Hui Yang, Ph.D.
Professor of Industrial and Manufacturing Engineering, Bioengineering
Abstract: Digital Medicine: In-silico Modeling, Experiments and Analytics for Healthcare Innovations
The Internet of Things (IoT) has propelled the evolution of medical sensing technologies to greater heights. Thus, traditional health systems have been transformed into new data-rich environments. This provides an unprecedented opportunity to develop new analytical methods and tools towards a new paradigm of digital medicine. However, big data arising from healthcare system also pose a significant challenge for efficient and effective sensor-based information processing and medical decision making. In this talk, we will present novel methods and tools about in-silico modeling, experiments and analytics for medical discoveries and healthcare innovations. Specifically, we will demonstrate digital health networks, biophysics-driven models, sensor-based models, statistical models, as well as optimization models to improve the understanding of disease-altered physiological dynamics. Further, treatment plans can be optimized, and life-saving interventions can be delivered in a timely manner. Finally, new pharmaceutical approaches can be designed by imposing genetical and molecular changes that counterbalance the dysfunction due to disease progressions. The new generation of digital medicine is strongly promised to improve the health of our society in the US and in the world.
Department of Industrial & Systems Engineering