Enhancing pedagogical practices with Artificial Neural Networks in the age of AI to engage the next generation in Biomathematics

by Jeremis Morales-Morales, Alonso Ogueda-Oliva, Carmen Caiseda, and Padmanabhan Seshaiyer

We propose leveraging both low-code and high-code programming approaches to facilitate a deeper understanding of Physics-Informed Neural Networks (PINNs) among the general student population, using the widely recognized SIR epidemiological model as a motivating example. 

C-MATH with PINN Framework.