Xiuli Qu

TitleAssociate Professor

DepartmentIndustrial and Systems Engineering

Phone336-285-3733

Fax336-334-7729

Emailxqu@ncat.edu

OfficeMcNair Hall
Room: 424

1601 East Market Street
Greensboro, NC 27411

Xiuli Qu

Education

Ph D: Industrial Engineering, Purdue University-Main Campus, 2006

MS: Industrial Engineering, Purdue University-Main Campus, 2002

MS: Electrical Engineering, University of Science and Technology Beijing, 1995

BS: Electrical Engineering, University of Science and Technology Beijing, 1992


Research Interests

Stochastic Modeling and Optimization, Healthcare Engineering, Data Mining and Health Information System, Emergency Response, Renewable Energy/Sustainable Systems, RFID/Wireless Sensor Network Applications


Recent Publications

Leaven, Laquanda  Qu, Xiuli  (2017).  A Two-Stage Stochastic Programming Model for Phlebotomist Scheduling in Hospital Laboratories.  In Sally Brailsford, Paul Harper, Fay Payton and Cindy Le Rouge  (3,  6,  pp. 1-12).  Health Systems.

Qu, Xiuli  Peng, Yidong  Shi, Jing  LaGanga, Linda  (2015).  An MDP model for walk-in patient admission management in primary care clinic.  (168,  pp. 303-320).  International Journal of Production Economics.

Peng, Yidong  Shi, Jing  Qu, Xiuli  (2014).  A hybrid simulation and genetic algorithm approach to determine the optimal scheduling templates for open access clinics admitting walk-in patients.  (74,  pp. 282-296).  Computers & Industrial Engineering.

Leaven, Laquanda  Qu, Xiuli  (2014).  Applying scenario reduction heuristics in stochastic programming for phlebotomist scheduling.  (3,  8,  pp. 1-4).  Management Science and Engineering.

Chapman, Jarrett  Davis, Lauren  Samanlioglu, Funda  Qu, Xiuli  (2014).  Evaluating the Effectiveness of Prepositioning Policies in Response to Natural Disasters.  (2,  5,  pp. 86-100).  International Journal of Operations Research and Information Systems.

Liu, Heping  Shi, Jing  Qu, Xiuli  (2013).  Empirical investigation on using wind speed volatility to estimate the operation probability and power output of wind turbines.  (67,  pp. 8-17).  Energy Conversion and Management.