Alina Faisal

Alina Faisal is a Master of Health Informatics student at the University of Michigan, with a strong focus on data science, machine learning, and UX design. Her academic background includes a Bachelor’s in Economics and Mathematics from LUMS, where she also minored in Computer Science. Alina has a wealth of experience in healthcare automation, leading AI-driven projects at Formstack to reduce administrative burdens and improve patient intake processes. She has worked on machine learning models for cardiovascular risk prediction during her Mitacs Globalink internship, applying advanced feature selection techniques like SHAP and XGBoost to enhance predictive accuracy. Her research in this area has been published in a peer-reviewed journal. 

 

Beyond her work in AI and machine learning, Alina has also been involved in other health-related projects that prioritize user-centered design and technology in healthcare. For instance, she has conducted in-depth user research and developed prototypes for healthcare applications, focusing on improving management for conditions like PCOS. Her health informatics research spans diverse areas, from disease risk prediction to health app usability, all aimed at driving innovation in healthcare and promoting better health outcomes through data-driven approaches.

 

Linkedin Profile: https://www.linkedin.com/in/alina-faisal-2abb871ab/