Dr. Renta Chintala Bhargavi


Email: bhargavi.r@vit.ac.in

PhD: Anna University

Research Area: Machine Learning, Deep learning

Employee ID50577
Educational details (Please mention all the degrees with latest first)
DegreePassed out yearSpecializationInstitute/University/ College
PhD2014Learning from Event StreamsMIT (Anna University)
M.Tech2004CSEIIT Madras
MSc.Tech1996CSESV University
Research Details
Areas of SpecializationMachine Learning, Deep Learning (Healthcare, Agriculture domains). Exploring other domains
ORCID IDhttps://orcid.org/0000-0001-8319-6851


Scopus IDhttps://www.scopus.com/authid/detail.uri?authorId=36661898100


H-index (scopus)10
Google Scholar IDhttps://scholar.google.com/citations?hl=en&user=AaljAEgAAAAJ


i10 index15
On-going Consultancy Project Details
On-going Consultancy Project TitleFunding Agency
Design and Development of Machine Learning Library for OMLAltair Engineering India Pvt Ltd., Bangalore.
Patent Published Details
Patent Published TitlePatent Published Application No.
Book / Book Chapter Published Details
Prabha, A. J. ., Bhargavi, R. ., & Harish, B. . (2021). An Efficient Machine Learning Model for Prediction of Dyslexia from Eye Fixation Events. New Approaches in Engineering Research Vol. 10, 171–179.BP Internationsl2021
Prabha, A. J., & Bhargavi, R. (2019). Prediction of Dyslexia Using Machine Learning—A Research Travelogue. In Proceedings of the Third International Conference on Microelectronics, Computing and Communication Systems (pp. 23-34). Springer, Singapore.Springer2019
Vaidehi, V., Ravi Pathak, Renta Chintala Bhargavi, Kirupa Ganapathy, C. Sweetlin Hemalatha, A. Annis Fathima, P. T. V. Bhuvaneswari, Sibi Chakkaravarthy S. and Xavier Fernando. “Enhanced Complex Event Processing Framework for Geriatric Remote Healthcare.” Handbook of Research on Investigations in Artificial Life Research and Development. IGI Global, 2018. 348-379. Web. 24 Jun. 2018. doi:10.4018/978-1-5225-5396-0.ch016IGI2018
Bhargavi. R, “Complex Event Processing framework for Big data Applications”, Data Science and Big data computing, Springer, pp. 41 – 56, 2016.Springer2016