University of Delaware
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Xiao Fang

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Title Professor of MIS, JPMorgan Chase Fellow
Email xfang@nospam687412fa2b20b.udel.edu
Office 357 Purnell Hall
Phone (302) 831-3806
Biography

Biography

Xiao Fang is Professor of MIS and JPMorgan Chase Senior Fellow at Lerner College of Business & Economics and Institute for Financial Services Analytics, University of Delaware. His current research focuses on financial technology, social network analytics and health care analytics with methods and tools drawn from reference disciplines including computer science (e.g., machine learning) and management science (e.g., optimization). He has published in business journals including Management Science, Operations Research, MIS Quarterly and Information Systems Research as well as computer science outlets such as ACM Transactions on Information Systems and IEEE Transactions on Knowledge and Data Engineering. Professor Fang co-founded INFORMS Workshop on Data Science in 2017. He was an associate editor for MIS Quarterly and currently serves on the editorial board of INFORMS Journal on Data Science.

Education

  • Ph.D. in management information systems, University of Arizona
  • M.S. in management information systems, Fudan University, China
  • B.S. in management information systems, Fudan University, China

Select Publications

  • Zhang, H., Zhao, X., Fang, X., and Chen, B. Proactive Resource Request for Disaster Response: A Deep Learning-based Optimization Model. Accepted by Information Systems Research.
  • Yin, K. Fang, X., Chen, B., and Liu Sheng, O. R. Diversity Preference-Aware Link Recommendation for Online Social Networks. Accepted by Information Systems Research.
  • Xu, D., Hu, P., and Fang, X. 2023. A Deep Learning-based Imputation Method to Enhance Crowdsourced Data for Online Business Directory Platforms. Journal of Management Information Systems, 40 (2), pp. 624-654.
  • Zhao, X., Fang, X., He, J., and Huang, L. 2023. Exploiting Expert Knowledge for Assigning Firms to Industries: A Novel Deep Learning Method. MIS Quarterly, 47 (3), pp.1147-1176.
  • Xie, J., Liu, X., Zeng, D., Fang, X. 2022. Discovering Reasons for Medication Nonadherence from Social Media: A Sentiment-Enriched Deep Learning Approach. MIS Quarterly, 46 (1), pp. 341-372.
  • Padmanabhan, B., Fang, X., Sahoo, N., Burton-Jones, A. 2022. Editor’s Comments: Machine Learning in Information Systems Research. MIS Quarterly, 46(1), pp. III-XVIII.
  • Lin, Y. and Fang, X. 2021. First, Do No Harm: Predictive Analytics to Reduce In-Hospital Adverse Events. Journal of Management Information Systems, 38 (4), pp. 1122-1149.
  • Fang, X., Gao, Y., Hu, P. 2021. A Prescriptive Analytics Method for Cost Reduction in Clinical Decision Making. MIS Quarterly, 45 (1), pp. 83-115.
  • He, J., Fang, X., Liu, H., Li, X. 2019. Mobile App Recommendation: An Involvement-Enhanced Approach. MIS Quarterly 43 (3), pp. 827-849.
  • Fang, X., and Hu, P. 2018. Top Persuader Prediction for Social Networks. MIS Quarterly 42 (1), pp. 63-82.
  • Li, Z., Fang, X., and O. R. Liu Sheng. 2018. A Survey of Link Recommendation for Social Networks: Methods, Theoretical Foundations, and Future Directions. ACM Transactions on Management Information Systems 9 (1) Lead Article.
  • Hu, P., Hu, H., and Fang, X. 2017. Examining the Mediating Roles of Cognitive Load and Performance Outcomes in User Satisfaction with a Website: A Quasi-Field Experiment. MIS Quarterly 41 (3), pp. 975-987.
  • Li, Z., Fang, X., Bai, X. and O. R. Liu Sheng. 2017. Utility-based Link Recommendation for Online Social Networks. Management Science, 63(6), pp. 1938-1952.
  • Fang, X., Liu Sheng, O. R., and P. Goes. 2013. When Is the Right Time to Refresh Knowledge Discovered from Data? Operations Research, 61(1), pp. 32-44.
  • Fang, X., Hu, P., Li., Z., and W. Tsai. 2013. Predicting Adoption Probabilities in Social Networks. Information Systems Research, 24(1), pp. 128-145.

Awards & Honors

  • Outstanding Associate Editor, MIS Quarterly, 2021.
  • Finalist, Artificial Intelligence (AI) Health Outcomes Challenge, U.S. Centers for  Medicare & Medicaid Services, 2019-2020
  • Best Paper Award, INFROMS Workshop on Data Science, 2019.
  • Lerner College Outstanding Scholar Award, University of Delaware, 2017.
  • Accounting and MIS Department Faculty Excellence in Research Award, University of Delaware, 2017.
  • INFORMS Design Science Award, 2016.
  • JPMorgan Chase Fellow, 2015-present.

Curriculum Vitae

Download Xiao Fang’s CV (PDF)

Website

Visit Xiao Fang’s Personal Webpage