Areas of Expertise
- Mobile Health Analytics
- Deep Learning
- Text Mining
- Data Mining
Shuo Yu is a PhD student at the University of Arizona. He is a Research Associate for the Artificial Intelligence (AI) Lab under the direction of Dr. Hsinchun Chen. His dissertation topic lies in mobile health analytics for senior citizens, utilizing motion sensor technologies such as accelerometers to detect adverse events (e.g., falls), assess the severity and predict the risk for chronic conditions (e.g., Parkinson’s Disease). He develops novel deep learning models including two-dimensional heterogeneous convolutional neural networks (2D-hetero CNN) and deep multi-source multi-task learning (DMML) using lab experiment and clinical trial data as well as secondary data from publicly available datasets for more precise, prompt, and personalized senior care. He also has a research interest in data and text mining in cybersecurity, e-commerce, and social media. His work has been published or forthcoming at IEEE Journal of Biomedical and Health Informatics (JBHI), IEEE Intelligent Systems, and AIS Transactions on Replication Research (TRR). He also has a manuscript with a Revise and Resubmit status at Information Systems Research (ISR).
Awards and Honors
Doctoral Consortium, International Conference on Information Systems (ICIS). 2018.
Doctoral Consortium, Conference on Health IT and Analytics (CHITA). 2018.
Doctoral Consortium, Americas Conference on Information Systems (AMCIS). 2018.
Nunamaker-Chen Doctoral Student Scholarship. 2014.