaching & Research: Industrial & Systems Engineering

  Texas A&M University

  University of Milan-Biccoca

  Milan

  Italy

  Teaching Stochastic Programming\nResearch in Air Traffic Flow Management

  Visiting Professor

  Research Assistant: Mining Robotics and Automation\nResearch Assistant: Systems and Industrial Engineering

  University of Arizona

  TexasA&M University-Qatar

  Teaching Engineering Systems Management

  Associate Professor

  Doha

  Qatar

  Bryan/College Station

  Texas Area

  Professor

  Texas A&M University

  Teaching Engineering Systems Management

  Associate Professor

  Doha

  Qatar

  Texas A&M University-Qatar

  Cluster Chair for Stochastic Programming

  INFORMS Optimization Society