New J-DSP machine learning functions have been developed for data clustering and phoneme recognition. These functions support learning modules for DSP and other classes. A computer project on phoneme recognition was developed, deployed and assessed in the Spring 2018 DSP class. A paper with details and assessments will be presented at the FIE 2018 conference (October 2018)

Publications: A. Dixit, J. Fan, S. Katoch, U. S. Shanthamallu, G. Muniraju, S. Rao, M. Banavar, P. Spanias, A. Spanias, Andrew Strom, "Multidisciplinary Modules on Sensors and Machine Learning" , American Society for Engineering Education (ASEE), Salt Lake City, Utah, 2018. Poster presented at ASEE 2018 can be found here

(Accepted) A. Dixit, U. S. Shanthamallu, A. Spanias, V. Berisha, and M. Banavar, "Online Machine Learning Experiments in HTML5", IEEE Frontiers In Education (FIE), San Jose, California, October 3-6, 2018.

NSF IUSE STEM Grant: Collaborate Research: Integrated Development of Scalable Mobile Multidisciplinary Modules (SM3) for STEM Education. The work at Arizona State University is supported in part by the NSF DUE award 1525716 and the SenSIP Center.