Minghong Xu portrait

Minghong Xu, PhD

Associate Professor of Practice
Academic AreaInformation Systems
Academic AreaOperations Management & Business Analytics
Areas of InterestInformation Systems

Minghong Xu, Ph.D., is an Associate Professor of Practice at the Johns Hopkins Carey Business School and an affiliated faculty member of the Center for Digital Health and AI (CDHAI). Her current research and teaching interests are in the areas of Big Data And Artificial Intelligence. Dr. Xu develops and teaches courses in machine learning, deep learning, generative AI, and cloud computing.

Education

  • Ph. D, Management Information Systems, University of Illinois - Chicago
  • MS, Revenue and Risk Management, Columbia University
  • BS, Computer Science, University College - Dublin
  • BS, Software Engineering, Fudan University

Research

Selected publications

  • Xu, M., & Bhattacharyya, S. (2021). "Taste Transitivity for Collaborative Filtering: A Stochastic Network Dynamics Approach" Decision Sciences, 52(3), 629-660
  • Xu, M., & Bhattacharyya, S. (2018, June). "Inferring Brand Knowledge from Online Consumer Associative Brand Networks" In Workshops at the Thirty-Second AAAI Conference on Artificial Intelligence, 113-121
  • Xu, M. and Bhattacharyya, S., 2018. "Taste Transitivity for Collaborative Filtering: A Stochastic Network Dynamics Approach" Decision Science, Data Mining and Decision Analytics Special Issue
  • Xu, M. and Bhattacharyya, S., 2018. "Inferring Brand Knowledge from Online Consumer Associative Brand Networks" AAAI Technical Report WS-18-02 pp.113-120
  • Miller, T., de Matta, R., & Xu, M. (2016). "High level inventory network modeling approaches" In Handbook of Research on Global Supply Chain Management, B. Christiansen (Ed.) (pp. 15- 44). IGI Global
  • Miller, T., De Matta, R., Xu, M., 2015. "Practitioners’ High Level Inventory Network Modeling Approaches" Handbook of Research on Global Supply Chain Management (Nov 2015): 15

Working papers

  • Xu, M. and Bhattacharyya, S., "Statistical Inferences on Generative Process of Various Recommendation Networks"

Teaching

Current

  • Generative AI for Business
  • AI Essentials for Business
  • Machine Learning; Cloud Computing

Previous

  • Large Scale Computing with Hadoop
  • Deep Learning with Unstructured Data
  • Information Systems
  • Telecom Cloud and Mobile Applications
  • IT and Global Sourcing Strategy
  • Developing Internet Systems and Services
  • Applied IS Architecture

Honors and distinctions

  • Nexus Award 2024
  • Teaching Innovation Award 2023
  • Dean’s Award for Faculty Excellence 2019
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