Application of Mathematical and Computational Models in Biomedical Science

Recent advances in biomedical science and engineering have brought new opportunities to develop novel mathematical and computational models. In this talk, I will present three projects that are related to these opportunities, in particular, focusing on (i) novel cell-based treatments, (ii) advanced biomedical data acquisition technologies, and (iii) bridging mathematics and clinics. In the first part, I will present a hybrid model of agent based and PDE of neural stem cell treatment for the brain. Our model can predict the migratory path of neural stem cells toward different parts of the brain and can be used to compare the treatment efficacy of different injection schemes. In the second part, I will present phenotypic cell state models developed using single-cell transcriptomic data. We demonstrate that the model provides an efficient way to study genetic alterations and predict the leukemic cell state in the blood cell system. In the third part, I will present a framework to determine patient-specific scanning schedules for cancer patients. The patient data collected according to the determined schedule by our methodology show a more accurate prediction of prostate cancer progression.

Bio
https://search.asu.edu/profile/4882967