Academics

Bio

Prof. Vandana Jagtap is an Assistant Professor at Dr. Vishwanath Karad MIT World Peace University, Pune, India. She has an M.Tech degree in Computer Science & Engineering from the University of Pune and is currently pursuing her Ph.D. in the same field. With 23 years of teaching experience, her areas of interest include Advanced Machine Learning, High-performance Computing, Distributed and Parallel computing, Cloud Computing, Algorithms, and Assistive Technology. Prof. Jagtap is the author of the book "Cloud Computing Policies, Outsourcing and Computing Keys: Cloud Computing policies" and has 50+ research publications in refereed international journals and conferences. She has also reviewed many refereed International journals and worked as an Advisory member and Editorial Board Member. Prof. Jagtap has delivered many expert lectures and is a member of various professional bodies such as ACM, CSI, ISTE, IEI. Under her guidance, 25 B.Tech (CSE) Project Groups and 13 M.Tech (CSE) Scholars have completed their projects.

Research Area
Machine Learning, Artificial Intelligence, Data Science

Publication
SSN 1877-0509,https://doi.org/10.1016/j.procs.2015.04.209.
2. Comparative Study of Machine Learning Approaches for Heart Transplantation. In: Saini, H., Sayal, R., Govardhan, A., Buyya, R. (eds) Innovations in Computer Science and Engineering. Lecture Notes in Networks and Systems, vol 74. Springer, Singapore. https://doi.org/10.1007/978-981-13-7082-3_47
3.AFMEACI: A Framework for Mobile Execution Augmentation Using Cloud Infrastructure. In: Kumar Kundu, M., Mohapatra, D., Konar, A., Chakraborty, A. (eds) Advanced Computing, Networking and Informatics- Volume 2. Smart Innovation, Systems and Technologies, vol 28. Springer, Cham. https://doi.org/10.1007/978-3-319-07350-7_49
4. Early prediction of breast cancer from mammogram images using classification
methods: a comparison, Open Access Published by De Gruyter 2019, https://www.degruyter.com/document/doi/10.1515/9783110628517-007/html?lang=en
5. Low-frequency detection of FRB180916 with the uGMRT, https://ui.adsabs.harvard.edu/abs/2020ATel13781....1S/abstract
6. Dependency Analysis for Secured Code Level Parallelization, Procedia Computer Science,Volume 78,2016,Pages 831-837,ISSN 1877-0509,
https://doi.org/10.1016/j.procs.2016.02.067.

Google  scolar link
https://scholar.google.com/citations?user=cj8DdQgAAAAJ&hl=en

Scopus  link
https://www.scopus.com/authid/detail.uri?authorId=56308121700

Orcid Link
​https://orcid.org/0000-0002-9857-0727