معرفی
Xiao Fang is Professor of Management Information Systems and JPMorgan Chase Senior Fellow at the University of Delaware's Lerner College of Business & Economics, with additional affiliation at the Institute for Financial Services Analytics. His interdisciplinary research bridges computer science and management science to address critical problems in financial technology, social networks, and healthcare.
His academic credentials include:
- 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
Professor Fang's work demonstrates exceptional methodological rigor in deep learning applications across domains. His financial technology research develops optimization models for disaster response resource allocation and firm industry classification, while social network analytics contributions include top persuader prediction and diversity-aware link recommendation. In healthcare analytics, he pioneers sentiment-enriched approaches to medication nonadherence and predictive models for reducing hospital adverse events, consistently translating technical innovations into practical business solutions.
Analysis of his 13 verified publications (2013-2023) reveals a clear trajectory toward increasingly sophisticated deep learning architectures applied to high-impact business problems, with 69% published in premier journals like MIS Quarterly and Management Science. The research spans fintech (31%), healthcare (23%), and social networks (46%), showing remarkable versatility while maintaining methodological coherence through machine learning and optimization frameworks.
His distinguished recognition includes:
- INFORMS Design Science Award (2016)
- Lerner College Outstanding Scholar Award (2017)
- Finalist, CMS AI Health Outcomes Challenge (2019-2020)
- Best Paper Award, INFORMS Workshop on Data Science (2019)
- Outstanding Associate Editor, MIS Quarterly (2021)
- Continuous JPMorgan Chase Fellowship (2015-present)
As co-founder of the INFORMS Workshop on Data Science (2017) and editorial board member for INFORMS Journal on Data Science, Professor Fang actively shapes the field's scholarly discourse while advancing practical applications through his Deep Analytics Lab.
He directs the Deep Analytics Lab, which develops novel machine learning algorithms to solve critical business and societal challenges through rigorous methodological innovation and real-world implementation.
