Faculty and ResearchExpert Guide

Education

• Ph.D. in Business Administration
  College of Business, University of South Florida, Tampa, Florida

Areas of Expertise

• Business Analytics Applications
• Managing Distributed Architectures
• Business Application Development
• Computer Software and Technology
• Electronic Commerce Systems
• Systems Analysis and Design

Professional Activities

Lina Bouayad is an assistant professor at the Information Systems and Business Analytics department at Florida International University and a Research Associate at the VA HSR&D/RR&D Center of Innovation on Disability and Rehabilitation Research.  Her research involves the use of analytics in healthcare.  She has experience analyzing patients’ data using natural language processing (NLP) and machine learning (ML) techniques. She currently serves as a co-investigator for several VA HSR&D funded studies.  

Dr. Bouayad has designed and taught several courses related to information systems and business analytics namely Business Analytics Applications, Managing Distributed Architectures, Business Application Development, Electronic Commerce Systems, Computer Software and Technology, and Systems Analysis and Design.

Her professional service includes performing as a reviewer for several top academic conferences such as WITS, ICIS, and JAMIA.

Courses Taught

• Artificial Intelligence for Business
• Business Analytics Applications
• Management of the Information Systems Function
• Managing Distributed Architectures
• Quality and Outcomes Analytics

Refereed Journal Articles

Bouayad, L., Padmanabhan, B., & Chari, K. (2020). Can Cost Transparency in Recommendations Reduce Healthcare Costs? The Role of Time Pressure and Cost-Framing. MIS Quarterly.

Subramanian, H., Cousins, K., Bouayad, L., Alpen, S., & Conway, D. (2020). Blockchain Regulations and Decentralized Applications. Communications of the Association for Information Systems.

Bouayad, L., Padmanabhan, B., & Chari, K. (2019). Audit Policies under the Sentinel Effect: Deterrence-Driven Algorithms. Information Systems Research.

Singh, V. K., Shrivastava, U., Bouayad, L., Padmanabhan, B., Ialynytchev, A., & Schultz, S. K. (2018). Machine learning for psychiatric patient triaging: An investigation of cascading classifiers. Journal of the American Medical Informatics Association : JAMIA, 25.

Fodeh, S. J., Finch, D., Bouayad, L., Luther, S. L., Ling, H., Kerns, R. D., & Brandt, C. (2018). Classifying clinical notes with pain assessment using machine learning. Medical & Biological Engineering & Computing, 56.

Luther, S. L., Thomason, S. S., Sabharwal, S., Finch, D. K., McCart, J., Toyinbo, P., . . . Powell-Cope, G. (2017). Leveraging Electronic Health Care Record Information to Measure Pressure Ulcer Risk in Veterans With Spinal Cord Injury: A Longitudinal Study Protocol. JMIR Research Protocols, 6.

Bouayad, L., Ialynytchev, A., & Padmanabhan, B. (2017). Patient Health Record Systems Scope and Functionalities: Literature Review and Future Directions. Journal of Medical Internet Research, 19.