Contact Info

Biography

Webpage: http://users.rowan.edu/~ravi/

Education:
Postdoctoral Fellow, AT&T Bell Laboratories
Ph.D., McGill University
M.E., McGill University
B.E., Concordia University

Impactful Research Areas:
Health
    Computational Health
Education
    Advancing Pedagogical Innovation

Research Expertise:
Digital Speech Processing

Dr. Ramachandran's work in the area of machine learning and artificial intelligence as applied to speech processing. This includes the areas of speech coding, speech enhancement, speech biometrics, speaker recognition and signal to noise ratio estimation. He is also working on vertically integrating machine learning and artificial intelligence topics throughout the undergraduate curriculum.

Professional Membership:
IEEE, Senior Member
ASEE

Recent Publications:
T. Ogunfunmi, R. P. Ramachandran, R. Togneri, Y. Zhao and X. Xia,``A Primer on Deep Learning Architectures and Applications in Speech Processing'', Circuits, Systems and Signal Processing, Vol. 38, No. 8, pp. 3406—3432, August 2019.

K. D. Dahm, R. P. Ramachandran and N. C. Bouaynaya, ``Use of Big Data Analytics in a First Year Engineering Project”, ASEE Annual Conference and Exhibition, Tampa, Florida, June 16--19, 2019.

R. P. Ramachandran, K. D. Dahm and N. C. Bouaynaya, ``Introducing Undergraduates to Pattern Recognition and Machine Learning Through Speech Processing”, IEEE Intl. Conf. on Acoustics, Speech and Signal Processing, Brighton, England, pp. 7635—7639, May 12--17, 2019.

J. Edwards, R. P. Ramachandran and U. Thayasivam, ``Robust Speaker Verification With a Two Classifier Format and Feature Enhancement”, IEEE International Symposium on Circuits and Systems, Baltimore, Maryland, pp. 292—296, May 29--31, 2017.

R. Ondusko, M. Marbach, R. P. Ramachandran and L. M. Head, `` Blind Signal to Noise Ratio Estimation of Speech Based on Vector Quantizer Classifiers and Decision Level Fusion”, Journal of Signal Processing Systems, Vol. 89, No. 2, pp. 335—345, November 2017.