Kuang Xu

kuang xu
Associate Professor, Operations, Information & Technology

Kuang Xu

Associate Professor of Operations, Information & Technology

Associate Professor of Electrical Engineering (by courtesy), School of Engineering
Botha-Chan Faculty Scholar for 2022–2023

Research Statement

Professor Xu is an expert in operations research, data science, innovation, marketplace and data-driven decision making. His research focuses on fundamental design and managerial principles of decision-making under uncertainty, with wide-ranging applications in marketplace platforms, data science experimentation, transportation and supply chains. Professor Xu has received numerous prestigious academic awards for his research, including a First Place in the INFORMS George Nicholson Paper Competition, a Best Paper Award as well as Outstanding Student Paper Award at ACM Sigmetrics, the premier venue for data-driven performance evaluation and modeling, and the ACM Sigmetrics Rising Star Research Award. His research has been published in leading journals, including Management Science, Operations Research, and Manufacturing & Service Operations Management (MSOM). His research and op-eds have been featured in media outlets including NPR, PBS, USA Today, NBC News and Business Insider. 

Research Interests

  • Decision-Making under Uncertainty
  • Data Science Strategy
  • Operations Research
  • Experimentation
  • AI Innovation in Logistics and Supply Chains
  • Machine Learning and Artificial Intelligence

Teaching Statement

Professor Xu teaches MBA, MSx, PhD, and executive education programs at the Stanford GSB. He developed the Business Analytics course for the GSB MSx program which enables students to use data science and optimization to structure next generation data-powered businesses, improve operational efficiency and drive growth. Professor Xu has also led workshops for executives on innovation, data science, and strategic decision-making in operations, supply chains and logistics. 

Bio

Kuang Xu is a tenured Associate Professor at the Stanford Graduate School of Business. He graduated from Massachusetts Institute of Technology with a Ph.D. in Electrical Engineering and Computer Science and from the University of Illinois at Urbana-Champaign with a Bachelor’s degree in Electrical Engineering. He has been with the Stanford GSB since July 2015. Professor Xu currently serves as an Associate Editor for Operations Research and Management Science.

Professor Xu is an expert in operations research and management, data science innovation, marketplace and data-driven decision making. His research focuses on fundamental design and managerial principles of decision-making under uncertainty, with wide-ranging applications in marketplace platforms, data science experimentation, transportation and supply chains. Professor Xu has received numerous prestigious academic awards for his research, including a First Place in the INFORMS George Nicholson Paper Competition, a Best Paper Award as well as Outstanding Student Paper Award at ACM Sigmetrics, the premier venue for data-driven performance evaluation and modeling, and the ACM Sigmetrics Rising Star Research Award. His research has been published in leading journals, including Management Science, Operations Research, and Manufacturing & Service Operations Management (MSOM). His research and op-eds have been featured in media outlets including NPR, PBS, USA Today, NBC News and Business Insider.

Professor Xu teaches MBA, MSx, PhD, and executive education programs at the Stanford GSB. He developed the Business Analytics course for the GSB MSx program which enables students to use data science and optimization to structure next generation data-powered businesses, improve operational efficiency and drive growth. Professor Xu has also led workshops for executives on innovation, data science, and strategic decision-making in operations, supply chains and logistics.

Professor Xu has served as a senior advisor on AI and data science strategies for a number of industry leaders in ride-sharing marketplaces, delivery and micro-fulfillment, artificial intelligence, logistics and supply chains.

Academic Degrees

  • PhD, Electrical Engineering and Computer Science, Massachusetts Institute of Technology, 2014
  • SM, Electrical Engineering and Computer Science, Massachusetts Institute of Technology, 2011
  • BS, Electrical Engineering, University of Illinois at Urbana-Champaign, 2009

Awards and Honors

  • Botha-Chan Faculty Scholar for 2021–22
  • Business School Trust Faculty Scholar, 2019–20
  • Business School Trust Faculty Scholar, 2018–19
  • Jin Au Kong Award for Best PhD Thesis in Electrical Engineering, MIT, 2014
  • Dimitris N. Chorafas Foundation award for outstanding PhD research, 2014
  • Best Paper Award, as well as a Kenneth C. Sevcik Outstanding Student Paper Award, from ACM SIGMETRICS, 2013
  • First-place winner of the INFORMS George E. Nicholson Student Paper Competition, 2011
  • Ernst A. Guillemin Thesis Award for Best SM Thesis in Electrical Engineering, MIT, 2011

Publications

Journal Articles

Working Papers

Academic Publications

Service to the Profession

  • Reviewer for Operations Research, Management Science, Mathematics of Operations Research, and Annals of Applied Probability

Associate Editor

  • Management Science, Operations Research

Insights by Stanford Business

School News