Xiao Liu
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BAC 662 Tempe, AZ 85287-4606
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Mail code: 4606Campus: Tempe
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Xiao Liu is an assistant professor in the Department of Information Systems at Arizona State University. Xiao received her Ph.D. in Management Information Systems from the Eller College of Management at the University of Arizona. Her research interests include data science and predictive analytics in healthcare, education, and fintech. Her work has appeared in several academic journals and peer-reviewed conferences, such as MIS Quarterly, Journal of Management Information Systems, Journal of Medical Internet Research, Journal of the American Medical Informatics Association, and the International Conference in Information Systems, among others.
Ph.D. The University of Arizona
Health Informatics, Social Media Analytics, Public Health Surveillance, Machine Learning, Natural Language Processing.
Jiaheng Xie, Xiao Liu, Daniel Dajun Zeng, and Xiao Fang. “Understanding Medication Nonadherence from Social Media: A Sentiment-Enriched Deep Learning Approach.” Accepted at MIS Quarterly, 2020.
Jiaheng Xie, Zhu Zhang, Xiao Liu, Daniel Dajun Zeng. “Understanding Barriers to Opioid Addiction Treatments from Social Media: A Semantic Network-Based Deep Learning Approach.” Accepted at Journal of Management Information Systems, 2020.
Jessica Sheng, Paul Hu, Xiao Liu, Tingshuo Huang, and Yu-Hsien Chen. “Predictive Analytics for Caring and Managing Acute Disease Patients: A Deep Learning-Based Method to Predict Crucial Complications Phenotypes. ”Accepted at Journal of Medical Internet Research, 2020.
Xiao Liu, Bin Zhang, Anjana Susarla and Rema Padman. “Go to YouTube and See Me Tomorrow: Use of Social Media for Chronic Conditions.” MIS Quarterly Volume 44, Issue 1, 2020, 257-283.
Jiaheng Xie, Xiao Liu, and Daniel Dajun Zeng. “Mining e-cigarette adverse events in social media using Bi-LSTM recurrent neural network with word embedding representation.” Journal of the American Medical Informatics Association 25.1, 2017, 72-80.
Xiao Liu and Hsinchun Chen. “Identifying Adverse Drug Events from Patient Social Media: A Case Study for Diabetes.” IEEE Intelligent System Volume 30, Issue 3. 2015. 44-49.
Xiao Liu and Hsinchun Chen. “A Research Framework for Pharmacovigilance in Health Social Media: Identification and Evaluation of Patient Adverse Drug Event Reports.” Journal of Biomedical Informatics 58, 2015, 268-279.
Funding Source: National Institutes of Health. Grant Title: "Leveraging YouTube Video Analytics for Patient Education on Health Management: A Digital Therapy Tool for Clinicians." Funding Amount: $984k (ASU Share: $262K). Role: ASU Site PI. Duration: 2021-2024.
Courses
2025 Spring
Course Number | Course Title |
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CIS 509 | Analytics Unstructured Data |
CIS 509 | Analytics Unstructured Data |
CIS 509 | Analytics Unstructured Data |
2024 Spring
Course Number | Course Title |
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CIS 509 | Analytics Unstructured Data |
CIS 593 | Applied Project |
CIS 509 | Analytics Unstructured Data |
CIS 593 | Applied Project |
2023 Spring
Course Number | Course Title |
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CIS 509 | Data Mining II |
CIS 593 | Applied Project |
CIS 509 | Data Mining II |
CIS 593 | Applied Project |
CIS 593 | Applied Project |
2022 Spring
Course Number | Course Title |
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CIS 593 | Applied Project |
CIS 593 | Applied Project |
2021 Spring
Course Number | Course Title |
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CIS 593 | Applied Project |
2020 Fall
Course Number | Course Title |
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CIS 415 | Big Data Analytics in Business |
CIS 415 | Big Data Analytics in Business |
CIS 415 | Big Data Analytics in Business |
CIS 415 | Big Data Analytics in Business |