Cong Shi
Home
Research
Curriculum Vitae

Cong Shi

Cong Shi 

Cong (Alex) Shi
Professor of Management and Patrick J. Cesarano Endowed Faculty Scholar
Department of Management
Miami Business School
University of Miami
Coral Gables, FL 33146
E-mail: congshi-at-bus-dot-miami-dot-edu

Biography

Dr. Cong (Alex) Shi is Professor of Management and Patrick J. Cesarano Endowed Faculty Scholar in the Department of Management at Miami Business School, University of Miami. Prior to joining the University of Miami, he was a faculty member in the Department of Industrial and Operations Engineering at the University of Michigan, Ann Arbor, from 2012 to 2023, where he was a tenured Associate Professor. He received his Bachelor of Science degree in Mathematics from the National University of Singapore in 2007 and his Ph.D. in Operations Research from the Massachusetts Institute of Technology in 2012.

Professor Shi's research focuses on the design and analysis of efficient and near-optimal algorithms for operations management, with an emphasis on online learning, reinforcement learning, and artificial intelligence (AI). His work has applications in supply chain management, revenue management, healthcare operations, and human-robot interaction. His research has been recognized with several awards, including those from the INFORMS George Nicholson Student Paper Competition, the INFORMS Junior Faculty Interest Group (JFIG) Paper Competition, the Amazon Research Award, and the Boeing Research Award.

Professor Shi currently serves as an Area Editor for Operations Research, an Associate Editor for Management Science and Manufacturing & Service Operations Management, and a Senior Editor for Production and Operations Management.

Education

Academic Employment

  • Professor of Management, Miami Business School, University of Miami, 2025 – Present

  • Associate Professor of Management (with tenure), Miami Business School, University of Miami, 2023 – 2025

  • Associate Professor of Industrial & Operations Engineering (with tenure), University of Michigan at Ann Arbor, 2019 – 2023

  • Assistant Professor of Industrial & Operations Engineering, University of Michigan at Ann Arbor, 2012 – 2019

Editorial Appointment

  • Area Editor, Operations Research, 2026–

  • Associate Editor, Operations Research, 2024–2026

  • Associate Editor, Management Science, 2021–

  • Associate Editor, Manufacturing & Service Operations Management, 2024–

  • Senior Editor, Production and Operations Management, 2019–

  • Associate Editor, Operations Research Letters, 2015–

  • Associate Editor, Naval Research Logistics, 2022–

  • Department Editor, Naval Research Logistics (Special Issue), 2023–2026

  • Associate Editor, IISE Transactions, 2017–2025

Regular Courses

  • MGT643 Principles of Operations Management

  • MGT303 Operations Management

  • MAS691 Applied Reinforcement Learning

  • MAS631 Statistics for Managerial Decision Making

  • MAS311 Applied Probability and Statistics

  • IOE541/IOE591 Optimization Methods in Supply Chain

  • IOE516 Stochastic Processes II

  • IOE265/STAT265 Probability and Statistics for Engineers

  • IOE202 Operations Modeling

PhD Students

  • Huanan Zhang (co-advised with Prof. Xiuli Chao), 2012–2017
    Dissertation: Data-Driven Algorithms for Stochastic Supply Chain Systems: Approximation and Online Learning
    First Position: Assistant Professor, Harold and Inge Marcus Department of Industrial and Manufacturing Engineering, Penn State University
    Current Position: Assistant Professor, Leeds School of Business, University of Colorado Boulder

  • Yuchen Jiang (co-advised with Prof. Siqian Shen), 2013–2018
    Dissertation: Supply Chain and Revenue Management for Online Retailing
    First Position: Data Scientist, Uber
    Current Position: Machine Learning Engineer, Meta

  • Weidong Chen (co-advised with Prof. Izak Duenyas), 2014–2019
    Dissertation: Online Learning Algorithms for Stochastic Inventory and Queueing Systems
    First Position: Data Scientist, Gap
    Current Position: Sr. Research Scientist, Amazon

  • Hao Yuan, 2015–2019
    Dissertation: Data Driven Optimization: Theory and Applications in Supply Chain Systems
    First Position: Applied Scientist, Amazon
    Current Position: Software Engineer, Google

  • Armando Bernal, 2016–2020
    Dissertation: Pricing in Network Revenue Management Systems with Reusable Resources
    First Position: Data Scientist, Amobee
    Current Position: Data Scientist, PepsiCo

  • Esmaeil Keyvanshokooh (co-advised with Prof. Mark P. Van Oyen), 2015- 2020
    Dissertation: Personalized Data-Driven Learning and Optimization
    First Position: Assistant Professor, Mays Business School, Texas A&M University
    Current Position: Associate Professor, Mays Business School, Texas A&M University

  • Huiwen Jia (co-advised with Prof. Siqian Shen), 2018- 2022
    Dissertation: Adaptive Optimization and Learning for Service Systems
    First Position: Applied Scientist, Amazon
    Current Position: Assistant Professor, Industrial Engineering & Operations Research, University of California at Berkeley

  • Jingwen Tang, 2019-2024
    Dissertation: Online and Offline Learning Algorithms in Operations Management
    First Position: Assistant Professor, Management, Herbert Business School, University of Miami

  • Yaohui Guo (co-advised with Prof. Jessie Yang), 2019-2024
    Dissertation: Trust-Aware Multi-Agent Human-Robot Teaming
    First Position: Software Engineer, Google

  • Shreyas Bhat (co-advised with Prof. Jessie Yang), 2020-2025
    Dissertation: Enabling Effective Human-Robot Collaboration via Trust-Driven Decision-Making
    First Position: Machine Learning Engineer, Motional

Selected Awards

Selected Awards (won by students)