Poonam Kapse
Prof. Poonam KapseAssistant Professor

Computer Science and Engineering (AI/ML) Department of Engineering and Technology, Navi Mumbai

Experience 1


To succeed in an environment of growth and excellence and earn a job which provide me self-development and helps to achieve personal as well as organizational goals.


S.No Degree Year of Passing Name of Institution Class/Grade Percentage (%)
1 M.Tech. ( IT ) 2017 RTM Nagpur University A 65%
2 B.E. ( IT ) 2015 RTM Nagpur University I 61.67%
3 HSC 2010 Maharashtra State Board I 73.5%
4 SSC 2008 Maharashtra State Board I 79.23%
S.No Organization Designation From To Years
1 Bharti Vidyapeeth Deemed to be University,Kharghar Navi Mumbai Assistant Professor 04/12/2022 Present 1
2 SIES Nerul, Navi Mumbai Assistant Professor 15/07/2022 2/08/2022 Less than 1
3 Vishwaniketan’s iMEET, Khalapur Assistant Professor 1/12/2021 14/07/2022 Less than 1
Sr.No. Degree Title Description Percentage
1 M.Tech. (Thesis) An Effective Approach of creation of Virtual Machine in Cloud Computing. Project introduced the need to create virtual machine on same physical machine if required. Ultimately it will reduce the cost of live migration. The scheduling of cloudlets is done by using three algorithms:
  • SJF
  • EDF
  • Credit Based Scheduling Algorithm
2 B.E. Project Multimedia Cryption This project is deals with confidential data transfer in a secured way. The sender hides file or message hide in image, video or audio file. This file is then sent to receiver. If receiver knows the password then only he can get the message otherwise the file will play in given format for providing security three algorithms are used: DES, 3 DES & RSA 65%
Sr.No. Degree Journal/ Conference Details
1 An Effective Approach of Creation of Virtual Machine in Cloud Computing IEEE International Conference ISMAC 2017 ISSN- 978-1-5090- 3243-3/2017
2 Mitigation of Cyber Risk through Digital Forensics Tools IOSR Journal ISSN: 2278-8727
3 An Effective Method for Skin Cancer Detection using Convolutional Kernel Extreme Learning Machine ICOEI Journal ISBN: 979-8-3503-9727-7/2023